Improved treatment planning for children

Abstract

The invention relates to a computer-implemented method for providing treatment readiness data (BBD) of a child to be treated in preparation for medical treatment, comprising the steps - Acquisition (S11, S21, S31, S41) of input data (ED), whereby the input data (ED) - a treatment statement relating to the medical treatment to be carried out, - an indication of the child’s age and / or sex, and - include at least one exercise parameter characterising an exercise activity of the child, - applying (S12, S22, S32) a first trained function (TF1) to the input data (ED), thereby generating the treatment readiness data (BBD), - Providing (S13, S23, S33) the treatment readiness data (BBD) to clinical staff in the treating medical facility.

Description

Over 10 percent of all medical imaging examinations are performed worldwide on patients under 18 years. However, the error rate in pediatric MRT studies with children between two to five years is at least 50 percent. In children between six and seven years, the failure rate is about one third. In the field of computed tomography or other x-ray x-ray radiography in children, a similar trend for pediatric examinations can be derived. Medical therapeutic measures in which a high patient cooperation is required, for example irradiation of pathological tissue, are also typically more difficult for children.An important reason for this is the repellency behavior, such as wines or chappels, which is frequently more pronounced in children during the examination or treatment.Those cases in which, with a consideration of the child age and the correspondingly expected defense behavior and the medical problem / diagnosis, an imaging examination or treatment is completely disregarded and thus no reliable radiology diagnosis is made or treated at all are completely ignored in this consideration.The usually strong physical movements of the children impair the imaging on the one hand and cause artifacts in the medical image data. These must subsequently be removed from the image data again by complicated and time-consuming correction algorithms, which delays the imaging process. However, in the case of more severe motion artifacts, the imaging examination must be completely repeated. The defense behavior of children frequently slows down the medical workflow considerably, which makes it less effective-individual examinations require an unscheduled longer time, have to be repeated and thus reduce the patient throughput of a medical device overall. This entails economic disadvantages for the medical device, but also an increased stress level for the medical personnel and for the patient or the attendant thereof. Similarly, it is particularly important for the performance of therapeutic measures, for example when irradiating pathological tissue with X-ray or particle beams, to move hardly in order for the radiation to reach the pathological tissue.For this reason, children under six years are often prepared with sedatives or in general anaesthesia for the medical measures. However, the use of sedatives or general anaesthesia is not a guarantee of successful performance, because in the case of a large proportion of the sedated children the sedation is insufficient, so that the children nevertheless move excessively and the treatment fails.Moreover, the use of sedatives and general anaesthesia poses health risks, not only but in particular for children.In addition, the preparation of the child with sedatives and the medical treatment itself are correspondingly more cost-consuming and time-consuming, since in addition to the sedative, corresponding personnel and / or apparatus for carrying out the sedative and monitoring of the child state must be ensured during the entire treatment. Waiting times for a treatment deadline thereby become longer. This in turn negatively influences the patient experience.The evaluation of performance and quality of health organizations has recently gone beyond an investigation of the quality of clinical care alone, and more and more patient experience is also considered an important indicator and is included in the evaluation. The inclusion of patient experiences as a column of quality is often populated with intrinsic values.It is obvious that, in particular in children, adequate patient preparation including their parents and / or care persons can lead to a better and more efficient examination in the sense of shorter or less treatment times, less stress for all participants and possibly also less necessary sedatives.Currently, in children (up to 9 years), the preparation of medical imaging examinations is limited to grouping the child according to their age and deciding whether or not a sedative must take place, taking into account the medical / clinical question, i.e. the planned medical imaging. The children are not considered psychologically, cognitively or emotionally, although parents and / or clinicians would wish to do so. In addition, the needs or competences of the parent / caregivers are not taken into account.Individual clinics are more complicated in order to be able to better assess children emotionally and cognitively before medical imaging. For example, additional information about the child is queried or knowledge about the examination process is communicated via individual telephone calls. This, in turn, is very resource-intensive and not standardized or structured.Solutions in the form of app applications are also known, with which children in a familiar environment, for example at home, can be prepared for an imaging examination by conveying them via the app, for example, the examination sequence or information about the imaging system or by allowing them to perform breathing or relaxation exercises online and thus train the actual examination situation.These solutions focus the patient or his private environment and are directed to bringing about a type of habituation effect or routine with regard to an pending imaging examination.However, a technical system is lacking which is designed to indicate to the clinician a "preparation status" of a child or family.In contrast, it is an object of the present invention to provide means for efficient patient preparation and treatment planning. In particular, it is the object of the present invention to provide technical aids to medical personnel, by means of which aids a mood and / or a general treatment readiness of a child patient and / or of the associated care persons can be better detected. In particular, it is also an object of the present invention to enable an improved, as predictive, examination planning on the basis of the detected mood state or the examination readiness.This object is achieved by a method for providing treatment readiness data of a child to be treated in preparation for a medical treatment, a corresponding system for providing treatment readiness data of a child to be treated in preparation for a medical treatment, and a corresponding computer program product and corresponding computer-readable storage medium according to the independent claims. Preferred and / or alternative advantageous embodiment variants are the subject matter of the dependent claims.The solution of the object according to the invention is described below with reference to the method claimed and also with reference to the devices claimed. Features, advantages or alternative embodiments mentioned here are likewise also to be transferred to the other claimed subject matters and vice versa. In other words, the subject claims (which are directed, for example, to a method) can also be further developed with features which are described or claimed in connection with one of the devices. The corresponding functional features of the method are formed by corresponding physical modules or units.The present invention relates to a method for providing treatment readiness data of a child to be treated in preparation for a medical treatment. The method comprises a plurality of steps. The method is designed as a computer-implemented method.A first method step is directed to acquiring input data. The input data includesa treatment specification relating to the medical treatment to be carried out,an indication characterizes the age and / or sex of the child, andat least one exercise parameter indicative of an exercise activity of the child.A further method step is directed to applying a first trained function to the input data, whereby the treatment readiness data are generated.A further method step is directed to providing the treatment readiness data for a clinic personnel in the treating medical facility.In embodiments, the method comprises further method steps. The method is therefore not limited to the steps carried out.A medical treatment is to be understood in the sense of the invention as a medical imaging examination by means of a medical imaging system such as a computed tomography system, a magnetic resonance tomography system, a fluoroscopic x-ray system, an ultrasound device, a positron emission system or the like. The medical imaging system is configured to generate medical image data of at least one body region of the child to be treated. Within the meaning of the invention, a medical treatment is also to be understood as meaning a medical therapeutic measure or a medical intervention, preferably medical imaging. This can include, for example, a therapeutic irradiation by means of X-ray or particle radiation or medical therapeutic interventions such as biopsy extraction or the like. In particular, for medical treatment, it may be necessary to administer a contrast agent to the child to be treated in order to emphasize body regions of the child to be displayed.A treatment specification thus describes one or more items of information in the form of data and / or parameters which unambiguously determine a medical treatment. The treatment specification comprises, for example, the information as to whether it is an imaging treatment or a therapeutic or interventional treatment. In another embodiment, the treatment specification comprises whether it is a computed tomography examination or a magnetic resonance tomography examination or the like. In a further embodiment, the treatment indication comprises information about the medical question or indication, for example which body part of the child is to be treated.The child to be treated is understood as a child patient. In this respect, without limiting generality, a patient as a treatment object is assumed below, which is a human. In the following, therefore, the two terms "child", "child to be treated" and "patient" are used interchangeably. In addition to individual, person-related details, the child can be assigned an age and / or a sex. The age of infant patients is between zero and 18 years old, in particular the present invention relates to infant patients between one to 10 years old, particularly preferably infant patients between two to five years old.In an application of a medical treatment, it is provided according to the invention that the child prepares for the medical treatment. For this purpose, the child is provided with exercise material comprising games, exercises and / or information materials that can perform, finish and / or carry out it. Games may involve, for example, performing trial treatment to make the child familiar with the course of the medical treatment. Exercises can be carried out, for example. These may be breathing or relaxation exercises, for example, in order to train the air stoppage for a medical imaging examination in a targeted manner over a predefined period of time. The information material can relate, for example, to the treatment facility itself and can comprise helpful information in order to make the child familiar with the treatment facility. For example, the information material can represent the functioning of the treatment system and / or explain sounds or signals occurring during the treatment. The exercise material is adapted in particular to the age of the child in order to achieve the best possible exercise effect. The exercise material is thus adapted in a preferred embodiment to the medical treatment to be performed and at least partially personalized for the child. The training material is preferably provided virtually via a user terminal such as a computer, a tablet or a smartphone. For example, when a deadline for medical treatment is agreed, the child and / or a care person, such as a parent or the like, is provided with an Internet address or a QR code, with the aid of which access to the training material can be obtained via the user terminal. According to the invention, exercise activity of the child is continuously monitored in preparation for the treatment term.Additionally or alternatively, it can be provided within the scope of the treatment preparation that the child (together with his care person) performs exercises on site in the medical facility at an exercise treatment facility (=mock-up system) and the exercise treatment facility is designed to acquire user information of the child input during the exercise, for example in the form of an exercise activity via an operator interface such as a touch screen or operator buttons, and to transmit it for processing according to the invention.According to one aspect of the method, the acquisition of the at least one exercise parameter typically comprises an exercise activity, generating it based on or from the exercise activity for the child. The exercise parameter can be designed, for example, in the form of a percentage value which describes how much of the provided exercise material has already been completed by the child. The training parameter can alternatively or additionally also specify a training duration or a training frequency. For example, the exercise parameter can specify how often a child has performed one of the games and / or one of the exercises or how long it has in each case required for it. In embodiments, individual training parameters or a combined training parameter can be generated in each case for the training effort, the training duration and / or the training frequency. The exercise parameter may be in the form of a numerical, alphanumeric or alphabetical parameter.As input data, the method according to the invention also considers details about the identity, age, sex, mother's speech, nationality and / or the like of the child. This information serves on the one hand to unambiguously identify the child; for this purpose, the name and the birth date can serve in particular. On the other hand, these details can be used to adapt the at least one treatment specification specifically for the child. For example, some imaging methods for children below a defined age are not considered. Other methods must then be used. Furthermore, these details serve to adapt or select the provided training material for the patient preparation with regard to the language, age and / or sex of the child.In the method step of acquiring, in particular, the input data is acquired or provided for further processing of the input data. The acquisition of the input data can comprise, in particular, a reception of the input data. In this case, input data can be provided partially, in particular by the child or a care person, via the user terminal. Alternatively or additionally, the input data can be input at least partially by a clinician via a corresponding operator or input interface. The clinician can be a person of medical-technical assistance, a treating physician, for example a radiology doctor or an anesthetic doctor, or a person of the caregiver. Alternatively or additionally, the input data can be at least partially recorded, i.e. transmitted or called up, or taken over from an electronic hospital record, by an internal database, for example a hospital or radiology information system (HIS / RIS).According to one aspect of the invention, the treatment readiness data generally indicate a measure of a treatment readiness and / or a preparation level of the child with respect to the pending treatment. In this regard, the treatment readiness data allow a prediction of how time-consuming and / or care-intensive the pending treatment will proceed. With respect to the exercise material, the treatment readiness data indicate how intensively the child has become familiar with the pending treatment and how well he has prepared for the treatment.According to the invention, treatment readiness data are generated on the basis of the input data. This takes place in the method step of applying the first trained function to the input data.In general, a trained function mimics cognitive functions associated with humans with human dementia. In particular, training based on training data allows the trained function to adapt to new circumstances and to recognize and extrapolate patterns.In general, parameters of a trained function can be adapted by means of training. In particular, supervised (supervised) training, semi-supervised (semi-supervised) training, unsupervised (unsupervised) training, reinforcement learning (reinforcement learning) and / or active learning (active learning) can be used for this purpose. Moreover, representation learning (an alternative term is "feature learning") (representation learning) may be used. In particular, the parameters of the trained functions can be iteratively adjusted by a plurality of training steps. Particularly preferably, the parameters of the trained function can also be later adjusted by means of a feedback loop during use of the trained function.In particular, a trained function may comprise a neural network, a support vector machine (support vector machine), a random tree or a decision tree (decision tree) and / or a Bayesian network, and / or the trained function may be based on k-means clustering (k-means clustering), Q-learning, genetic algorithms and / or association rules. In particular, a trained function can comprise a combination of a plurality of uncorrelated decision trees or an ensemble of decision trees (random forest). In particular, the trained function can be determined by means of XGBoosing (extreme gradient boosting). In particular, a neural network may be a deep neural network (deep neural network), a convolutional neural network (convolutional neural network) or a convolutional deep neural network (convolutional deep neural network). Moreover, a neural network may be an adversarial network (deep adversarial network), a deep adversarial network (deep adversarial network), and / or a generative adversarial network (generative adversarial network). In particular, a neural network can be a recurrent neural network (recurrent neural network). In particular, a recurrent neural network may be a long-short-term-memory (LSTM) network, in particular a gated recurrent unit (GRU). In particular, a trained function can comprise a combination of the described approaches. In particular, the approaches described here for a trained function are called the network architecture of the trained function.The first trained function performs a weighting of individual input data on the basis of its numerous parameters and converts these into the treatment readiness data according to their individual weighting. All captured input data can consequently be included by the first trained function with individual weights in the determination of the treatment readiness data. The individual weighting factors can correspond in embodiments to local or national specifications and can also differ or be adapted from medical device to device.In the method step of providing the treatment readiness data, these are provided in particular to the clinical staff, for example to an attending or attending physician or to a medical-technical assistance staff. In this case, the provision of the treatment readiness data can comprise, in particular, a display of the treatment readiness data and / or a sending of the treatment readiness data, for example via e-mail or SMS, and / or an at least temporary storage of the treatment readiness data in a memory or a database or a cloud memory.In particular, it can be provided that the hospital staff can access the treatment readiness data via a web app. This allows flexible access to the treatment readiness data, regardless of a current location of the clinician. When accessing via a mobile tablet computer or a smartphone, the presence of the clinical staff in the medical facility is not even necessary. Access via a web app also has the advantage that it can be effected at any desired time and in particular repeatedly or multiple times within a preparation period by the clinician. In this respect, the method according to the invention also allows observation of a development of the treatment readiness data. Alternatively, the providing may comprise outputting the treatment readiness data to the clinician as an integral part of a treatment facility software in the form of a web API (API=application programming interface=application programming interface) via an output interface of the facility or a fixed facility workstation with close reference to the respective treatment workflow. The incorporation of the method according to the invention into a piece of equipment software presupposes the on-site presence of the clinician.By acquiring input data according to the invention, generating treatment readiness data and providing these treatment readiness data to the clinic personnel, the present invention opens up the possibility of including the treatment readiness determined for the child in the treatment planning, because with well prepared children less delay due to consulting and / or care is likely required during the treatment than with less prepared children. The method according to the invention consequently makes the treatment readiness data usable or accessible for the treatment planning, so that a treatment planning can be improved in the sense that it can be more accurately aligned with the actual requirements of the child.In a further aspect of the invention, the input data also comprise a mood parameter characterizing at least one personal and / or emotional property of the child. The consideration of a mood parameter in the context of the input data is based on the realization that although the expression of different personal and / or emotional properties varies with the age of a child, the individual deviations appear to be significantly greater from child to child and independent of the age, for example due to different environments in which children are embossed. For example, a three year child can go more muted and more open to a treatment than an eight year child.Personal or emotional properties can be, for example, the following properties, which can describe the character of a child: open / closed, new-generic / disinterested, anxiety / mutyg, excited / relaxed, kind / aggressive, etc. The list of the mentioned properties can be continued as desired and should not be understood as exhaustive. The various properties or their form can be represented, for example, in each case via a numerical, alphanumeric or alphabetical value, for example, a particularly neugy child can be assigned an 'N+3', a particularly desinterested child can be assigned an 'N-3', a particularly mutty child can be assigned an 'M+3', a particularly anxiety child can be assigned an 'M-3', or the like. In between, depending on the characteristic, for example, can be formed. Thus, values between '+2' and -2' may be assigned at intervals of integers. The mood parameter can be designed to aggregate the individual values for the detected properties to form an overall value or to comprise the individual values in the sense of a property vector, wherein each property forms a dimension of a property space.In embodiments of the method, acquiring a mood parameter can comprise acquiring the individual property values, for example via the user terminal, at which the property values are input by the child or a care person. Alternatively, the mood parameter is acquired by the clinician inputting the property values in the presence of the child and / or the caregiver. In embodiments of the method, the acquisition can also comprise converting or calculating the mood parameter or the mood parameter from the property values. Mood parameters and / or property values may also be acquired as input data with respect to the caregiver in embodiments.In embodiments, the acquisition of the input data also comprises an acquisition of mood parameters and / or emotional properties with respect to earlier, i.e. already completed, treatments of the child. The collection may in these cases comprise input of this input data by the clinician involved in performing the previous treatments. Or, the input data may be retrieved from an electronic patient record and / or a HIS / RIS.Taking into account the mood parameter in addition to the training parameter can further improve the treatment planning, because a care intensity for the child can be predicted even more accurately on the basis of the mood parameter.A further aspect of the method further provides that the input data also comprise a participation parameter characterizing a participation readiness of at least one care person of the child. This procedure is based on the realization that the behavior or the setting and / or emotions of a child are significantly influenced by the behavior and embossing of the parent or respectively next-standing care persons. In addition, at least one care person is generally also an attendant in medical treatment, which can necessitate increased care expenditure by the clinician in the treatment situation in addition to the child. In this respect, it can also be provided for at least one caregiver to generate and provide a mood parameter via a corresponding property profile, as already illustrated above with respect to the child, by corresponding input at the user terminal.According to a further aspect of the method, it can be provided to generate the participation parameter based on a quantity of information material which the caregiver has read and / or based on the exercise parameter and / or the exercise activity of the child. Material in the form of information material is also offered to the parent or the care person in preparation for the medical treatment, which material can be viewed, read through or listened to. The informational material is intended to bring the care giver closer to the course of the medical examination, to answer questions in advance, to present risks and side effects, or many more. The contributing parameter can take into account which information material has been processed, how often it has been processed, or how much time it has taken the processing. The information material can be provided in the form of texts, for example an info brochure in pdf format or the like or also as a hearing book. In embodiments of the invention, access to the information material preferably also takes place via the user terminal and, for example. QR code. The participation parameter can also take into account the training activity or the training parameter of the child. The invention assumes that the caregiver has a great influence on the infant's exercise activity. Thus, the greater the participation parameter, the more cooperative the attending person is perceived, wherein the invention assumes that the latter in turn positively influences the treatment readiness of the child, so that a treatment duration can be expected to be set shorter in time in the planning. The contributing parameter can consequently also be designed as a numerical, alphanumeric or alphabetical value.In a further aspect, information on earlier medical treatments of the child can also be taken into account or acquired as input data. These can be called up from a HIS or RIS, for example, or provided by a physician. These may be, for example, possible. Information on earlier sedatives of the child relates to. These details may be provided as input data from an anesthetist.In further aspects, a procedure can be that, according to the method, further input data from an anesthetist are taken into account, which data relate, for example, to a medical history of the child and which data relate, for example, to the type or duration of a possible sedative action of the child during the pending medical treatment.Based on this type of input data, according to the invention, the treatment readiness data and / or the recommendations for action can be adapted even better to an individual patient and even better predictions can be made about the pending treatment.As described at the beginning, the various input data are weighted in the step of ascertaining treatment readiness data. The individual weighting factors can differ from trained function to trained function and / or from training iteration to training iteration. In particular, they can differ by individual user specifications and / or local customs or from clinic to clinic. The weighting factors can also be determined by the type of input data. Thus, for example, a weight for current mood parameters or current emotional properties of the child can always be greater than a mood parameter or emotional property for earlier treatments of the child, because the earlier details can be in the meantime "adult" in the sense of. In particular, the weights for input data relating to the child can be weighted higher than input data relating to the caregiver, for example the participation parameter or mood parameter relating to the caregiver.If a child or his care person does not show any or hardly any preparatory activity in the request for a treatment, this input data enters into the ready-to-treat data with a higher weighting than input data identifying a better preparatory activity. In this way, according to the invention, the treatment planning can provide longer treatment times or more personnel, for example, for the sake of safety, in order to ensure a success of the treatment.It can likewise also be used with input data which can be concluded from a continuous processing of the training and information material or a continuous indication of emotional properties or emotional parameters. These are preferably weighted higher, since they represent the actual properties of the infant patient or the care person rather than representing one-time information which has a greater risk of representing just one snapshot.According to a particularly preferred aspect of the method, the provision of the treatment readiness data comprises visually displaying the treatment readiness data to the clinic personnel via an output device.Depending on the complexity of the information used as input data regarding the child or the at least one care person, the treatment readiness data can be embodied to be more or less clear. In particular, the information for identifying the child is also typically required as individual information in order to indicate to the clinician which patient is about. In this respect, the visual display of the treatment readiness data can comprise arranging it in a type of patient dashboard and outputting the input data at least partially individually as the numerical, alphanumeric or alphabetical values as they are present. Particularly preferably, however, the remaining treatment readiness data are transferred in particular into a type of diagram. A diagram for the child and a diagram for the at least one caregiver can be provided in each case. Alternatively, a correspondingly multi-dimensional diagram representative of the family or group of people comprising the child to be treated can be provided. The output is then in turn effected via a display device, for example in the form of a monitor, on one of the output devices already listed above. This type of display has the advantage that a preparation status of the patient or a treatment readiness can be detected optically more quickly or more easily than parameter values can be checked individually. Particularly suitable are, for example. Circle or spider plots can easily represent any dimensionality corresponding to the variety of input parameters.In embodiments, the first trained function is configured to convert the treatment readiness data according to the input data taken into account directly into presentation information according to a patient dashboard or at least one treatment readiness diagram.In order to simplify the treatment planning on the basis of the treatment readiness data for the clinic personnel even further and to shorten the planning time, a particularly preferred aspect of the method further comprisesapplying a second trained function to the treatment readiness data, whereby at least one action recommendation for treatment planning is generated, andproviding the hospital staff with the recommendation for action together with the treatment readiness data.The second trained function can in this case basically be embodied like the first trained function as described at the beginning. In particular, the second trained function can be comprised by the first trained function. In particular, the first and the second trained function can be combined in a treatment planning algorithm. In particular, the treatment planning algorithm or the second trained function for determining the at least one recommendation for action can comprise a sequence recognition algorithm (sequence mining). Patterns in partially structured data can be recognized in this case. To determine the at least one action recommendation, the second trained function can comprise in particular a "natural language processing" for the analysis of text data or alphabetical data or alphanumeric data.In embodiments, the first trained function establishes a functional relationship between the input data as described above and the treatment readiness data. The input data therefore represents the input data and the treatment readiness data represents the output data of the first trained function. In embodiments, the second trained function establishes a functional relationship between the treatment readiness data and the at least one recommendation for action as described above. The treatment readiness data therefore represent the input data and the recommendation for action represents the output data of the second trained function. In embodiments in which the first and the second trained function are combined in a treatment planning algorithm, the treatment readiness data represent both an intermediate result and output data of the treatment planning algorithm.The invention optionally also relates to a computer-implemented method for providing a first and / or second trained function. The method comprises a method step of providing first and second training input data, respectively, wherein for training the first trained function the first training input data can comprise the above-described input data and for training the second trained function the second training input data can comprise already existing treatment readiness data. The method also comprises the method step of providing first and second training output data, respectively, wherein the first training output data of the training of the first trained function comprises treatment readiness data and the second training output data of the training of the second trained function comprises at least one recommendation for action. In this case, the training output data and the training input data are each related to one another. The method also comprises the method step of training the first trained function and the second trained function, respectively, based on the training input data and the training output data. The method also comprises the method step of providing the first and / or the second trained function for use in the method according to the invention for providing treatment readiness data and / or recommendations for action.In particular, the training input data and the training output data can be created, compiled or selected in advance by an expert or a user. Specifically, the training input data and the training output data relate to a period in the past. In particular, earlier treatment readiness data or earlier action recommendations with respect to the training input data for generating training output data are already known to the expert or user. In particular, the training output data can be derived by the expert or the user from the training input data. In particular, the training input data and the training output data are thus related to one another.In particular, in the method step of training the first trained function and / or the second trained function, the training can be carried out by means of supervised learning (supervised training) or unsupervised learning (unsupervised training). In particular, the supervised learning may include random over / undersampling (random over / undersampling) or synthetic minority oversampling (artificial minority oversampling). In particular, the supervised learning may alternatively or additionally comprise cost-sensitive learning (cost-sensitive learning). The unsupervised learning may include, in particular, abnormality detection (abnormality detection) using a deep autoencoder model (deep autoencoder model).The inventors have recognized that past data may be used as training input data. In particular, the inventors have recognized that the training output data for the past can be created by an expert or user and can be based on actual treatment readiness data, actual action recommendations or an actual treatment success in the past.According to further aspects of the method, the derived action recommendations may include the following different recommendations. In particular, combinations of different of the aforementioned recommendations can be derived in each case on the basis of the treatment readiness data. In particular, individual recommendations can also call for a further recommendation in each case. A recommendation is directed to adapting the planned treatment duration, i.e. shortening or lengthening the planned treatment duration. A further recommendation is directed to or against a sedative effect of the child under treatment. A further recommendation takes into account the type of sedative, i.e. the sedative to be used and the device or equipment necessary for this. Another recommendation may recommend a number of required clinicians. A further recommendation can propose, for example, depending on the required hospital personnel including anaesthesia, a specific treatment room which has, for example, the required size. Another recommendation may be directed to proposing a specific treatment system and / or a specific treatment protocol, for example a specific imaging protocol with a plurality of specific treatment or protocol parameters. Depending in particular on an availability of an anesthetist and / or the clinician and / or a treatment room and / or a treatment facility, a recommendation can also be directed to a deadline shift to another date or time. In order to facilitate access to the child in the treatment situation, a further recommendation can be directed to the use of an additional equipment for the child, for example in the form of a playing piece, an inserter, a mask pot, a book or the like.The inventors have recognized that action recommendations for an improved course of treatment advantageously go beyond a recommendation for or against a sedative of the child. Instead, according to the invention, it is provided that the treatment plan can be optimally adapted to the entirety of all input data by the at least one recommendation for action being optimally adapted to the input data.The invention further relates to a computing unit for determining a tissue function of a tissue in a region of interest of an examination object, comprising means for carrying out the method according to the invention.The invention also relates to a medical imaging system having a computing unit according to the invention. The computing unit is advantageously integrated into the medical imaging system. Alternatively, the computing unit can also be arranged remotely. The computer unit can be designed to carry out, in particular, the step of ascertaining a function parameter relating to the tissue function for each of at least two tissue regions, but also the entire method according to the invention, for a medical imaging system or for a multiplicity of systems, e.g. in a radiology center or hospital comprising a plurality of magnetic resonance systems.In a particularly preferred aspect, the method also provides for a treatment facility to be controlled during the performance of the medical treatment according to the recommended treatment protocol. In other words, according to the invention, control commands corresponding to the plurality of protocol parameters of the recommended treatment protocol are generated for the treatment installation and transmitted to the treatment installation for execution. The control commands corresponding to the protocol parameters can relate, for example, to a positioning and / or movement of a moving component of the treatment system, for example the positioning of a patient couch or an X-ray source or an X-ray detector, for example a feed movement of the patient couch under an imaging procedure. The control commands can alternatively relate to a beam triggering or the setting of a specific x-ray tube current or the like.According to a further aspect of the method, it also comprises adetermining provisional treatment readiness data representing a provisional treatment readiness of the child at a defined time interval before the medical treatment by applying the first trained function to the input data,comparing the provisional treatment readiness with a predefined threshold value for the treatment readiness and, if the threshold value is undershot,generating an exercise and / or participation request, andproviding the training and / or participation request for the child and / or the care person.The defined time interval can be set manually in advance, for example according to individual user specifications or preferences or according to specifications of the medical device, or can be specified by the system according to the invention. Preferably, the defined time interval is two weeks, one week or the like. In this way, sufficient time is advantageously granted between the determination of the provisional and an actual treatment readiness (at the time of the medical treatment).The determination of the provisional treatment readiness data by the first trained function differs only by the time from the determination of the treatment readiness data already described above (at the deadline or at the time of the medical treatment or shortly before it). In these embodiments, the method according to the invention consequently comprises two steps of determining treatment readiness data which are carried out separately from one another or one after the other in time by the defined time interval.The provisional treatment readiness is then compared with a threshold value for the treatment readiness, which threshold value is likewise predefined in advance. The threshold value corresponds to a minimum treatment readiness, which must result from the input data below which medical treatment appears only moderately meaningful with regard to workflow efficiency or treatment success. If this threshold value is undershot, according to the invention an exercise or participation request is generated, for example in the form of a message, for example in the form of an email or an SMS or the like, and is provided, for example sent, to the patient or the caregiver. The practice / participation request is used to attempt to draw the attention of the child and / or the caregiver to not yet completed / performed exercises or games or not yet processed information material. The inventors have recognized that, on the basis of the determination of the provisional treatment readiness data, an influence can still be taken in good time on a previously inadequate training and preparation activity in order to achieve a better treatment performance and a better treatment success. In embodiments, a plurality of defined time intervals can be provided and the step of determining preliminary treatment readiness data can be carried out a plurality of times, each at one of these points in time, in order to achieve optimum preparation of the child.Optionally, according to the invention, together with the determination of provisional treatment readiness data representing a provisional treatment readiness of the child, at least one provisional recommendation for action at the first defined time interval before the medical treatment can also be derived by applying the second trained function to the provisional treatment readiness data. In this way, the clinician can also perform preliminary treatment planning, which then only needs to be finally adapted to individual changes.The application of the second trained function differs here only in the point in time, as already described above with reference to the first trained function.According to a further aspect of the method according to the invention, the first and / or the second trained function is continuously further trained by means of feedback from the clinic staff and / or the child and / or the care person. In this case, the feedback takes place following the medical treatment carried out and is based on a correspondence value between an expected quality and an actual quality of the treatment.In particular, the actual quality of the treatment can be ascertained later, for example on the basis of a detected satisfaction of the child or the care person, a treatment duration or a repetition rate, an image quality of image data detected during the treatment, a treatment success or the like. The actual treatment quality can thus be determined after the actual treatment, for example on the basis of a feedback from the patient and / or the clinic staff and / or the care person. However, the expected treatment quality is derived directly from the provided treatment readiness data and the at least one action recommendation.In particular, the correspondence value can then be determined by a comparison between the actual and the expected treatment quality. In particular, the match value can be determined by the expert or automatically. In particular, the match value may comprise a value on a continuous scale or a discrete class. For example, the agreement value can comprise classes analogous to school notes. In particular, the match value may comprise a class "1" if there is a very good match and a class "6" if there is no match.The inventors have recognized that in this way the first and / or the second trained function can be continuously improved and adapted.Preferably, the first and / or the second trained function can be selected in each case from a plurality of first and / or second trained functions. The selection is based on the match value. In particular, this method is known by the term "model selection". In particular, the selection can take place during the training of the first and / or second trained function. In particular, a plurality of first and second trained functions can be trained during the training. In particular, the first trained functions can be different with regard to their mode of operation or network architecture. Example network architectures are described above. In particular, during training, the correspondence value between actual and expected treatment quality can be determined. In this case, the correspondence value is determined based on the training output data and the treatment quality predicted by the first and second trained functions. In other words, the training output data is compared with the treatment satisfaction during the training that can be determined by the first and second trained functions. From this comparison, the match value can be determined. The match value may be configured as described above. The correspondence value can be determined in particular automatically or manually. In particular, the first or second trained function can then be selected whose ascertained treatment quality has the best match value with the training output data.In particular, the selection of the first or second trained function can take place alternatively or additionally during the execution of the method according to the invention or subsequently thereto. In particular, the treatment quality can be determined in parallel for each of the first and second trained functions. In this case, the treatment quality is provided to the user (child / care person / clinic personnel) only by the selected first or second trained function. The feedback can now be used to determine the correspondence value as described above for each of the first and second trained functions. Based on the match value, the treatment quality determined by the first trained function having the best match value can be provided the next time or when the method is repeatedly executed. In other words, the selected first or second trained function can be replaced by another first or second trained function if, according to the feedback, its correspondence value is better than that of the originally selected first or second trained function. In this case, the selection can alternatively be based on a means of a plurality of match values for a plurality of quality parameters. In particular, it is possible to continuously check which first or which second trained function is the most suitable or which has the best correspondence value.In this way, it can be ensured according to the invention that the treatment quality that is most suitable with regard to the agreement value is provided.The invention also includes a system for providing treatment readiness data of a child to be treated in preparation for a medical treatment. The system comprises a computing unit and an interface. The computing unit is designed to acquire input data. The input data includea treatment specification relating to the treatment to be carried out,an indication characterizes the age and / or sex of the child, andat least one exercise parameter characterizing an exercise activity of the child.In this case, the arithmetic unit is also designed to apply a first trained function to the input data, as a result of which the treatment readiness data are generated.The interface is designed to acquire input data and / or to provide the treatment readiness data to the clinician.Such a system can be configured in particular to carry out the above-described methods for providing treatment readiness data of a child to be treated in preparation for a medical treatment in the various aspects. The system is designed to execute these methods and their aspects by virtue of the interface and the arithmetic unit being designed to execute the corresponding method steps.The invention may also relate to a training system for providing a first and / or second trained function. The training system can comprise a training interface and a training computing unit. In this case, the training arithmetic unit can be designed to provide training input data. In this case, the training input data can comprise input data or treatment readiness data as described above. In this case, the training arithmetic unit is also designed to provide training output data. The training output data here comprise treatment readiness data and / or at least one treatment recommendation. Here, the training output data and the training input data are related to each other. The training arithmetic unit is designed to train the first or second trained function on the basis of the training input data and the training output data. The training interface is designed to provide the first and / or second trained function.The invention also relates to a computer program product having a computer program and to a computer-readable storage medium. A realization largely through software has the advantage that even systems already used up to now can be easily retrofitted by a software update in order to operate in the described manner. In addition to the computer program, such a computer program product can optionally comprise additional components, such as documentation and / or additional components, as well as hardware components, such as hardware keys (dongles, etc.) for using the software.In particular, the invention also relates to a computer program product having a computer program which can be loaded directly into a memory of a system, having program sections in order to carry out all method steps of the above-described methods for providing treatment readiness data of a child to be treated in preparation for a medical treatment and its aspects when the program sections are executed by the system.In particular, the invention relates to a computer-readable storage medium on which program sections readable and executable by a system are stored in order to carry out all method steps of the above-described methods for providing treatment readiness data of a child to be treated in preparation for a medical treatment and their aspects when the program sections are executed by the system.The above-described characteristics, features and advantages of this invention and the manner in which these are achieved become clearer and more clearly comprehensible in conjunction with the following description of the exemplary embodiments, which are explained in more detail in conjunction with the drawings. This description does not limit the invention to these exemplary embodiments. In different figures, identical components are provided with identical reference numerals. The figures are generally not to scale. The following are shown: FIG. 1 shows a representation of a method according to the invention in an embodiment of the present invention, FIG. 2 shows a representation of a method according to the invention in a further embodiment of the present invention, FIG. 3 shows a representation of a method according to the invention in a further embodiment of the present invention, FIG. 4 shows a representation of a method according to the invention in a further embodiment of the present invention, and FIG. 5 shows a schematic illustration of a system according to the invention in an exemplary embodiment of the present invention.FIG. 1 shows a representation of a method according to the invention in one embodiment of the present invention. The method is a computer-implemented method, it serves to provide treatment readiness data BBD of a child to be treated in preparation for a medical treatment. The method can be carried out, for example, with or in a system according to FIG. 5.In a step S 11, input data ED is acquired. The acquisition of input data can comprise receiving input data ED via an interface SS, but also generating / deriving input data ED with a computing unit RE. The input data ED comprise a treatment specification with respect to the medical treatment to be carried out. The treatment specification thus identifies the treatment to be performed on a child patient, for example a computed tomographic imaging examination. The input data ED also comprise an indication characterizing the age and / or sex of the child or general indications relating to the child that allow it to be identified, such as name, date of birth, place of birth, etc. The input data ED further comprise at least one exercise parameter characterizing an exercise activity of the child. The exercise parameter, which can be derived from an exercise activity, identifies how intensively a child has prepared for the pending treatment on the basis of information material and / or exercise material. In this respect, the acquisition of the exercise parameter can comprise acquisition of an exercise activity of the child (over a predefined period of time) and formation of the exercise parameter on the basis of the exercise activity of the child.In a step S 12, a first trained function TF 1 is applied to the input data ED. The first trained function TF 1 is configured to generate treatment readiness data BBD from the sum of the acquired input data ED. The treatment readiness data BBD indicate a measure of a treatment readiness and / or a preparation level of the child with respect to the pending treatment. In this regard, the treatment readiness data allow a prediction of how time-consuming and / or care-intensive the pending treatment will proceed. The first trained function TF 1 can be executed in particular by a computing unit RE. The first trained function TF 1 can be stored in a memory MEM in particular retrievable by the computing unit RE.In a step S 13, the treatment readiness data BBD is provided to a hospital staff in the medical facility being treated. The provision comprises, on the one hand, a visual display or output of the treatment readiness data BBD for the clinic personnel, for example via an output device or a display unit such as a workplace AP in the medical facility or via a tablet computer, so that treatment readiness can be detected optically quickly and easily by the clinic personnel. In this respect, the step S 12 of generating the treatment readiness data BBD also comprises creating the treatment readiness data BBD in graphically displayable form. In this case, the treatment readiness data can be displayed in the form of a patient dashboard and / or a multiaxial diagram.In embodiments, the provision of the treatment readiness data BBD also comprises (intermediate) storage thereof, for example in a memory MEM, so that the treatment readiness data BBD are available for later further processing, for example as input data of the second trained function TF 2.In the present case, the input data ED also comprise a mood parameter characterizing at least one personal and / or emotional property of the child. The mood parameter thus takes into account whether it is a more anxiety or a muted, more retaining or neugierous child, or the like. The invention is based on the fact that mutty, neugierous children handle a treatment better and are more cooperative in the treatment situation per se than anxiety or restraining children, and that independently of their age. This information is also taken into account according to the invention in order to generate the treatment readiness data BBD. In this respect, according to the invention, a treatment for a mutated, disrupted more recent child can be planned shorter and, if appropriate, with less equipment than for an anxiety-like older child.The input data ED further comprise an participation parameter characterizing the participation readiness of at least one care person of the child. The participation parameter is determined, for example, by analyzing which and / or how much information material a care person of the child patient has read. The participation parameter can also indicate how many further input data ED, for example concerning the child, have been input by the caregiver. The participation parameter can also take into account which or how many questions are presented by the caregiver with respect to the pending examination. The participation parameter may also be generated based on the infant's exercise activity, assuming that the caregiver can significantly influence the infant's exercise activity. In this respect, the participation parameter can be entered by the care person himself, but also by the clinician, for example, into the system SYS according to FIG. 5, or can be generated by the latter from further information entered by the care person, the child or the clinician.FIG. 2 shows a representation of a method according to the invention in a further embodiment of the present invention. Steps S21, S22 and S23 correspond to steps S11, S12 and S13, respectively. In this respect, the disclosure of FIG. 1 is also adopted in FIG. 2.The method shown here further comprises a step S 24. This is directed to applying a second trained function TF 2 to the treatment readiness data BBD. The second trained function TF 2 can be executed by the arithmetic unit RE of the system SYS. It can be stored in the memory MEM in such a way that it can be called up for the arithmetic unit RE. By applying the second trained function TF 2 to the treatment readiness data BBD, at least one, preferably a plurality of, action recommendations HE for treatment planning is generated. The at least one action recommendation HE comprises proposals with respect to the treatment to be carried out that are adapted to the treatment readiness of the child. The at least one action recommendation HE can comprise, for example, a recommendation for adapting the planned treatment time, a recommendation for or against a sedative of the child, a recommendation of a type of sedative (medication and device), a recommendation of a treatment room, a recommendation of a medical treatment facility and / or a special treatment protocol comprising a plurality of protocol parameters, a recommendation of a number of required clinical personnel, a recommendation of a time delay, in particular depending on an availability of an anesthetic and / or of the clinical personnel and / or of a treatment room and / or of a treatment facility, a recommendation for using an additional equipment for the child, or the like. The at least one action recommendation serves to facilitate treatment planning by a clinician and to enable an improved treatment procedure.A further step S 25 is directed to providing the clinic personnel with the recommendation for action HE together with the treatment readiness data BBD. In this case, step S 25 can be embodied analogously to step S 23. Particularly preferably, steps S 23 and S 25 are carried out jointly or simultaneously. In particular, the at least one action recommendation HE is displayed directly to the clinician via the display unit as part of the display of the patient dashboard or the treatment readiness diagram.A further step S 26 of the method in question is directed to continuously training the first and / or the second trained function TF 1, TF 2 further by means of feedback from the clinician and / or the child and / or the caregiver. In step S 26, training TR of the first / second trained function TF 1, TF 2 is thus carried out. In this case, the feedback takes place following the medical treatment carried out. The feedback is based on a match value between an expected quality and an actual quality of the treatment. On the basis of the at least one correspondence value, individual parameter values of the first and / or second trained function TF 1, TF 2 can now be continuously or iteratively adjusted between two treatments in the sense of a feedback loop. The adaptation is thereby the greater the greater the deviation between the expected and actual treatment quality or the smaller the agreement value. As an alternative to adapting individual function parameters, functions other than the previous trained functions can be selected as first and second trained functions TF 1, TF 2 and used for the next treatment planning.More preferably, step S26 is carried out after each treatment carried out to effect a continuous improvement of the system.FIG. 3 shows a representation of a method according to the invention in a further embodiment of the present invention.Steps S 31, S 32, S 33 and S 34 substantially correspond to steps S 21, S 22, S 32 and S 24. In this respect, the disclosure of FIG. 1 is also adopted in FIG. 2.In step S 34, as shown in FIG. 3, a second trained function TF 2 is also applied to the treatment readiness data BBD in order to generate at least one recommendation HE for action for treatment planning. In this embodiment, one of the at least one action recommendation HE is a specific recommendation of a medical treatment system BA comprising a specific treatment protocol BP comprising a plurality of protocol parameters. By means of this recommendation HE for action, a specific imaging system is therefore selected from a plurality of imaging systems in question, for example, and a specific imaging protocol with corresponding protocol parameters such as x-ray tube current, various recording positions or the like is proposed as an optimum imaging solution.A further step S 35 is directed to providing the at least one recommendation for action HE comprising the proposed treatment system BA and the proposed treatment protocol BP for the clinic personnel, likewise preferably as explained in step S 25.A further step S 36 of the method in question is further directed to controlling, at the moment of treatment, the proposed treatment facility BA according to the recommended treatment protocol BP comprising the protocol parameters. In other words, the computing unit RE is designed to generate control signals corresponding to the protocol parameters on the basis of the at least one action recommendation HE and the recommended treatment protocol BP to one or more control devices of the treatment system BA, for example to transmit a control signal for setting the predefined X-ray tube current to the control device of the X-ray source of the treatment system BA. Before step S 36, confirmation of the proposed treatment system BA or of the proposed treatment protocol BP by the clinician may be required or provided.FIG. 4 shows a representation of a method according to the invention in a further embodiment of the present invention. In a step S 41, input data ED is acquired as already described with reference to the previous figures. At a defined time interval before the medical treatment, for example one or two weeks, step S 42 involves determining provisional treatment readiness data representing a provisional treatment readiness VBB of the child. The provisional treatment readiness data are likewise generated by applying the first trained function TF 1 to the input data ED already available one or two weeks before the actual treatment, as already described with reference to steps S 12, S 22, S 32 of the preceding figures. In this respect, the invention assumes that the input data ED available up to then are still incomplete and the derived treatment readiness data are therefore provisional treatment readiness data. From these provisional treatment readiness data, a previous preparation state of the infant patient or the care person can be determined early or timely before the actual treatment, which can also be influenced at the moment of the defined time interval in such a way that the treatment result can be improved.In this respect, in a further step S 43, the provisional treatment readiness VBB is compared with a predefined threshold value SW for the treatment readiness. The defined threshold value SW can be individually defined by the clinician according to user specifications or specifically for different age groups of the child patients or taking into account the medical treatment to be performed. It can correspond in particular to a minimum preparation level. In step S 43, the arithmetic unit RE consequently checks whether the provisional treatment readiness is below or above the defined threshold value. If in step S 43 equality or exceeding of the threshold value SW is determined, the method according to the invention is carried out again at a later point in time with a shorter time interval for treatment, for example by means of steps S 31, S 32, S 33, S 34, S 35 and S 36 according to FIG. 3. If the threshold value SW is undershot, in a further step S 44 a training and / or participation request AF is generated for the infant patient and / or the care person. The training or participation request AF comprises instructions for the child and / or the caregiver about the current preparation state and is intended to aim at still processing exercises which have not yet been completed or not yet sufficiently completed or not yet read information materials in the remaining time. For this purpose, the request AF also comprises, in embodiments, a reminder of the pending medical treatment. The purpose of the training or participation request AF is to improve the preparation level still further in the time remaining until the time of the treatment.In a step S45, the training and / or participation request AF is provided for the child and / or the care person. The training and / or participation request AF can be provided in particular as a push message via the user terminal EG or as an email.FIG. 5 shows a schematic illustration of a system SYS according to the invention in an exemplary embodiment of the present invention. The system SYS serves to provide treatment readiness data BBD of a child to be treated in preparation for a medical treatment. The system SYS is designed to execute a method according to the invention for providing treatment readiness data BBD of a child to be treated in preparation for a medical treatment.The system SYS comprises at least one interface SS, a computing unit RE and a memory unit MEM.The system SYS further optionally comprises a user terminal EG which is designed to capture input data ED of the child and / or of the at least one care person and to provide it to the computing unit RE via the interface SS. The user terminal EG is further configured to provide and display training or information material to the child and / or the caregiver. The user terminal EG is in particular designed as a smartphone, tablet computer, laptop or the like.The system SYS further comprises a (clinic) workstation AP, via which the (preliminary) treatment readiness data BBD, action recommendations HE, but also individual input data ED, such as the details of the person regarding the infant patient or the like, are provided, in particular displayed, to a clinic personnel. Furthermore, input data ED can also be transferred to the system SYS via the workstation AP. For example, the (clinic) workstation can be designed as a fixed planning workstation or radiology workstation in a medical facility. The workstation AP can alternatively be configured via a portable user terminal, for example a tablet computer.The system SYS further optionally comprises a treatment plant BA. This can be designed in the form of a medical imaging system, for example a computed tomography system, a magnetic resonance tomography system or the like. It can alternatively be designed as a radiotherapy or intervention system, for example a C-arm X-ray device. The treatment system can also be designed to provide or display, for example, (provisional) treatment readiness data BBD, action recommendations HE and / or individual input data ED to the clinician.The system SYS further comprises a sample treatment plant PBA. This can be simulated to the actual treatment system, for example, and can likewise be configured to provide or display training and / or information material to the child. The trial treatment facility may serve to player the course of treatment close to the child to create a routine and de-excrete.User terminal EG, workstation AP, treatment system BA and sample treatment system PBA can be connected via the interface SS for data exchange with the computing unit RE of the system SYS or the memory MEM.In embodiments, user terminal EG, workstation AP, treatment system BA and sample treatment system PBA each comprise a display unit, for example for the graphic display of training material or the treatment readiness data BBD or action recommendations HE, and an input unit. The display unit can be, for example, an LCD, plasma or OLED screen. It can furthermore be a touch-sensitive screen which is also designed simultaneously as an input unit. The input unit is, for example, a keyboard, a mouse, a so-called "touch screen" or also a microphone for speech input. The input unit can be configured to recognize movements of a user and to translate them into corresponding commands. By means of the input unit, a user can input input data ED or information regarding a treatment planning based on displayed treatment readiness data BBD.The arithmetic unit RE is designed to acquire input data ED. The acquisition can comprise, on the one hand, a reception of the input data ED via the interface SS and / or other data. The acquisition can also comprise generating, i.e. calculating, generating, deriving the input data ED from other data. The input data ED comprise a treatment specification with respect to the treatment to be carried out. This includes features and / or parameters of the treatment to be carried out, so that this can be identified on the basis of the treatment specification or selected from a list of different possible treatments according to their features. The input data ED further comprise an indication characterizing the age and / or sex of the child, more generally the input data ED comprise indications and characteristics allowing a unique identification of the child patient. The input data ED further comprises at least one exercise parameter characterizing an exercise activity of the child. The computing unit RE is also designed to apply a first trained function TF 1 to the input data ED. As a result, the arithmetic unit RE generates treatment readiness data BBD which indicate how good or poor a child is prepared for the pending treatment.The computing unit RE is also further configured to generate at least one recommendation for action HE by applying a second trained function TF 2 to the treatment readiness data BBD. The computing unit RE is also further configured to determine a provisional treatment readiness VBB and, based thereon, to generate an participation request AF.The interface SS is designed to provide the treatment readiness data BBD or the recommendation for action HE or the training and / or participation request AF. For example, the treatment readiness data BBD can be transmitted via the interface SS into the memory MEM of the system SYS or to the workstation AP or the treatment installation BA. In this respect, the interface SS is designed for bidirectional data communication from or to the arithmetic unit RE. The interface SS can be designed, in particular, to receive and / or transmit data. In this case, the bidirectional data communication can be configured in a manner known per se in a cableless or cable-bound manner. The interface SS is to be understood in this respect as an input and / or output interface.The system SYS can be, in particular, a computer, a microcontroller or an integrated circuit (IC). Alternatively, the system SYS may be a real or virtual computer network (a technical designation for a real computer network is "cluster", a technical designation for a virtual computer network is "cloud"). The system SYS can be designed as a virtual system which is executed on a computer or a real computer network or a virtual computer network (a technical designation is "virtualization"). The interface SS can be a hardware or software interface (for example a PCI bus, USB or Firewire). Data is preferably exchanged by means of a network connection. The network may be a local area network (LAN), for example. An intranet or a wide area network (WAN) may be formed. The network connection is preferably configured wirelessly, for example as a wireless LAN (WLAN or WiFi). The network may include a combination of different network examples. Data transmission can be carried out based on a data query or in a self-initiated manner. Data transmission between two units or system components can be bidirectional or unidirectional.The interface SS can in particular comprise a plurality of sub-interfaces which execute different method steps of the respective method according to the invention or are involved therein. In other words, the interface SS can be formed as a plurality of interfaces SS. The computing unit RE can in particular comprise a plurality of sub-computing units which execute different method steps of the respective method according to the invention. In other words, the computing unit RE can be designed as a plurality of computing units RE.The computing unit RE can comprise hardware and / or software components, for example a microprocessor or a so-called FPGA (field programmable gate way). The computing unit RE, individual components or all of its subcomponents can alternatively be arranged in a decentralized manner, e.g. individual computing steps of the method can be carried out in a central data center of a medical service device, e.g. a hospital, or in the cloud. In this case, in particular data and patient protection must be taken into account during the data exchange.The computing unit RE can cooperate with a computer-readable storage medium or data carrier in the form of the memory MEM, in particular in order to carry out a method according to the invention by means of a computer program product comprising program code. Furthermore, the computer program can be stored on the computer-readable data carrier in such a way that it can be called. In particular, the computer-readable data carrier can be a CD, DVD, Blu-ray disc, a memory stick or a hard disk. The memory unit MEM can be designed as a non-permanently operating random access memory (RAM) or as a permanent mass storage device (hard disk, USB stick, SD card, solid state disk (SSD)).The invention is summarized again briefly below:According to the invention, a self-learning algorithm is provided which has carried out various attributes in the form of input data ED, for example how often a child has carried out a breathing exercise, a relaxation exercise, etc., or whether or which information material has been read by the parent. The input data ED can also comprise details as to whether the child has selected a (animal) mask over the preparation material, each representing a specific emotion. According to the invention, input data ED for a child patient are collected and, from this, a treatment readiness in the form of treatment readiness data BBD corresponding to a "preparation status" is made available to the clinic personnel for assistance in the treatment planning. The invention allows the clinician to better estimate infant patients before an pending treatment via the treatment readiness data BBD and to be able to more easily and individually access the infant or the care person or the family during the treatment. Furthermore, the idea makes it possible to derive action recommendations HE for the treatment planning directly on the basis of the treatment readiness data BBD. For example, a list of individual action recommendations can be derived. The list may be checked, discarded or validated point by point by the clinician. The list of recommended actions HE provided to the clinician prevents the clinician from overlooking aspects in treatment planning.The input data ED, the treatment readiness data BBD and / or the recommendations for action HE are displayed in the clinic or the medical facility preferably via a web application and a (fixed) treatment planning workstation AP, alternatively via a portable terminal on which the clinic personnel can also perform treatment planning outside the medical facility. In addition, it is possible to carry out the treatment planning comprising the display of the information derived according to the invention directly on the treatment installation BA. For this purpose, the method according to the invention could be executed, for example, in a patient-centric data model or integrated into the control software of the treatment system BA by means of a Web API.The solution according to the invention is not limited to a specific treatment system, in particular a specific medical imaging system. The method according to the invention can consequently be used within the scope of an examination planning not only by means of a magnetic resonance tomography system but also in other medical imaging modalities with which children are examined, for example a computer tomography system, in particular a photon-counting computer tomography system, but also for fluoroscopic examinations, for example for a milicisurography or an esophageal pulp-swallow radiography.Input data ED can also be acquired according to the invention by means of a sample treatment system PBA or training material can be provided for the child. A sample treatment facility PBA can be arranged in a medical facility. The child can complete various exercises directly at the sample treatment facility PBA and thereby learn handling strategies. The sample treatment system PBA can be designed in embodiments to monitor a movement of the child during a sample treatment that is simulated to the actual treatment (for example by means of a camera monitor) in order to detect whether or how long the child can be at a standstill. Such data can also be recorded as input data ED and evaluated according to the invention.In order to derive treatment readiness data BBD from the various and partially comprehensive input data ED, the method according to the invention uses machine learning in the form of the first trained function TF 1. The first trained function TF 1 is trained with training data which correspond to a ground truth database and which are formed from attributes of previous treatments, for example by means of measurements / queries of time durations relating to the previous treatments, acquired stress levels of infant patient, care person and / or clinic personnel during a treatment or else movement artifacts in image data acquired during the treatment.The solution according to the invention allows clinicians to better assess how infant patients and a care person are to be treated under time pressure within the framework of standardized treatment processes and thus to plan the treatment better. In this case, the action recommendations HE derived by means of the second trained function support in particular.In this way, a stress level on the part of the patient, care person and / or clinic personnel can be reduced, and the workflow can be made more smooth and tighter. Shorter examination times result, and the number of required sedatives and thus the health risk for the treated children can optionally also be reduced as a result. In addition, the medical image data acquired during a medical treatment have fewer movement artifacts, in more general terms the quality of the medical treatment increases. Not least because of this, the satisfaction of the child, the care person and the clinic personnel also increases.The applicant points out that, independently of the grammatical sex of a certain term-here for example the term "patient"-persons with male, female and other sex identity are always included.Although the invention has been illustrated and described in more detail by the preferred exemplary embodiment, the invention is not restricted by the disclosed examples and other variations can be derived therefrom by the person skilled in the art without departing from the scope of protection of the invention.

Claims

Computer-implemented method for providing treatment readiness data (BBD) of a child to be treated in preparation for a medical treatment, comprising the steps of - acquiring (S11, S21, S31, S41) input data (ED), wherein the input data (ED) - comprises a treatment indication relating to the medical treatment to be carried out, - an indication characterizing the age and / or sex of the child, and - at least one exercise parameter characterizing an exercise activity of the child, - applying (S12, S22, S32) a first trained function (TF1) to the input data (ED), whereby the treatment readiness data (BBD) are generated, - providing (S13, S23, S33) of the treatment readiness data (BBD) for a hospital staff in the medical facility being treated.Method according to claim 1, wherein the treatment readiness data (BBD) indicate a treatment readiness and / or a preparation level of the child.Method according to claim 1 or 2, wherein the input data (ED) also comprise a mood parameter characterizing at least one personal and / or emotional property of the child.Method according to one of the preceding claims, wherein the input data (ED) also comprise an participation parameter characterizing the participation readiness of at least one care person of the child.The method according to claim 4, wherein acquiring (S11, S21, S31, S41) the input data (ED) comprises: - generating the participation parameter based on an amount of information material that the caregiver has read and / or based on the exercise activity of the child.The method according to any of the preceding claims, wherein the acquiring (S11, S21, S31, S41) of the input data (ED) comprises: - generating the at least one exercise parameter based on the exercise activity of the child.Method according to one of the preceding claims, wherein the provision (S13, S23, S33) of the treatment readiness data (BBD) comprises visually displaying the treatment readiness data (BBD) to a clinic staff via an output device (EG, AP, BA).Method according to one of the preceding claims, further comprising - applying (S24, S34) a second trained function (TF2) to the treatment readiness data (BBD), whereby at least one treatment recommendation (HE) for treatment planning is generated, and - providing (S25, S35) to the clinician the treatment recommendation (HE) together with the treatment readiness data (BBD).Method according to claim 8, wherein the recommendation for action (HE) is a recommendation from the group of the following recommendations: a) recommendation for adapting the planned treatment time, b) recommendation for or against a sedative of the child, c) recommendation of a type of sedative (medication and device), d) recommendation of a treatment area, e) recommendation of a medical treatment facility (BA) and / or a special treatment protocol (BP) comprising a plurality of protocol parameters, f) recommendation of a number of required clinical personnel, g) recommendation of a time delay, in particular depending on an availability of an anesthetist and / or the clinical personnel and / or a treatment area and / or a treatment facility, h) Recommendation for Utilizing Supplementary Equipment for Child.Method according to claim 9, alternative e), further comprising - controlling a treatment plant (BA) according to the recommended treatment protocol (BP).Method according to one of the preceding claims, further comprising - determining (S42) preliminary treatment readiness data representing a preliminary treatment readiness (VBB) of the child at a defined time interval before the medical treatment by applying the first trained function (TF1) to the input data (ED), - comparing (S43) the preliminary treatment readiness (VBB) with a predefined threshold value (SW) for the treatment readiness and, if the threshold value is undershot, - generating (S44) an exercise and / or participation request (AF), and - providing (S45) the exercise and / or participation request (AF) for the child and / or the care person.Method according to one of the preceding claims, wherein the first and / or the second trained function (TF1. TF 2) is continuously further trained by means of feedback from the clinician and / or the child and / or the care person (S 26), wherein the feedback is effected subsequent to the performed medical treatment and is based on a match value between an expected quality and an actual quality of the treatment.System (SYS) for providing treatment readiness data (BBD) of a child to be treated in preparation for a medical treatment, comprising a computing unit (RE) and an interface (SS), wherein the computing unit (RE) is designed to acquire input data (ED), wherein the input data (ED) - comprises a treatment indication relating to the treatment to be carried out, - an indication identifying the age and / or sex of the child, and - at least one exercise parameter identifying an exercise activity of the child, wherein the computing unit (RE) is also designed to apply a first trained function (TF1) to the input data (ED), whereby the treatment readiness data (BBD) are generated, wherein the interface (SS) is designed to provide the treatment readiness data (BBD).Computer program product having a computer program which can be loaded directly into a memory of a system (SYS), having program sections in order to carry out all method steps of the method according to one of Claims 1 to 12 when the program sections are executed by the system (SYS).Computer-readable storage medium on which program sections readable and executable by a system (SYS) are stored in order to execute all method steps of the method according to one of Claims 1 to 12 when the program sections are executed by the system (SYS).

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