Ways to navigate healthcare data

Abstract

The present invention includes a computer-implemented method, the computer-implemented method including the steps of providing a medical dataset, the medical dataset comprising data for a plurality of patients and relating to at least one disease; associating data in the dataset with corresponding parts of a human body to which the data pertains; displaying a graphical representation (1) of the human body or a portion of the human body on a display device; displaying a plurality of activatable buttons (2) on the display device, the activating buttons (2) being associated with different parts of the graphical representation (1); receiving user input activating one of the plurality of activatable buttons (2); and, based on the activation, displaying on the display device a graphical representation of data (4) associated with the part of the human body to which the activatable button (2) activated by the user input pertains.

Description

[Technical field]

[0001] The present invention relates to a computer-implemented method for navigating medical data, particularly large medical data sets involving data for multiple patients. [Background technology]

[0002] Especially in the pharmaceutical industry, large-scale medical investigations involving large numbers of patients are carried out. For the process of drug approval, clinical trials involving several thousand patients are carried out. Clinical data in the form of patient demographics, medical history, baseline disease characteristics, composite measures of disease activity assessment, and patient-reported outcomes (PROs) are collected at different time points and over time (which may extend to 5 years of follow-up). For example, patients suffering from psoriasis or psoriatic arthritis may be periodically examined to see how their joints and / or their skin condition have evolved since starting to use a drug.

[0003] The resulting time-dependent data is usually available in the form of large tables (so-called patient-level data).

[0004] This huge amount of data is usually analyzed according to a statistical analysis plan and used to generate a Clinical Study Report (CSR), which can be up to 10,000 pages long including appendices. Only a very small percentage of these outputs are published in peer-reviewed journals, and these are mainly summary tables or statistical tests.

[0005] However, such summaries do not preserve the data in their anatomical and / or physiological integrity. For example, with respect to psoriatic arthritis, a question may arise as to whether the location of swollen or tender joints may affect treatment response. Such a question obviously cannot be answered using published summaries. Given the number of locations of possible joint pain (78 joints), using traditional patient-level data to answer the question would be cumbersome, if at all practically possible. Summary of the Invention [Problem to be solved by the invention]

[0006] It is therefore an object of the present invention to provide a computer-implemented method that facilitates efficient searching and evaluation of data in large medical datasets. [Means for solving the problem]

[0007] This object is achieved by a method according to claim 1. Preferred embodiments are specified in the dependent claims.

[0008] The method allows efficient retrieval of specific data in their corresponding anatomical and / or physiological context, and furthermore, it provides a framework for interactive exploration of medical datasets.

[0009] The medical dataset can include patient level data for multiple patients, particularly for more than 500 patients, particularly for more than 1,000 patients. For each patient, one or more medical data items can be stored in the medical dataset.

[0010] The medical dataset may, inter alia, be a clinical dataset, including, inter alia, data from one or more clinical trials.

[0011] The graphical representation of the human body or a portion of the human body may be a schematic or realistic representation. Also, the graphical representation may include one or more anatomically correct representations of a portion of the human body or an anatomically correct representation of the human body as a whole. The graphical representation of the human body or a portion thereof may be a two-dimensional (2D) or three-dimensional (3D) representation.

[0012] Also, the graphical representation of the body or part of the body may be animated, in particular the graphical representation of the body or part of the body may change in response to the disease progression and / or the graphical representation of the displayed data.

[0013] An activatable button is a virtual button displayed on a display device. The form of the activatable button is not particularly limited. According to one embodiment, the color and / or form of the activatable button can change when it is activated. In this way, a user can easily identify an activated button.

[0014] The activatable buttons may each be positioned overlapping or adjacent to a portion of the graphical representation that represents the particular part of the human body to which the activatable button pertains. In other words, the activatable buttons may be associated with a particular element of the human body via the graphical representation. For example, an activatable button may relate to a hand or foot of the human body, while another activatable button relates to the head or shoulders. When the graphical representation provides more detail or is a representation of a portion of the human body, the activatable button may also relate to a smaller element of the human body (such as, for example, a joint, an organ, or a blood vessel).

[0015] The activatable buttons may, inter alia, be anchored to the respective portions of the graphical representation. The activatable buttons may be displayed such that they are visible on the display when the respective portions of the graphical representation are visible. The activatable buttons may be re-displayed in the appropriate position if, after a user input (e.g., after a zooming operation or a repositioning of another window that overlaps the respective button), the button is no longer visible in its previous location.

[0016] A user may activate the activatable button in any suitable manner, for example, using a touch-sensitive display or a mouse.

[0017] The method may further comprise displaying a context menu in response to activation of the activatable button, the context menu offering a set of options for determining the graphical representation of the data and / or for choosing a subset of the data associated with the respective part of the human body. In this way, the data used for the graphical representation of the data or the details of said graphical representation may be further refined. For example, a medical dataset may include various measurements for quantifying a particular symptom. Using the context menu, one of said measurements may be selected such that only data in the medical dataset related to said measurement and to the respective part of the human body will be taken into account for the graphical representation of the data.

[0018] The graphical representation of the data may include one or more charts or graphs. For example, the graphical representation may include a pie chart, a bar graph, a box plot, a scatter plot, or a dot plot. The graphical representation of the data may alternatively or additionally include one or more images of the patient or patients and / or one or more realistic representations of the patient or an average patient. For example, the images may show portions of the patient's skin and / or realistic representations of lesions may be shown.

[0019] The graphical representation of the data may, inter alia, show the temporal disease progression, for example, via one or more charts, graphs, and / or tables showing the temporal disease progression.

[0020] The term "realistic representation" refers to image data obtained from one or more photographs of a patient, as distinct from the photograph itself, and the one or more images may include one or more anatomical images (e.g., x-ray images, MRIs, CT scans, and / or angiograms, etc.).

[0021] Via the above mentioned context menu, the user is able to select the particular chart or graph that will be used for the graphical representation of the data.

[0022] The medical data set may include time-dependent data, and the graphical representation of the data may include representations of different temporal snapshots of the data. In this manner, the time evolution of at least one disease symptom and / or the response of one or more patients to a particular drug may be evaluated. For example, a series of charts or graphs may be used as representations of the different temporal snapshots.

[0023] The method may further include displaying a temporal control element (such as, for example, a timeline) to select a time point to which data for the graphical representation of the data should relate. The method may further include receiving user input via the temporal control element and displaying the graphical representation of the data relating to the selected time point. For example, a slider element may be provided, which may be shifted along the timeline to select a time point. In this way, the temporal disease progression may be efficiently explored by the user.

[0024] The graphical representation of the human body or of a part of the human body can be an interactive representation, inter alia, a scalable and / or rotatable representation. In this way, it is possible to explore the medical dataset with respect to different parts of the human body. The graphical representation of the human body or of a part of the human body can show different levels of detail depending on the zoom level. For example, at a first zoom level, the graphical representation of the human body can show only a schematic illustration of a body element (such as, for example, a hand). When zooming in, this graphical representation can change to a more detailed (inter alia, an anatomically correct) representation of the body element (such as, for example, a hand including a representation of individual fingers and joints). Additional activatable buttons can be displayed for additional elements of the graphical representation, which become visible after zooming and / or rotation. Also, the activatable buttons can be removed from the display if, for example, after zooming or rotation, the corresponding part of the graphical representation is no longer visible.

[0025] The medical dataset can relate to more than one disease, and the method includes: providing an interface that allows a user to select a disease; limiting the graphical representation of data associated with the portion of the human body to which the activatable button activated by the user input relates to data related to the selected disease; In this way, the medical dataset may be searched for different diseases, in which case the method may further comprise the step of associating data in the dataset with the different diseases to which the data relates.

[0026] Alternatively or additionally, the medical data set may relate to two or more drugs used to treat at least one disease, and the method may further comprise: providing an interface that allows a user to select a medication; limiting the graphical representation of data associated with the portion of the human body to which the activatable button activated by the user input relates, to data related to the selected medication; In this way, the medical dataset can be searched for different medications. This can assist the user in selecting the most appropriate medication. In this case, the method can further include the step of associating the data in the dataset with the corresponding medication to which the data relates.

[0027] The graphical representation of the body or a portion of the body, when animated, can change in response to the selected disease and / or medication, for example, the graphical representation of the body or a portion of the body can reflect the disease or its progression over time and / or the effect of the selected medication on the disease or its progression over time.

[0028] The step of relating the data in the dataset to the corresponding part of the human body to which the data relates can include providing at least one matrix for each patient's data, the elements of the matrix being respectively associated with a predefined part of the human body, and inputting at least a part of the data or a quantity derived from said data into the at least one matrix. The matrix can also be an nx1 matrix, which is referred to herein as a "vector". There can be more than one matrix per patient, each matrix relating to a different region of the human body. For example, one matrix can refer to the joints of the human body, while a second matrix refers to a different internal organ. Each matrix can be associated with a predefined time point. Thus, the temporal evolution of the patient-level data can be transformed into a series of matrices, each corresponding to a different time point.

[0029] The step of relating the data in the dataset to the corresponding parts of the human body to which the data relate may further comprise receiving and / or determining anatomical scores for each patient and storing them as elements in at least one matrix. Thus, the anatomical scores may correspond to data in the medical dataset or to quantities derived from said data.

[0030] Anatomical score is defined as a clinical assessment or evaluation performed on a specific anatomical location. Joint score (swelling, tenderness) is one example of an anatomical score. For example, 78 joints are monitored in psoriatic arthritis, so the resulting matrix can be a 78x1 matrix, i.e., a vector with 78 entries.

[0031] Other anatomical scores are contemplated as well, such as an enthesitis score for the insertions (where the tendons attach to the bone), a psoriasis skin score (red spots on the head, torso, etc.), a dactylitis score (for the fingers, toes), and / or a bone erosion and joint space narrowing score (e.g., derived from an x-ray).

[0032] In other diseases, the anatomical score may relate to edema (excess fluid) on the retina in patients with age-related macular degeneration (ADM) or diabetic retinopathy, blood velocities (measured, for example, by Doppler echocardiography) in various heart valves (locations), and / or wall thickness in cardiomyopathies among heart failure patients, and the anatomical score may relate to T2 lesions in the brain of multiple sclerosis (MS) patients.

[0033] The step of associating the data in the dataset with a corresponding part of the human body to which the data relates may further include determining an anatomical score from patient-level data of at least one patient using machine learning techniques and / or artificial neural networks, in particular deep neural networks. The anatomical score may be determined based on medical images (e.g., X-ray images, computed tomography (CT) scans, and / or magnetic resonance imaging (MRI), etc.), among others.

[0034] The step of relating the data in the dataset to the corresponding part of the human body to which the data relates may further include determining statistical quantities of the medical data based on at least one matrix for each patient. The statistical quantities (e.g., averages, correlations, quantiles, and / or clustering, etc.) may be determined based on a subset of patients less than all patients in the dataset or based on all patients. Thus, the statistical quantities may be derived from the complete patient-level data.

[0035] For example, for two patients with joint scores x1 and x2, the sum x1+x2 or the difference x1-x2 can be computed by the corresponding matrix or vector operations, the result of which is again a matrix or vector.

[0036] The statistical quantities may be used to determine a graphical representation of the data associated with a portion of the human body, for example, the joint scores of the corresponding mean vectors may be displayed in color-coded form superimposed on each joint location in a schematic representation of the human body.

[0037] The present invention further provides a data processing apparatus comprising a processor adapted to perform the steps of the method described above.

[0038] The invention further provides a computer program product comprising instructions, which when the program is executed by a computer, cause the computer to carry out the steps of the method described above.

[0039] The present invention further provides a computer-readable storage medium containing instructions which, when executed by a computer, cause the computer to perform the steps of the methods described above.

[0040] The step of structuring the medical dataset, as described above with respect to the step of associating data in the dataset with corresponding parts of the human body to which the data relates, may also be embodied without other steps of the method of claim 1.

[0041] In other words, the present invention also provides a computer-implemented method for structuring a medical dataset comprising data of a plurality of patients and relating to at least one disease, the method comprising the steps of providing at least one matrix for the data of each patient, the elements of the matrix being respectively associated with a predetermined part of the human body, and inputting at least a portion of the data or quantities derived from said data into the at least one matrix.

[0042] As mentioned above, the matrix can be an nx1 matrix, which is referred to herein as a "vector". There can be more than one matrix per patient, each matrix relating to a different region of the body. For example, one matrix can refer to the joints of the body, while a second matrix refers to a different internal organ. Each matrix can be associated with a given time point. Thus, the temporal evolution of the patient-level data can be converted into a series of matrices, each corresponding to a different time point.

[0043] Structuring the medical dataset may further comprise receiving and / or determining anatomical scores for each patient and storing them as elements in at least one matrix. Thus, the anatomical scores may correspond to data in the medical dataset or to quantities derived from said data.

[0044] An anatomical score is defined as a clinical assessment or evaluation performed on a specific anatomical location. Joint scores (swelling, tenderness) are one example of an anatomical score. Since 78 joints exist in the human body, the resulting matrix can be a 78x1 matrix, i.e., a vector with 78 entries.

[0045] Other anatomical scores are contemplated as well, such as an enthesitis score for the insertions (where the tendons attach to the bone), a psoriasis skin score (red spots on the head, torso, etc.), a dactylitis score (for the fingers, toes), and / or a bone erosion and joint space narrowing score (e.g., derived from an x-ray).

[0046] In other diseases, the anatomical score may relate to edema (excess fluid) on the retina in patients with age-related macular degeneration (ADM) or diabetic retinopathy, blood velocities (measured, for example, by Doppler echocardiography) in various heart valves (locations), and / or wall thickness in cardiomyopathies among heart failure patients, and the anatomical score may relate to T2 lesions in the brain of multiple sclerosis (MS) patients.

[0047] Structuring the medical dataset may further include determining an anatomical score from patient-level data of at least one patient using machine learning techniques and / or artificial neural networks, particularly deep neural networks. The anatomical score may be determined based on medical images (e.g., X-ray images, computed tomography (CT) scans, and / or magnetic resonance imaging (MRI), etc.), among others.

[0048] Structuring the medical dataset may further include determining statistical quantities of the medical data based on at least one matrix for each patient. The statistical quantities (e.g., averages, correlations, quantiles, and / or clustering, etc.) may be determined based on a subset of less than all patients in the dataset or based on all patients. Thus, the statistical quantities may be derived from the complete patient-level data.

[0049] For example, for two patients with joint scores x1 and x2, the sum x1+x2 or the difference x1-x2 can be computed by the corresponding matrix or vector operations, the result of which is again a matrix or vector.

[0050] The present invention further provides a data processing apparatus comprising a processor adapted to perform the steps of the method described above.

[0051] The invention further provides a computer program product comprising instructions, which when the program is executed by a computer, cause the computer to carry out the steps of the method described above.

[0052] The present invention further provides a computer-readable storage medium containing instructions which, when executed by a computer, cause the computer to perform the steps of the methods described above.

[0053] The present invention further provides a computer-implemented method for identifying a patient phenotype in a medical dataset comprising data of a plurality of patients and relating to at least one disease. A phenotype is defined as a composite of observed clinical traits. The method may include identifying clusters of patients, where the probability of a condition is homogenous within each cluster. In other words, each cluster may include patients associated with a given phenotype. The clusters may be identified using machine learning techniques and / or artificial neural networks, in particular deep neural networks.

[0054] Identifying clusters of patients may include, among other things, applying a hierarchical clustering algorithm (eg, Ward's method) to a portion of the medical dataset or to the complete dataset.

[0055] The method may further include applying the mixture model to clinical endpoints in the medical dataset.

[0056] The method may be used in combination with any of the methods described above. For example, the identified clusters may be used to determine a graphical representation of the data. The above matrix may be used to identify clusters of patients. The medical dataset may include one or more of the features identified above.

[0057] The method can be used in therapeutics, prognosis, and clinical judgment, and can be used in personalized medicine.In particular, clustering is based on the assumption that two patients will only share a cluster if they have a similar probability of symptom presence across all clinical variables.As a result, if a patient can be assigned to a certain cluster, individualized treatment based on the predetermined optimized treatment for the cluster is possible.

[0058] The advantageous embodiments will now be described in conjunction with the enclosed figures. [Brief description of the drawings]

[0059] [Figure 1] FIG. 1 illustrates an exemplary graphical representation of the human body. [Diagram 2] FIG. 1 is an exemplary diagram for navigating medical data. [Diagram 3] FIG. 1 illustrates an exemplary graphical representation of data. [Figure 4] FIG. 1 illustrates an exemplary client-server system that can be used to implement the present invention. [Diagram 5] FIG. 1 illustrates an exemplary interface that allows a user to select a disease. [Figure 6] FIG. 13 is a further exemplary diagram for navigating medical data. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0060] In Fig. 1, an exemplary graphical representation 1 of a human body is shown. The representation 1 is a 3D representation, which can be viewed from any direction with corresponding user input. Also, the user can zoom in on a desired area of ​​the representation 1. In other words, the graphical representation 1 is an interactive representation, in particular a rotatable and scalable representation. The graphical representation 1 can also be referred to as a "virtual patient".

[0061] Associated with certain elements of the graphical representation 1 are activatable buttons 2. For example, one activatable button 2 is associated with the head, another with the hands and a third with the feet. The activatable buttons 2 are fixed to respective parts of the representation 1 and thus to respective parts of the human body. Consequently, when the graphical representation 1 is modified, for example when rotated and / or scaled, the activatable buttons 2 remain displayed overlapping or adjacent to respective parts of the representation 1 as long as these parts are still discernible.

[0062] Upon activating one of the activatable buttons 2, the button 2 can change its color and / or shape, in this way the user can easily recognize the activated button and thus the associated part of the human body.

[0063] As described further below, a context menu may be displayed in response to activation of an activatable button 2. The availability of a context menu is indicated by a "+" symbol adjacent to the respective activatable button 2.

[0064] 2 illustrates an example view after activating an activatable button 2 associated with the foot and toes. A context menu 3 is displayed, offering a set of options (in this example, three).

[0065] Below this figure is a medical dataset, which comprises data of a number of patients and relates to at least one disease (notably psoriatic arthritis). The data in the dataset is associated with a corresponding part of the human body to which the data relates. In response to activation of the activatable button 2, a graphical representation of the data 4 associated with that part of the human body to which the activatable button 2 activated by the user input relates is displayed. The context menu 3 may further be used to determine the graphical representation of the data 4 and / or to select a subset of the data associated with the respective part of the human body. In the illustrated example, the context menu 3 allows to select a subset of data related to a particular symptom, for example dactylitis (referring to a sausage-like swelling of the toes that may be present with slight redness and deformation).

[0066] The data in the dataset may be structured in the form of at least one matrix. The matrix may include dactylitis scores of the fingers / toes. Each element of the matrix may relate to a different finger / toe. The matrix may relate to a single patient or an average patient. In other words, the matrix may include average scores.

[0067] Further, a context menu, not shown, may be provided for selecting one or more diseases, one or more treatments, and / or one or more data sources. A temporal control element, not shown, may be provided, for example in the form of a timeline, making it possible to select one or more time points to which the graphical representation of the data 4 should relate.

[0068] In the example illustrated in FIG. 2, the graphical representation of data 4 includes three donut charts, one for treatment with a 300 mg dose of a given substance, one for treatment with a 150 mg dose of the same substance, and one for treatment with a placebo. The percentages indicate the dactylitis resolution for the treatments. Such a graphical representation of data 4 allows a physician to easily and efficiently select an appropriate treatment or allows a patient to estimate the prospects for a cure.

[0069] Other charts are possible as well. In particular, the graphical representation of the data 4 may illustrate different time snapshots of the time evolution of the characteristics of the underlying data.

[0070] The graphical representation of the data 4 may also include one or more graphical representations of the human body or parts thereof. For example, color coding may be used to indicate the severity of a condition (e.g., joint pain for various joints). Such a graphical representation of the data is illustrated in FIG. 3. Three temporal snapshots illustrate the temporal evolution of a swollen or tender joint.

[0071] The dataset may also include one or more photographs (e.g., of a patient's skin). The graphical representation of the data 4 may display low-resolution versions of high-resolution photographs of the dataset (e.g., of two or more patients for a particular time point during treatment, or of one patient for two or more time points during treatment). Upon selection of a photograph via user input, the high-resolution photograph may be recalled and displayed. In this manner, efficient searching and recall of medical images is possible.

[0072] Instead of raw medical images, realistic representations may also be provided and / or one or more anatomical images (e.g., X-ray images, MRIs, CT scans, and / or angiograms, etc.) may also be provided.

[0073] As mentioned above, the context menu 3 may be used to select one or more diseases to which the data should pertain. Figure 5 illustrates an alternative interface for selecting one or more such diseases. In particular, a selection screen is displayed, which may include two or more selectable icons 5 associated with different diseases (in this example, associated with psoriatic arthritis and psoriasis, respectively). Upon selecting one of the selectable icons 5, the graphical representation may be restricted to data related to the selected disease. In addition, the available activatable buttons 2 may depend on the selected disease.

[0074] Fig. 6 shows another exemplary diagram for navigating medical data. As in the embodiment of Fig. 2, a graphical representation of a human body 1 is displayed next to a graphical representation of data 4. Additionally, an interface 6 is provided that allows the user to select a medication. The interface 6 is in this example a virtual switch, which allows to switch between medication A and medication B, respectively. Depending on the state of the virtual switch, the graphical representation of data 4 can be restricted to data related to the selected medication.

[0075] Moreover, a temporal control element is provided, in the example of Fig. 6, inter alia, in the form of a timeline 7. To select the point in time to which the graphical representation of the data 4 should relate, a slider element 8 is provided, which can be shifted along the timeline 7 to select the point in time.

[0076] The graphical representation 1 of the human body may be animated, e.g., it may perform movements and generate a realistic impression of a human. In particular, the graphical representation 1 of the human body may change depending on the displayed graphical representation of disease progression and / or data. For skin diseases, for example, the virtual skin of the graphical representation 1 of the human body may represent the skin pathology at a given snapshot in time.

[0077] The described method allows, for example, to navigate large medical data sets (such as those derived from clinical trials) in a very efficient and exemplary manner. It is then possible to see, for example, pathologies and their evolution for specific parts of the human body, for example in response to different drugs or different application rates. This can help the doctor in choosing the appropriate treatment or help the patient in predicting the further course of the disease.

[0078] The present invention may be embodied in a client-server architecture. Alternatively, the present invention may be embodied entirely on a single computing device, i.e., as a stand-alone solution. In the latter case, the single computing device may include one or more of the features described below with respect to the client.

[0079] A general client-server architecture for remote services is illustrated diagrammatically in FIG. 4. The arrangement includes one or more clients 100 in communication with one or more servers 200. The clients may be implemented in computing devices or client devices, as described below. The servers may be implemented in server devices provided by a service provider and / or a cloud provider. However, the present disclosure is not limited to these particular implementations, but may apply to any arrangement in which a local client (device) requests a service from a remote server (device) that is provided to the client by the server. Alternatively, as mentioned above, the present invention may be implemented solely in a local client.

[0080] It is understood that a service may be provided by a single or multiple servers or server devices, but may itself rely on a distributed system architecture. The servers may include, for example, a web server as a front end, an application server, and a database server. For simplicity, the remote entity providing the service will be referred to as a service provider hereinafter, whether it is a single server or server device, or a distributed or microservices-based system, etc. Moreover, the client is not limited to a single client or client device, but may itself include a distributed system. The client may further act as a server itself, for example, as an intermediate server, in a distributed environment. The term client is used herein to include any of the above architectures, and merely indicates that an entity 100 (e.g., a client device) receives a service from a remote entity 200 (e.g., a server device). With respect to aspects other than providing and receiving remote services, the client 100 and the server 200 may even exchange roles.

[0081] The clients 100 and the service providers 200 may be operatively connected to one or more respective client and server data stores (not shown), which may be used to store information local to the respective clients 100 and servers 200 (e.g., application code, application data, input data, output data, authentication data, etc.). Medical databases may be stored, for example, in the client data stores or the server data stores.

[0082] The client 100 and the service provider 200 can communicate information between each other using a communication framework, as indicated by the arrows. The information can include authentication information, such as keys and / or signatures for establishing a secure communication channel, one or more applications (e.g., as code or binaries), input and / or configuration data for execution of the remote applications, and output data of the remote applications. The information can further include keys and / or signatures for software authentication, as described below. Additionally, the applications can be provided as interpreted code to be executed by an interpreter.

[0083] In an Infrastructure as a Service (IaaS) architecture, a remote application may be provided by the client 100 and communicated to the service provider 200 via a communication channel before it is executed by the service provider. In this case, the remote service may include installing (e.g., compiling) or interpreting the application code received by the client, executing the received application as a remote application at the service provider's side, and communicating the results of the execution back to the client 100. In a Software as a Service (SaaS) architecture, the remote application is provided by the service provider itself, and the remote service may include executing the remote application against input data and / or configuration data received from the client 100, and communicating the results to the client.

[0084] The communication framework used for communication between the client 100 and the service provider 200 can implement any well-known communication technique and protocol. The communication framework can be implemented as a packet-switched network (e.g., public networks such as the Internet and private networks such as corporate intranets), a circuit-switched network (e.g., the public switched telephone network), or a combination of packet-switched and circuit-switched networks (with appropriate gateways and translators). The client-server architecture can include various common communication elements such as transmitters, receivers, transceivers, radios, network interfaces, baseband processors, antennas, amplifiers, filters, and power supplies. However, the embodiments are not limited to these implementations.

[0085] The communication framework can implement various network interfaces that are arranged to accept, communicate with, and connect to communication networks. A network interface can be viewed as a specialized form of input / output interface. A network interface can use connection protocols including, but not limited to, direct connection, Ethernet (e.g., thick Ethernet, thin Ethernet, and twisted pair 10 / 100 / 1000 Base T Ethernet), token ring, wireless network interface, cellular network interface, IEEE 802.1 1a-x network interface, IEEE 802.16 network interface, and IEEE 802.20 network interface. Additionally, multiple network interfaces can be used to engage with various communication network types. For example, multiple network interfaces can be used to enable communication over broadcast, multicast, and unicast networks. In cases where processing requirements dictate greater speed and capacity, a distributed network controller architecture can be similarly used to pool, load balance, and otherwise increase the communication bandwidth required by the client 100 and server 200. The communications network can be any one and combination of wired and / or wireless networks, including, but not limited to, direct interconnects, secure custom connections, private networks (e.g., corporate intranets), public networks (e.g., the Internet), personal area networks (PANs), local area networks (LANs), metropolitan area networks (MANs), Operating Missions as Nodes on the Internet (OMNIs), wide area networks (WANs), wireless networks, cellular networks, and other communications networks.

[0086] As mentioned above, the client 100 and the server 200 may each include a device that may be any electronic device capable of receiving, processing, and transmitting information (e.g., through a communication component). Examples of computing or electronic devices may include, but are not limited to, a client device, a personal digital assistant (PDA), a mobile computing device, a smartphone, a mobile phone, an e-book reader, a messaging device, a computer, a personal computer (PC), a desktop computer, a laptop computer, a notebook computer, a netbook computer, a handheld computer, a tablet computer, a server, a server array or server farm, a web server, a network server, an Internet server, a workstation, a network appliance, a web appliance, a distributed computing system, a multiprocessor system, a processor-based system, a consumer electronics device, a programmable consumer electronics device, a gaming device, a television, a set-top box, a wireless access point, a base station, a subscriber station, a mobile subscriber center, a radio network controller, a router, a hub, a gateway, a bridge, a switch, a machine, or a combination thereof. The embodiments are not limited in this context.

[0087] The device may perform processing operations or logic for one or several applications, such as the exemplary client application 110 and remote application 210, for a communication component, for an operating system, particularly an operating system kernel, and for other software elements using one or more processing components (i.e., processing circuits). A processing component or processing circuit may include various hardware elements, such as devices, logic devices, components, processors, microprocessors, circuits, processor circuits, circuit elements (e.g., transistors, resistors, capacitors, inductors, etc.), integrated circuits, application specific integrated circuits (ASICs), programmable logic devices (PLDs), digital signal processors (DSPs), field programmable gate arrays (FPGAs), memory units, logic gates, registers, semiconductor devices, chips, microchips, chipsets, etc. Examples of software elements may include a software component, a program, an application, a computer program, an application program, a system program, a software development program, a machine program, operating system software, middleware, firmware, a software module, a routine, a subroutine, a function, a method, a procedure, a software interface, an application program interface (API), an instruction set, computing code, computer code, a code segment, a computer code segment, a word, a value, a symbol, or any combination thereof.

[0088] A device may perform communication operations or logic for communicating with other devices using one or more communication components. The communication components may implement any well-known communication techniques and protocols, such as techniques suitable for use with packet-switched networks (e.g., public networks such as the Internet and private networks such as corporate intranets), circuit-switched networks (e.g., the Public Switched Telephone Network), or combinations of packet-switched and circuit-switched networks (with appropriate gateways and translators). The communication components may include various types of standard communication elements, such as one or more communication interfaces, network interfaces, network interface cards (NICs), radios, wireless transmitters / receivers (transceivers), wired and / or wireless communication media, physical connectors, and the like. By way of example and without limitation, communication media include wired and wireless communication media. Examples of wired communication media may include wires, cables, metal leads, printed circuit boards (PCBs), backplanes, switch fabrics, semiconductor materials, twisted pair wires, coaxial cables, optical fibers, propagating signals, and the like. Examples of wireless communication media may include acoustic, radio frequency (RF) spectrum, infrared, and other wireless media.

[0089] A device may communicate with other devices over a communication medium using communication signals such as those shown in Figure 1, via one or more communication components. The other devices may be internal or external to the device, as desired for a given implementation.

[0090] The device may be implemented in the form of a distributed system that may distribute portions of the structure and / or operations described above across multiple computing entities. Examples of distributed systems may include, but are not limited to, client-server architectures, three-tier architectures, N-tier architectures, tightly coupled or clustered architectures, peer-to-peer architectures, master-slave architectures, shared database architectures, and other types of distributed systems. The embodiments are not limited in this context.

[0091] The client 100 and / or the server 200 may include a computing architecture as described below. In one embodiment, the computing architecture may include or be implemented as part of an electronic device. Examples of electronic devices may include those described above. The embodiment is not limited in this context.

[0092] As used in this application, the terms "device," "component," "client," "server," "service provider," and "software provider" are intended to refer to computer-related entities, either hardware, a combination of hardware and software, software, or software in execution, examples of which are provided by the exemplary computing architecture described below. For example, a component can be, but is not limited to, a process running on a processor, a processor, a hard disk drive, multiple storage drives (optical and / or magnetic storage media), an object, an executable file, a thread of execution, a program, and / or a computer. By way of example, both an application running on a server and the server can be a component. One or more components can reside within a process and / or thread of execution, and a component can be localized on one computer or distributed among two or more computers. Furthermore, components can be communicatively coupled to each other by various types of communication media to cooperate in their operations. Cooperation can require unidirectional or bidirectional information exchange as needed. For example, components can communicate information in the form of signals communicated over a communication medium. Information can be implemented as signals assigned to various signal lines. In such an assignment, each message is a signal. However, further embodiments may alternatively use data messages. Such data messages may be transmitted across a variety of connections. Exemplary connections include parallel interfaces, serial interfaces, and bus interfaces.

[0093] The computing architecture may include various common computing elements, such as one or more processors, multi-core processors, co-processors, memory units, chipsets, controllers, peripherals, interfaces, oscillators, timing devices, video cards, audio cards, multimedia input / output (I / O) components, power supplies, etc. However, embodiments are not limited to implementations according to this computing architecture.

[0094] The computing architecture may include a processing unit, a system memory, and a system bus. The processing unit may be any of a variety of commercially available processors, including, but not limited to, AMD® Athlon®, Duron®, and Opteron® processors; ARM® Application, Embedded, and Secure processors; IBM® and Motorola® DragonBall® and PowerPC® processors; IBM and Sony® Cell processors; Intel® Celeron®, Core(2) Duo®, Itanium®, Pentium®, Xeon®, and XScale® processors; and similar processors. Dual microprocessors, multi-core processors, and other multi-processor architectures may also be used as the processing unit.

[0095] The system bus provides an interface for system components, including, but not limited to, a system memory to a processing unit. The system bus can be any of several types of bus structures that can be further interconnected to a memory bus (with or without a memory controller), a peripheral bus, and a local bus using any of a variety of commercially available bus architectures. Interface adapters can connect to the system bus through a slot architecture. Exemplary slot architectures can include, but are not limited to, Accelerated Graphics Port (AGP), Card Bus, (Extended) Industry Standard Architecture ((E)ISA), Micro Channel Architecture (MCA), NuBus, Peripheral Component Interconnect (Extended) (PCI(X)), PCI Express, and Personal Computer Memory Card International Association (PCMCIA), among others.

[0096] The computing architecture may include or be implemented with a computer-readable storage medium to store logic. Examples of computer-readable storage media may include any tangible medium capable of storing electronic data, including volatile or non-volatile memory, removable or non-removable memory, erasable or non-erasable memory, and writable or rewritable memory. Examples of logic may include executable computer program instructions implemented using any suitable type of code, such as source code, compiled code, interpreted code, executable code, static code, dynamic code, object-oriented code, visual code, and the like. Also, embodiments may be implemented at least in part as instructions contained in or on a non-transitory computer-readable medium, which may be read and executed by one or more processors to enable performance of the operations described herein.

[0097] The system memory can include various types of computer-readable storage media in the form of one or more faster memory units, such as read-only memory (ROM), random-access memory (RAM), dynamic RAM (DRAM), double-data-rate DRAM (DDRAM), synchronous DRAM (SDRAM), static RAM (SRAM), programmable ROM (PROM), erasable programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), flash memory, polymer memory, such as ferroelectric polymer memory, ovonic memory, phase-change or ferroelectric memory, silicon-oxide-nitride-oxide-silicon (SONOS) memory, magnetic or optical cards, arrays of devices, such as Redundant Array of Independent Disks (RAID) drives, solid-state memory devices (e.g., USB memory, solid-state drives (SSD)), and any other type of storage media suitable for storing information. The system memory can include non-volatile memory and / or volatile memory. A basic input / output system (BIOS) may be stored in the non-volatile memory.

[0098] The computing architecture may include various types of computer-readable storage media in the form of one or more slower memory units, including an internal (or external) hard disk drive (HDD), a magnetic floppy disk drive (FDD) for reading from or writing to a removable magnetic disk, and an optical disk drive for reading from or writing to a removable optical disk (e.g., CD-ROM, DVD, or Blu-ray). The HDD, FDD, and optical disk drive may be connected to the system bus by an HDD interface, an FDD interface, and an optical drive interface, respectively. The HDD interface for an external drive implementation may include at least one or both of Universal Serial Bus (USB) and IEEE 1394 interface technologies.

[0099] The drives and associated computer-readable media provide volatile and / or nonvolatile storage of data, data structures, and computer-executable instructions. For example, a number of program modules may be stored in the drives and memory units, including an operating system, particularly an operating system kernel, one or more application programs (also referred to herein as applications), other program modules, such as, for example, the exemplary client application 110 and the exemplary remote application 210, and program data. In one embodiment, the one or more application programs, other program modules, and program data can include, for example, various applications and / or components to implement the disclosed embodiments.

[0100] A user may input commands and information into a computing device through one or more wired / wireless input devices, such as a keyboard and a pointing device (e.g., a mouse, etc.). Other input devices may include a microphone, infrared (IR) remote control, radio frequency (RF) remote control, game pad, stylus pen, card reader, dongle, fingerprint reader, glove, graphic tablet, joystick, keyboard, retina reader, touch screen (e.g., capacitive, resistive, etc.), track ball, track pad, sensor, stylus, etc. These and other input devices are often connected to the processing unit through an input device interface that is coupled to the system bus, but may also be connected by other interfaces, such as a parallel port, IEEE 1394 serial port, game port, USB port, IR interface, etc.

[0101] A display device may also be connected to the system bus via an interface (e.g., a video adapter, etc.). The display device can be internal or external to the computing device. In addition to a display device, computing devices typically include other peripheral output devices (e.g., speakers, printers, etc.).

[0102] A computing device may operate in a networked environment using logical connections to one or more remote computers (e.g., remote devices, etc.) via wired and / or wireless communications. The remote devices may be workstations, server computers, routers, personal computers, portable computers, microprocessor-based entertainment appliances, peer devices or other common network nodes, and typically include many or all of the elements described with respect to the computing architecture. The logical connections may include wired / wireless connectivity to a local area network (LAN) and / or larger networks, e.g., a wide area network (WAN). Such LAN and WAN networking environments are commonplace within offices and companies, facilitating enterprise-wide computer networks (e.g., intranets, etc.), all of which may be connected to a global communications network (e.g., the Internet).

[0103] When used in a LAN networking environment, the device is connected to the LAN through a wired and / or wireless communication network interface or adapter. The adapter may facilitate wired and / or wireless communication to the LAN, which may also include a wireless access point disposed thereon for communicating with the wireless functionality of the adapter.

[0104] When used in a WAN networking environment, the device may include a modem or be connected to a communication server over the WAN or have other means for establishing communications over the WAN (e.g., via the Internet, etc.). The modem may be internal or external to the wired and / or wireless device, and the modem connects to the system bus via an input device interface. In a networked environment, program modules or portions thereof may be stored in a remote memory / storage device. It will be appreciated that the network connections are exemplary and other means of establishing a communications link between the devices may be used.

[0105] The client / server device is operable to communicate with wired and wireless devices or entities using the IEEE 802 family of standards (e.g., wireless devices operatively arranged for wireless communication (e.g., IEEE 802.11 radio modulation techniques, etc.). This includes at least Wi-Fi (or Wireless Fidelity), WiMax, and Bluetooth™ wireless technologies, among others. Thus, the communication can be of a predefined structure similar to a traditional network, or can simply be an ad-hoc communication between at least two devices. A Wi-Fi network uses a radio technology called IEEE 802.11x (a, b, g, n, etc.) to provide secure, reliable, and fast wireless connectivity. A Wi-Fi network can be used to connect devices to each other, to the Internet, and to wired networks (which use IEEE 802.3 related media and functions).

[0106] Although the previously discussed embodiments and examples of the present invention have been described separately, it should be understood that some or all of the features described above may also be combined in different manners. The embodiments discussed above are not intended as limiting, but serve as examples illustrating the features and advantages of the present invention. [Explanation of symbols]

[0107] 1. Graphic representation 2 Activatable Buttons 3 Context Menu 4. Data 5 Icons 6. Interface 7. Timeline 8. Slider Element 100 clients 110 Client Applications 200 Servers 210 Remote Applications

Claims

1. providing a medical dataset, the medical dataset comprising data for a plurality of patients and relating to at least one disease; associating the data in the medical dataset with a corresponding part of the human body to which the data relates; displaying a graphical representation (1) of said human body or of a part of said human body on a display device; displaying on the display device a number of activatable buttons (2) associated with different parts of the human body in the graphical representation (1); receiving a user input activating one of the plurality of activatable buttons (2); upon activation, displaying on the display device a graphical representation of the data (4) associated with that part of the human body to which the activatable button (2) activated by the user input pertains; Including, the step of relating the data in the medical dataset to a corresponding part of the body to which the data relates comprises the steps of providing at least one matrix for the data of each patient, the elements of the matrix being respectively associated with a predefined part of the body, and inputting at least a part of the data or quantities derived from the data into the at least one matrix, Computer-implemented methods.

2. 2. The computer-implemented method of claim 1, further comprising displaying a context menu (3) in response to the activation of the activatable button (2), the context menu (3) providing a set of options for determining the graphical representation of the data (4) and / or for selecting a subset of the data associated with each corresponding part of the human body.

3. The computer-implemented method of claim 1 or 2, wherein the graphical representation of the data (4) comprises one or more charts.

4. 4. The computer-implemented method according to claim 1, wherein the medical dataset comprises time-dependent data, and wherein the graphical representation of the data (4) comprises, inter alia, representations of different temporal snapshots of the data, and wherein a temporal control element, inter alia, in the form of a timeline, is provided for selecting one or more temporal snapshots to which the graphical representation of the data (4) should relate.

5. 5. A computer-implemented method according to any one of claims 1 to 4, wherein the graphical representation of the human body (1) or of a part of the human body is an interactive representation, in particular a scalable and / or rotatable representation.

6. The medical dataset relates to two or more diseases, and the method comprises: providing an interface that allows a user to select a disease; limiting the graphical representation of the data (4) associated with the part of the human body to which the activatable button (2) activated by the user input pertains to data related to the selected disease; The computer-implemented method of claim 1 , further comprising:

7. The medical data set relates to two or more drugs used to treat the at least one disease, and the method comprises: providing an interface that allows a user to select a medication; limiting the graphical representation of the data (4) associated with the part of the human body to which the activatable button (2) activated by the user input pertains to data related to the selected medication; The computer-implemented method of claim 1 , further comprising:

8. 2. The computer-implemented method of claim 1, wherein associating the data in the medical dataset with a corresponding part of the human body to which the data relates further comprises receiving and / or determining anatomical scores for each patient and storing them as entries in the at least one matrix.

9. 10. The computer-implemented method of claim 8, further comprising determining an anatomical score from patient-level data for at least one patient using machine learning techniques and / or artificial neural networks.

10. 10. A data processing apparatus comprising a processor adapted to carry out the steps of the method according to any one of claims 1 to 9.

11. A computer program comprising instructions which, when the program is executed by a computer, cause the computer to carry out the steps of the method according to any one of claims 1 to 9.

12. A computer readable storage medium containing instructions which, when executed by a computer, cause the computer to perform the steps of the method of any one of claims 1 to 9.

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