30 results about "Medical guideline" patented technology

Medical guidelines are generated based on the history of the medical records for a large patient population, which includes creating a patient trajectory graph from the records including nodes and edges by automatically clustering patients based on relevant the patients' features included in their medical records. The nodes are scored based on the time patients remain with the nodes and desirability of any associated outcomes, resulting in edge scores derived from the scores of the edge-connected nodes. Top ranked interventions obtained from the edge scores that evaluates whether a transition from one node to another is better or worse are included in the generated medical guidelines. Additionally, effect sizes and confidence intervals of medical treatments for a pre-defined patient population are estimated by using the patients' medical records and dividing the population in an exposed and non-exposed group. Estimates are based on match choices between exposed and non-exposed patients.

A medical support system and method for performing at least one medical support process relating to diagnosis and treatment of a medical condition and that includes or employs medical records relating to patients and medical support databases including medical guidelines for the diagnosis and treatment of a medical condition. A medical support process includes one or more process phases, which may include a data phase, a diagnostic phase and a therapy / treatment recommendation phase. Each process phase includes one or more process operations wherein each of the process operations of a process phase includes one or more process forms providing interfaces between a user and the process operations. Each process form includes fields for passing user inputs to the process operations and for displaying the results of the process operations to the user and the support processes are responsive to user inputs, the medical records and the guidelines to execute an interactive dialogue between the medical support process and the user to provide guidance to the user in performing the medical support process according to the guidelines and dependent upon the user inputs and the medical record.

A medical guideline integration engine is presented. The engine imports medical guideline information from disparate sources based on various guideline standards into a knowledge base. The knowledge base houses the information in a database. Upon request, the engine retrieves the information from the knowledge base and converts the information into a desired guideline format.

The invention relates to a system (100) for mapping a patient data structure (PD) for describing a patient's case into a guideline data structure (GD) for describing a medical guideline, the system comprising storage (170) for storing:a plurality of data items (DI1; DI2; . . . ; DI99);the patient data structure (PD) comprising data items (DI1; DI3; DI5; DI27; DI47, DI67, DI74) of the plurality of data items (DI1; DI2; . . . ; DI99);the guideline data structure (GD) comprising a guideline graph (GG), wherein the guideline graph (GG) is a directed graph, the guideline graph (GG) comprising action nodes (AN1; AN2), wherein each action node (AN1; AN2) is associated with an action; the system further comprising a linker (110) for linking data items (DI1; DI3; DI5; DI27; DI47, DI67, DI74) comprised in the patient data structure (PD) to action nodes (AN1; AN2) of the guideline graph (GG), based on a relation between said data items and actions associated with said action nodes (AN1; AN2), thereby mapping the patient data structure (PD) into the guideline data structure (GD). By decoupling the data input functionality and the medical guideline functionality, the use of the medical guideline of the invention imposes fewer constraints on the quality and completeness of the available patient data. Advantageously, mapping the patient data structure into the guideline graph of the guideline data structure provides an easy way of implementing and visualizing a personalized medical guideline which coincides with the general guideline requirements.

The invention relates to the technical field of artificial intelligence, and provides a treatment recommending method, system and device, and a storage medium. The treatment recommending method includes the steps: regularizing the treatment decision knowledge in a medical guide into guide rules, wherein the guide rules provide the confidence according to the source and the level of evidence, and include three elements: features, operators and thresholds; according to the guide rules and the basic information, diagnosis results, test and inspection results, and medication history of a patient,constructing a decision tree model; and according to the constructed decision tree model, accurately clustering the clinically similar patients, and analyzing the medication modes of the similar patients, thus achieving personalized recommendations for treatment. The treatment recommending method, system and device, and the storage medium can solve the problems of inaccuracy of a traditional treatment recommendation scheme.

An embodiment of the invention discloses a therapeutic scheme selection method and a therapeutic scheme selection system. The therapeutic scheme selection method comprises the steps of: acquiring patient information; selecting all available therapeutic schemes from a therapeutic scheme list according to the patient information and medical guideline recommendations, wherein the therapeutic scheme list is determined in advance according to clinical data and the medical guideline recommendations; acquiring a machine learning model corresponding to each available therapeutic scheme, wherein the machine learning model comprises at least two machine learning sub-models, each of which is determined in advance based on the clinical data; regarding the patient information as input of the machine learning sub-models in each machine learning model, and determining an available probability value of each available therapeutic scheme according to output of each machine learning sub-model; and determining a recommended scheme according to each available therapeutic scheme and the corresponding available probability value. Therefore, the intelligent determination of availability of each therapeutic scheme is realized, and a reference is provided for the doctor to select the optimal therapeutic scheme.

The invention discloses a medical guide mapping construction search system and method for an intelligent question-answering system. The method comprises the following steps of: constructing a medicalguideline as a medical knowledge graph; representing the user input by using a matrix to obtain a keyword representation matrix, matching the keyword representation matrix with a knowledge graph representation matrix to calculate the matrix similarity, and outputting an inquiry result and the like according to the matrix similarity. The system and the method are beneficial to improving the efficiency and the accuracy of the inquiry of the intelligent question-answering system.

A medical support system and method for performing at least one medical support process relating to diagnosis and treatment of a medical condition and that includes or employs medical records relating to patients and medical support databases including medical guidelines for the diagnosis and treatment of a medical condition. A medical support process includes one or more process phases, which may include a data phase, a diagnostic phase and a therapy / treatment recommendation phase. Each process phase includes one or more process operations wherein each of the process operations of a process phase includes one or more process forms providing interfaces between a user and the process operations. Each process form includes fields for passing user inputs to the process operations and for displaying the results of the process operations to the user and the support processes are responsive to user inputs, the medical records and the guidelines to execute an interactive dialogue between the medical support process and the user to provide guidance to the user in performing the medical support process according to the guidelines and dependent upon the user inputs and the medical record.

A system includes an analytics unit (140), which compares a medical image (105) and associated information with a stored medical guideline (142), and identifies an error or a deviation (340) from the medical guideline based on the comparison.

An interactive clinical decision support system and method is presented. The support system includes a mobile device, a database having up-to-date medical guidelines, and a network. The support system may further include one or more sensors configured to provide patient information. The interactive method includes steps of calculating scores based on clinical studies, which use patient information to generate an initial management plan recommendation and management plan rating. The method further includes a clinician discretion factor to balance benefits, risks, burdens, and costs of obtaining unknown patient information. A significance value of each patient information which may result in a management plan with a stronger recommendation, is calculated and ranked according to the clinician discretion factor. A set of unknown patient information is presented as options for creating a clinical order that will be executed once selected.

The invention relates to a system (100) for mapping a patient data structure (PD) for describing a patient's case into a guideline data structure (GD) for describing a medical guideline, the system comprising storage (170) for storing: a plurality of data items (DI1; DI2; ...; DI99); - the patient data structure (PD) comprising data items (DI1; DI3; DI5; DI27; DI47, DI67, DI74) of the plurality of data items (DI1; DI2; ...; DI99); the guideline data structure (GD) comprising a guideline graph (GG), wherein the guideline graph (GG) is a directed graph, the guideline graph (GG) comprising action nodes (AN1; AN2), wherein each action node (AN1; AN2) is associated with an action; the system further comprising a linker (110) for linking data items (DI1; DI3; DI5; DI27; DI47, DI67, DI74) comprised in the patient data structure (PD) to action nodes (AN1; AN2) of the guideline graph (GG), based on a relation between said data items and actions associated with said action nodes (AN1; AN2), thereby mapping the patient data structure (PD) into the guideline data structure (GD). By decoupling the data input functionality and the medical guideline functionality, the use of the medical guideline of the invention imposes fewer constraints on the quality and completeness of the available patient data. Advantageously, mapping the patient data structure into the guideline graph of the guideline data structure provides an easy way of implementing and visualizing a personalized medical guideline which coincides with the general guideline requirements.

A system and method relate to dynamic financial models associated with financing, such as leasing or purchasing, equipment and / or services. The financial models may dynamically update a rate of payment based upon variable conditions. In one aspect, the financial models facilitate the lease of medical equipment. A rental rate for a piece of medical equipment being leased may be adjusted to account for changing conditions. The rental rate may be updated as a function of fluctuating health care insurance re-imbursement rates, fluctuating billing or other medical guidelines, the number and / or type of procedures being performed with medical equipment being leased, interest rates, and / or other factors. The dynamic calculation of the rental rate to reflect actual conditions may reduce financial risk posed to a medical practitioner or facility. Accordingly, a significant barrier of entering a highly specialized market associated with medical equipment and the medical services provided thereby may be alleviated.

Methods and systems for providing an interactive guideline are provided. In one example, a method comprises: receiving, from a database, data of a directed graph representing a medical guideline, the medical guideline including a decision tree including a plurality of clinical decisions and preconditions leading to at least some of the clinical decisions, the directed graph including a plurality of nodes representing the clinical decisions and the preconditions and edges connecting the plurality of nodes to represent dependency relationships among the clinical decisions and the preconditions; providing, via a navigation interface, a graphical representation of at least part of the directed graph; receiving, via the navigation interface, a selection of a node of the directed graph from the graphical representation; and based on the selection of the node, updating the graphical representation of the at least part of the directed graph to provide a navigation result of the medical guideline.

A system (100) for context aware medical recommendations includes a recommendation engine (138) and a user interface (122). The recommendation engine (138) identifies at least one suggested recommendation (140) according to a medical guideline and context in response to a first input indicating a finding (150) in a medical image (112) of a patient. The user interface (122) displays on a display device (120) the at least one suggested recommendation selectable as a second input.

The invention provides a medical care network. A system operable to send medical care data to a user device is provided. The user device is configured to analyze the medical information. The system maintains, in a database, data representing a first directed graph representing at least a portion of a medical guideline and a plurality of patient models including medical care data. The system selects an element from the first directed graph by processing the plurality of patient models and the data representing the first directed graph. A first patient group and a second patient group are identified based on a combination of the selected element and the plurality of patient models, the treatment of the first patient group deviating from at least a portion of the medical guideline at the selected element. At least one patient group characteristic that distinguishes the first patient group from the second patient group is determined by processing the plurality of patient models. A second directed graph is generated based at least on the identified at least one patient group characteristic, and the second directed graph is sent for receipt by the user device.

The invention provides for a medical instrument (200, 300, 600) comprisines a medical guideline database (218, 608) containing a set of clinical guidelines for cervical cancer. The medical instrument further comprises a memory (214) for storing machine executable instructions, wherein execution of the instructions causes a processor to: receive (100) demographic data (230) of a subject; receive (102) symptom data (232) descriptive of the subject; receive (104) screening test data (222) descriptive of the subject; select (106) a screening guideline subset (234) of the set of clinical guidelines in accordance with the demographic data, the symptom data, and the screening test data; generate (108) a colposcopic inspection request (236) using the screening guideline subset; receive (109) colposcopic data (235) acquired by a colposcope; and select (110) a colposcopic guideline subset (238) of the set of clinical guidelines in accordance with the demographic data, and the colposcope data.

A tumor tracking device (110) includes a guideline engine (130), a detection engine (132), and a user interface (134). The guideline engine (130) receives a current measurement and a plurality of prior measurements of at least one lesion according to a medical image of a subject, each of the current and the plurality of prior measurements identified chronologically, and calculates growth between the current measurement and a most recent measurement of the plurality of prior measurements. The detection engine (132) calculate growth between the current measurement and each of non-most recent measurements of the plurality of prior measurements, and identified at least one of the non-most recent measurements in response to calculated growth between the current measurement and each of non-most recent measurements of the plurality of prior measurements exceeding a threshold according to a medical guideline and the calculated growth between the current measurement and a most recent measurement of the plurality of prior measurements failing to exceed the threshold. The user interface (134) displays on a display device (136) an indicator (138) of the identified at least one of the non-most recent measurements of the at least one lesion.

The invention provides a method for intelligently providing targeted medical suggestions. The method comprises the following steps: establishing a medical guide database; identifying the medical datainformation of a patient uploaded by a patient terminal; performing operation screening in a medical guide database according to the medical data information of the patient to generate a guide suggested value, and transmitting the guide suggested value to a doctor terminal; if the doctor of the doctor terminal considers that the guide suggestion value is reasonable, generating medical suggestionsafter confirmation, and transmitting the medical suggestions to the patient terminal; and if the doctor at the doctor end considers that the guide suggestion value is unreasonable, modifying the guidesuggestion value into a reasonable medical suggestion, and transmitting the medical suggestion to the patient terminal.

The invention discloses an interactive training method and system for a medical guideline. In the interactive training method of the present invention, first construct the knowledge map library of the medical guideline, and create a training system based on this to conduct interactive learning with the learners, that is, gradually display the clinical steps and knowledge of the medical guideline according to the interactive operation of the learners Points and related literature and other learning content, breaking through the traditional medical guideline presentation is limited by page or paper size, expand the guideline content step by step, and browse the guideline content by scrolling and zooming in the window; The electronic representation enables the system to have the ability to calculate knowledge, so that after the learning is completed, the training system automatically generates test questions and automatic judgment questions based on the knowledge map and pre-stored patient data, thereby giving learners accurate and timely learning interactions and improving learners Learning efficiency, and then provide patients with higher quality and more standardized diagnosis and treatment services in clinical practice.

A medical guideline integration engine is presented. The engine imports medical guideline information from disparate sources based on various guideline standards into a knowledge base. The knowledge base houses the information in a database. Upon request, the engine retrieves the information from the knowledge base and converts the information into a desired guideline format.

The invention brings forward a patient-characteristic adaptive treatment scheme recommendation system based on medical big data analysis. The system includes a data layer, an engine layer and an application layer, integrates a plurality of treatment recommendation models aiming at multi-scale characteristics, and filters in combination with medical guidelines. When a user inputs a certain characteristic value, the system can give an appropriate treatment scheme recommendation; and with the gradual accumulation of characteristics, the accuracy of recommendation is getting higher and higher. Theinvention also provides a patient-characteristic adaptive treatment scheme recommendation method based on the above system.

The present invention provides a medical guideline and data-driven treatment plan recommendation system, including training a data-driven recommendation model; establishing a classification list of treatment plans to determine the mapping relationship between coarse-grained treatment plans and fine-grained treatment plans; Use the recommended treatment plan of the data-driven recommendation model as the first recommended treatment plan; use the recommended treatment plan of the medical guideline rule base as the second recommended treatment plan; classify the first recommended treatment plan and the second recommended treatment plan according to the treatment plan Filtering is performed, and the filtered recommended treatment plan is obtained as the third recommended treatment plan, and the third recommended treatment plan is recommended to the target case. The invention integrates the respective characteristics of medical guidelines and data-driven, recommends more reasonable treatment plans, and reduces decision-making risks. The recommended scheme obtained by the present invention can not only be rationally explained by medical guidelines, but also can be supported by historical cases as evidence, and can be more convincing to patients.

A system includes an analytics unit (140), which compares a medical image (105) and associated information with a stored medical guideline (142), and identifies an error or a deviation (340) from themedical guideline based on the comparison.

The invention discloses an intelligent auxiliary diagnosis method for thyroid diseases, and the method comprises the following steps: constructing a rule decision-making tree according to related medical guidelines, and the rule decision-making tree comprises a plurality of judgment nodes; embedding a machine learning model in each judgment node of the rule decision tree; processing the case data of the patient to obtain thyroid judgment data of the patient; importing thyroid judgment data of the patient into the rule decision tree for judgment to obtain a thyroid diagnosis result and statistical indexes of the patient; and outputting a diagnosis report according to the thyroid diagnosis result and the statistical indexes. The intelligent auxiliary diagnosis method can assist doctors in diagnosing thyroid diseases. The invention further discloses an intelligent auxiliary diagnosis system for thyroid diseases and a readable storage medium.

A system for generating a mitochondrial dysfunction nourishment program includes a computing device configured to obtain a biological indicator, produce a mitochondrial profile as a function of the biological indicator, wherein producing further comprises identifying a probabilistic vector as a function of a medical examination, and producing the mitochondrial profile as a function of the probabilistic vector and the biological indicator using a profile machine-learning model, identify a biological modification as a function of the mitochondrial profile, wherein identifying the biological modification further comprises receiving a medical guideline, and identifying the biological modification as a function of the medical guideline and mitochondrial profile using a biological machine-learning model, determine an edible as a function of the biological modification, and generate a nourishment program as a function of the edible.

The invention discloses a system and method for constructing and searching medical guideline graphs for an intelligent question answering system. The characterization matrix is ​​matched with the knowledge map characterization matrix to calculate the matrix similarity, and the consultation results are output according to the matrix similarity; the invention is beneficial to improve the efficiency and accuracy of the intelligent question answering system consultation.

A system (100) for context aware medical recommendations includes a recommendation engine (138) and a user interface (122). The recommendation engine (138) identifies at least one suggested recommendation (140) according to a medical guideline and context in response to a first input indicating a finding (150) in a medical image (112) of a patient. The user interface (122) displays on a display device (120) the at least one suggested recommendation selectable as a second input.