49 results about "Medical decision making" patented technology

A method and systems for managing a multi-domain health and wellness program using remotely located terminal devices, software agents and remotely stored participant information associated with definable access levels. The system referred to herein as Intelligent Health Management Technology (IHMT) system, provides assistance in regards to the management of chronic diseases in conjunction with multi-domain health and wellness programs. The system collects personal health information and medical record data and analyzes the information, and simulates medical decision-making process and is based on general medical decision making principles, common sense principles, and specific logic for a given IHMT module. As a result, customized recommendations are provided and may include computer generated recommendations and input from participating third parties (i.e., doctors, dieticians, pharmacists etc.).

The present invention relates to a system and method of medical knowledge domain modeling and automated medical decision-making, such as for online, questionnaire-based medical triage. In the present invention, information such as conditions and characteristics related to a diagnosis or disposition level is modeled in a Bayesian Network. The Bayesian Network may comprise instantiable nodes, fault nodes, intermediary nodes, a utility node and a decision node. Using Bayesian inference, the conditional probability of any pair in the network may be determined in real-time. These conditional probabilities are modified upon the input of evidence, which is typically in the form of answers to a dynamic set of questions designed to identify a diagnosis or disposition level for the patient under evaluation.

A multi-user system for creating and maintaining a knowledge base is implemented on a variety of computer systems, including single-user personal computers, networked personal computers, and data communications networks, including the Internet. The system has a graphic user interface which can be easily learned by non-programmers. The knowledge base is displayed as a hierarchical multiplicity of nodes, in which each node is related to one or more superior nodes. Title of text, rules, references, and attributes associated with each node are displayed, and may be modified. Simulation is used to verify the knowledge base once generated. Data may be extracted from the bases in the form of hard-copy books, databases for downloading into Web browsers, and databases for downloading into hand-held computers including a multiplicity of grids, and a multiplicity of branches in the form of a logic tree. The user may choose one of the alternative display formats, and the hierarchy can be displayed in either collapsed view or expanded view. Interference between two or more users accessing the system concurrently is prevented by a locking and authorization subsystem, which also prevents unauthorized access to the environment. The system provides an organization of workflow into a multiplicity of development stages. Each such stage has associated with it an authorization level, developers working on the system concurrently are limited by these levels to access only particular stages and levels of development.

Analysis of individual's serial changes, also referred to as the physiological, pathophysiological, medical or health dynamics, is the backbone of medical diagnosis, monitoring and patient healthcare management. However, such an analysis is complicated by enormous intra-individual and inter-individual variability. To address this problem, a novel serial-analysis method and system based on the concept of personalized basis functions (PBFs) is disclosed. Due to more accurate reference information provided by the PBFs, individual's changes associated with specific physiological activity or a sequence, transition or combination of activities (for example, a transition from sleep to wakefulness and transition from rest to exercise) can be monitored more accurately. Hence, subtle but clinically important changes can be detected earlier than using other methods. A library of individual's PBFs and their transition probabilities (which can be described by Hidden Markov Models) can completely describe individual's physiological dynamics. The system can be adapted for healthcare information management, diagnosis, medical decision support, treatment and side-effect control. It can also be adapted for guiding health, fitness and wellness training, subject identification and more efficient management of clinical trials.

Improved systems and methods for collecting Protected Health Information (PHI) with or without the assistance of a physician scribe are described. Documenting a patient encounter utilizing a template-based charting system (either electronic or paper-based), and the tracking of this document status and patient clinical status throughout the encounter, for purposes of managing multiple patients and multiple patients' documents, as well as improved communication between providers and assistants. The systems and methods of this invention generally comprise an electronic records system for creating and maintaining information in electronic records; patient tracking system (either computerized or not) for managing tasks specific to provider documentation of specific clinical care actions and patient clinical status; complimentary utilization of medical history questionnaires which are designed to correlate with template-based charting tools; methods of communication between provider assistants (including physician assistants, nurses, secretaries, scribes, patients, or other assistants) to convey the status of the collection and management of the PHI, including patient history, patient examination, testing results, medical decision making, patient disposition plan, follow-up information and other elements of provider charting of PHI; sequence of patient tracking indicators that represent steps in the care of the patient, status of the document, and clinical or documentation-related tasks for completion by providers or provider assistants; improvements on a real-time compliance system for identifying the specific stage or status of each electronic record, and allowing providers and assistants to track this completion status, thereby streamlining documentation and compliance workflows.

Systems and methods for measuring saliva sodium concentration using a chromatographic reaction enable rapid-results, low-cost diagnosis of various medical conditions in an outpatient setting. In one embodiment, measured patient saliva sodium concentration is used by the patient or the patient's healthcare provider to guide medical decision making. In another embodiment, measured patient saliva sodium concentration is processed to mechanically adjust the concentration of sodium in an aqueous solution to be delivered to the patient for oral administration. In yet another embodiment, a closed loop system measures saliva sodium concentration and uses any of a number of different types of feedback control systems to monitor and control the fluid and / or electrolyte state of the patient.

A medical decision support system including a computer and a computer program product arranged to provide data derived from examination of digital images of a tissue specimen according to predetermined criteria for histopathological analysis, and a method for assisting in obtaining a pathological diagnosis from a plurality of pictures representing a specimen on a slide, the method including obtaining digitized data corresponding to images of a specimen on a slide placed under a microscope; processing the images; examining the images in accordance with predetermined histopathological criteria; and providing an examination report based on the examination.

A medical decision making support apparatus performs the inference processing of obtaining an inference result by performing inference processing associated with medical diagnosis based on a plurality of pieces of input medical information, and the calculation processing of calculating the degree of denial or affirmation of the inference result in association with each of a plurality of partial sets including each medical information extracted from the plurality of pieces of medical information as an element. The medical decision making support apparatus presents a user an inference result obtained by the inference processing and negative information indicating medical information included in a partial set, of the plurality of partial sets, for which the degree of denial is calculated by the calculation processing.

The present invention relates to a system and a method of making optimal medical decisions. In one embodiment presented for illustration the system comprises a quantitative model of the disease in the form of transition probabilities, the quantitative model of the effect of the medical treatment (therapy, drug or remedy) on the course of the disease, the quantitative model of costs and benefits, including monetary as well as non-monetary costs and benefits, and the model of preferences with respect to the costs and benefits. Using probabilistic inference, distributions of parameters of models are extracted from the data and the opinions of parties involved in the medical treatment. An expectation of the value of the treatment is computed. Optimality of the treatment is achieved by choosing the treatment or its parameters that give the greatest value given the evidence, the models, and the preferences. Other embodiments are discussed.

The embodiment of the invention provides a medical data processing method, a medical data processing device, a computer readable medium and an electronic device. The method includes the steps of determining a disease recommended treatment scheme according to obtained illness state parameters of a current patient and medical experience, conducting matching in a medical history of historical patients to determine target medical history information according to the illness state parameters, and using the recommended treatment scheme and the target medical history information as medical decision making information of the current patient. Through the medical decision making information of the current patient determined by the technical scheme, the diagnosis and treatment scheme of the current patient is determined; meanwhile, considering the two factors of medical experience and clinical medical history, the management and analysis result practicability based on medical data can be easily improved, and then the obtained medical decision making information for disease treatment meets clinical use requirements.

The embodiment of the invention, which belongs to the technical field of data processing, relates to a medical data processing method and device. The method comprises: acquiring original medical record data that meets a preset condition and acquiring first medical decision-making information and first feature information of target medical record data from the original medical record data; traininga machine-learning-based original model based on the first medical decision-making information and the first feature information to obtain an auxiliary decision-making model; and predicting second feature information of a to-be-processed patient by using the auxiliary decision-making model to obtain second medical decision-making information of the to-be-processed patient. With the method provided by the invention, a problem of low accuracy rate of the recommended medical scheme based on the rule tree in the prior art is solved; and the accuracy of the recommendation of the medical scheme isimproved.

The present invention discloses a doctor recommendation system based on collaborative filtering. The system is characterized in comprising a patient characteristic extraction module, for automatically establishing basic data of a patient by determination, and establishing a complete patient database based on the input requirements; a patient similarity calculation module, for carrying out similarity calculation on the patient with other existing patients in the database through the database established by the patient characteristic extraction module, and obtaining a similarity value; and a recommendation system module, for carrying out collaborative filtering on similar cases by using the result provided by the patient similarity calculation module, recommending a doctor group and departments, tracking the results selected by the patient, and recording and transmitting the content selected by the patient and the click behavior. The system disclosed by the present invention helps the patient to accurately find a similar and successful diagnosis and treatment record, an appropriate doctor is recommended for the patient, and active doctor recommendation is converted to, so that quality of medical care and quality of service are improved, the patient is involved in and informed of the medical decision-making of the diagnosis and treatment process, and the doctor-patient relationship is improved.

The invention relates to the field of intelligent decision technology, and provides a data matching decision method based on multi-knowledge-database inference, a system, a device and a storable medium, wherein the method comprises the following steps of establishing a clinical auxiliary decision knowledge database, wherein the clinical auxiliary decision knowledge database at least comprises three sub knowledge databases: a transferring consultation recommending knowledge database, a medicine taking recommending knowledge database and a risk evaluation knowledge database; according to to-be-matched data information, matching knowledge information which corresponds with the data information in each sub knowledge database of the clinical auxiliary decision knowledge database; fusing knowledge information which matches each sub knowledge database according to a preset rule, and forming a final data matching decision. The method, the system, the device and the storable medium can effectively alleviate problems of one-sided knowledge database, low integrating performance and low applicability of an existing clinical auxiliary decision system, thereby improving diagnosis-and-treatment standardization of a community hospital, improving diagnosis-and-treatment capability level of community doctors and supplying the scientific and auxiliary medical decision for community clinical treatment.

The invention relates to an active health medical decision-making assisting method and device. The method comprises the following steps: obtaining the individual features of a patient group with various health problems and diseases as a training sample, carrying out the training through a machine learning method or a deep learning method, and generating a disease risk assessment model corresponding to the health problems or diseases; pre-compiling health medical decision-making auxiliary schemes corresponding to various diseases, and storing the compiled health medical decision-making auxiliary schemes into a health medical decision-making auxiliary database; crawling individual data of the user from a multi-source heterogeneous health medical platform, and performing preprocessing and cleaning to obtain individual features of the user; inputting the individual characteristics of the user into a health assessment model, and outputting health problems or diseases that the user may suffer from; and obtaining a health medical decision-making auxiliary scheme corresponding to the health problem or disease from a health medical intervention database according to the disease that the user may suffer from, and sending the health medical decision-making auxiliary scheme to the user after cooperative processing by a doctor.

The invention relates to the field of big data, and discloses a video inquiry method, a device, equipment and a storage medium. The method comprises the steps of obtaining user inquiry data based on preset intelligent sensing equipment, and performing pre-diagnosis on the inquiry data to obtain a pre-diagnosis result; when the pre-diagnosis result is not matched with the illness corresponding to the user, receiving an inquiry request uploaded by the user side, and determining a department allocated to the user according to the inquiry request; acquiring a medical knowledge graph corresponding to the department, and analyzing the user inquiry data according to the medical knowledge graph to obtain medical decision information; diagnozsthe user is diagnosed according to the medical decision information, and a final diagnosis result is generated. According to the method, the convenience of online medical treatment and the professional property of a traditional medical institution hospital are combined, the illness state of a user group is predicted through a large amount of collected patient data, and the technical problem that an existing video inquiry mode is low in diagnosis accuracy is solved.

In a further aspect of the invention, the calculated results may be communicated as a graphical output 196, such as is illustrated in FIG. 27. The graphical output 196 may be accessed by pressing a graph report button 198 on the report output dialog box (FIG. 26). The graphical output 196 is useful to further illustrate to the physician and the patient the changes in the calculated risk value over time, and in relation to the cholesterol levels. The graphical output 196 is also useful as a further tool in enabling a patient to understand the relationship between their health habits and the associated risk factor, and in encouraging the patient to participate in their own medical decision making.

A method for generating a medical suggestion useful for supporting a process of medical decision making is presented. A database with a particular, advantageous structure and content allows for the efficient evaluation of received known medical facts based on a set based processing and calculation. Thus, a digital, automatic, and holistic method generating a medical suggestion is provided, which increases the reliability of the selected medical suggestion which is provided to the user as most probable. The structure of the herein provided database provides for maintenance advantages of the database as the complexity is reduced and single structures of the database are manageable and easily understandable. A corresponding medical decision support system is presented as well.

A method (and the associated system) for risk evaluation in a vascular region of interest V are provided, making it possible, based on a fluidic study and / or on a treatment algorithm using a learning method, to generate risk models MR predictively indicating the risk level NR for the occurrence of events such as: occurrence and rupture of an aneurysm, coarctation, etc., and the associated anatomical areas. The models MR are intended to serve as an assistance support for the medical decision-making of a physician.

Systems and methods are provided for providing decision making support in healthcare. A user is able to provide healthcare data, including qualifier, indications, body part modifiers, body parts, modality modifiers, modalities, procedures and protocols. A graphical user interface (GUI) is provided to allow procedure rules to be created by selecting components of the healthcare data. The procedure rules identify and recommend appropriate procedures based on user input. The GUI also allows for global rules, body part rules, modality rules and modality modifier rules to be created; these rules are contra-indicators to procedures. Upon establishing the rules, a physician can enter data about a patient into the system, and the system will use the rules to return one or more appropriate procedures.

The invention relates to an intelligent active cardiopulmonary resuscitation instrument. The technical scheme adopted by the invention lies in that the intelligent active cardiopulmonary resuscitationinstrument comprises a cardiopulmonary resuscitation system which can be mounted on a stretcher in a sliding manner, wherein the cardiopulmonary resuscitation system comprises a supporting structure,a control device, a monitoring device, a pressing device, a defibrillation device and a respiratory device; the pressing device is arranged on the upper part of the supporting structure, and comprises a pressing machine and a vacuum generator which is connected with the pressing machine; the pressing machine comprises a main pressing machine and an auxiliary pressing machine; the auxiliary pressing machine comprises at least two auxiliary pressing suckers; the auxiliary pressing suckers are connected with the defibrillation device; and the defibrillation device comprises a cardioversion electrode piece which is arranged in each auxiliary pressing sucker. Through the adoption of the intelligent active cardiopulmonary resuscitation instrument disclosed by the invention, in order to solve the problems that the medical care professional background of masses is still insufficient and a conventional cardiopulmonary resuscitation instrument cannot automatically adjust the pressing depth, thecardiopulmonary resuscitation instrument which is capable of performing medical decision making, automatically adjusting the pressing depth and performing active decompressing is designed, and increasing the success rate of cardiopulmonary resuscitation is facilitated.

A method for determining a patient radiation and diagnostic study score associated with past diagnostic radiologic tests. In light of the obvious benefits of diagnostic radiology, the risks inherent in its use are often overlooked. Ionizing radiation, which is a component of much, but not all, diagnostic radiology, carries with it a small risk of inducing cancer every time it is used. This additional risk, known as “Lifetime Attributable Risk,” is layered on top of an individual's lifetime base risk of invasive cancer. The present method for determining a patient radiation and diagnostic study score provides right time, right place, and right format radiology information to assist providers in their medical decision-making. With greater awareness of recent study history, and individually contextualized risk and benefit considerations, providers are more likely to decrease their overall usage of diagnostic radiology and better counsel their patients on future risk.

The invention provides a medical decision method, a medical decision device, electronic equipment and a computer readable storage medium, and belongs to the technical field of artificial intelligence.The method comprises the steps of acquiring initial medical information of a target object, wherein the initial medical information comprises basic information and symptom information of the target object; processing the initial medical information through a first model for obtaining an intermediate decision result of the target object; generating characteristic data of the target object according to the initial medical information and the intermediate decision result; and processing the characteristic data through a second model, and obtaining a final decision result of the target object. The medical decision method can improve accuracy of the medical decision result and realizes intelligence of a medical decision process.

The embodiment of the invention relates to the technical field of knowledge maps, and particularly provides an information search method and device and a storage medium. Medical search content submitted by a user through a client is obtained; generating at least two text query statements according to the medical search content; querying in the created medical knowledge graph through the at least two text query statements to obtain medical knowledge corresponding to the text query statements; reasoning the medical knowledge corresponding to the text query statement to obtain a search result; and outputting a search result to the client. Through the scheme, a user can simply and quickly search medical knowledge through the client, and obtains a structured medical decision through reasoning, so that daily medical requirements of the user can be met. Besides, based on the text query statement, the medical knowledge is retrieved and reasoned, the appropriate medical knowledge can be quickly positioned and selected, and the accuracy and the acquisition efficiency of the medical knowledge are improved.

The invention provides a medical decision-making system based on medical big data and artificial intelligence, which belongs to the technical field of medical data mining and specifically comprises a medical big data system, a data uploading module and a hospital system. The medical big data system is responsible for processing the uploaded data of the data uploading module, generating symptom keywords of a patient to be treated, performing similarity matching on the symptom keywords of the patient to be treated and symptom keywords of historical clinical symptoms, and obtaining similar diagnosis and treatment cases; extracting clinical diagnosis and treatment inspection information data, and matching the clinical diagnosis and treatment inspection information data with the clinical diagnosis and treatment inspection information data of the similar diagnosis and treatment cases to obtain a consistent diagnosis and treatment case; extracting clinical diagnosis and treatment image information of the patient to be treated, and matching the clinical diagnosis and treatment image information with the clinical diagnosis and treatment image information conforming to the diagnosis and treatment case to obtain a matched diagnosis and treatment case; the data uploading module is responsible for uploading the uploading data; and the hospital system is responsible for generating uploading data and pushing the matched diagnosis and treatment case to a diagnosis doctor, so that accurate and rapid medical record matching is realized.

The invention discloses an improved Apriori algorithm, and an application of the same in Tibetan-medicine association mining, capable of converting a transaction database into a Boolean matrix only byscanning the transaction database for one time, and then converting scanning of the transaction database into vector operation. In the matrix, rows represent transactions, columns represent data items, and if one item is appears in a transaction, the item is represented by 1, and the item is represented by 0 if the item does not appears. The Boolean matrix is more compact than the transaction database as the Boolean matrix does not need to scan the data set repeatedly, and the support degree is calculated by vector operation. The improved vector-based Apriori algorithm is significantly betterthan the original Apriori algorithm. The improved Apriori algorithm is applied to the field of Tibetan medicine diagnosis and treatment to assist medical decision-making analysis, can help Tibetan medical workers to obtain useful information in a timely and accurate manner, can effectively avoid medical errors, can improve the modernization level of Tibetan medicine, and can provide a powerful tool for assisting Tibetan medicine diagnosis and treatment by using the advanced science and technology.