59 results about "Treatment decision making" patented technology

Pain factors are labeled with targeted agents or markers delivered into the body. The labeled pain factors are imaged with appropriate imaging tools in a manner allowing selective identification and localization of areas of pain source or transmission. The labeled pain factors allow spatial differentiation in the imaging sufficient to specify the location of the pain so as to drive therapeutic decisions and techniques in order to treat the pain. Pain factors labeled and imaged in this manner may include one or more of nerve factors, blood vessel factors, cellular factors, and inflammation factors. Labeled markers may include for example radioactive materials (e.g. tritiated or iodinated molecules) or other materials such as metal (e.g. gold) nanoparticles. Intermediary binding materials may be used, such as for example bi-specific antibodies. Therapeutic components of the system and method include for example localized energy delivery or ablation treatments, or local drug or other chemical delivery. Locations containing pain factor selectively bound by targeted agents are selectively treated with directed energy into a region containing the targeted agent bound to the pain factor.

A treatment algorithm for managing hemodynamically unstable patients is provided. Specifically, measurements of arterial pressure and stroke volume can be used to calculate pulse pressure variation, stroke volume variation, mean arterial pressure, elastance and cardiac power, the values of which guide treatment decisions and allow optimal management of critically ill patients. In an additional embodiment, a computer system implementing the treatment algorithm is provided.

A system provides early prediction of heart tissue malfunction and electrophysiological pathology by determining anatomical tissue impedance characteristics for use in medical patient monitoring and treatment decision making. At least one repository of data indicates multiple predetermined expected impedance value ranges for corresponding multiple impedance measurements taken at multiple particular different sites of at least one anatomical organ. An impedance measurement processor automatically determines whether multiple measured impedance values taken at multiple particular different sites of an anatomical organ using an invasive catheter are within corresponding multiple predetermined expected impedance value ranges derived from the at least one repository. An output processor automatically communicates data comprising at least one message to a destination. The at least one message includes data indicating whether the multiple measured impedance values taken at the multiple particular different sites of the anatomical organ are within the corresponding multiple predetermined expected impedance value ranges.

Pain factors are labeled with targeted agents or markers delivered into the body. The labeled pain factors are imaged with appropriate imaging tools in a manner allowing selective identification and localization of areas of pain source or transmission. The labeled pain factors allow spatial differentiation in the imaging sufficient to specify the location of the pain so as to drive therapeutic decisions and techniques in order to treat the pain. Pain factors labeled and imaged in this manner may include one or more of nerve factors, blood vessel factors, cellular factors, and inflammation factors. Labeled markers may include for example radioactive materials (e.g. tritiated or iodinated molecules) or other materials such as metal (e.g. gold) nanoparticles.

The invention discloses a diagnosis and treatment decision-making support system. The system includes a human-computer interaction unit, a processing unit, a decision-making support unit and a database unit, wherein the human-computer interaction unit is used for a user to exchange data with the diagnosis and treatment decision-making support system, the processing unit is connected with the human-machine interaction unit and is used for performing business and data processing, the decision-making support unit is connected with the processing unit and is used for feeding back decision-making schemes according to input data, and the database unit is used for storing medical treatment data to provide a data foundation for the decision-making support unit. The system of the invention can maximally conform to actual clinical diagnosis and treatment processes and provide full-process diagnosis and treatment decision-making services for doctors. With the diagnosis and treatment decision-making support system of the invention adopted, diagnosis and treatment schemes and suggestions can be provided for doctors; the doctors can be assisted to improve decision-making levels; the doctors canbe prompted with potential errors; diagnostic suggestions and decision-making schemes can be provided according to the disease conditions of specific patients, so that the doctors can be assisted to comprehensively understand a wide range of possibilities; the doctors can be assisted to make better decisions, so that a misdiagnosis rate can be reduced; and the system can be combined with the actual diagnosis and treatment processes, so that the actual diagnosis and treatment processes can be standardized.

A system and (or) method, for use with a computer system, recommends a treatment among a plurality of treatment options for a given medical condition of a patient. To that end, the system and method receive patient information related to the patient and the medical condition, and search, at least in part in a computer process, a database with a plurality of indexed studies relating to the plurality of different treatment options for the given medical condition. The system and method then assign, at least in part in a computer process, a study value to each of the plurality of studies, and determine the applicability of the studies to the patient using the patient information to produce a plurality of applicability values. At least the study values and the applicability values are used to generate treatment scores for the treatment options for generating a report listing the treatment options and a) the treatment scores and / or b) information derived from the treatment scores.

A system provides clinicians with realtime medication suggestions. A treatment decision support system comprises at least one repository including information associating candidate treatment items, treatment costs, treatment supply availability, patient specific medical information and corresponding related treatment parameters. An individual treatment item is associated with multiple related treatment parameters. A communication processor accesses the information in the at least one repository. A treatment decision processor uses accessed information provided by the communication processor for providing data representing candidate treatments in response to user entry of data identifying an initial treatment based on both clinical and non-clinical factors. The non-clinical factors include lowest cost and availability and the clinical factors include patient specific medical information and predetermined treatment guidelines for treating a particular medical condition. A display processor provides data representing at least one display image identifying the candidate treatments.

The invention discloses a cardiovascular slow disease management method based on intelligent decision support technology, and the method comprises the steps of S1 creating a patient's health archive; S2 assessing cardiovascular disease thrombus and hemorrhage risk; S3 tracking anticoagulant treatment curative effect and predicting medicament interruption risk; S4 long-term following a discharged or a treated cardiovascular disease patient with structured disease; S5 being supported by the doctor; and S6 being supported by the patient. The method is fused with Internet communication technology; a risk early warning model is established; data analysis and an authoritative cardiovascular disease management guide are conducted; a set of treatment decision flow with data support at real time is constructed; the patient's risk change is monitored dynamically; and the doctor's guidance and the patient's participation are combined for self management; the data analysis model is used to provide a risk assessment related to the cardiovascular disease; the cardiovascular disease treatment effect is tracked; the customized risk list of the patient's long-term self management is grabbed automatically and provided according to the patient's situation; safe medicine usage is guaranteed; and life quality is improved.

The invention discloses a tumor accurate medicament taking interpretation system and a method thereof. The system comprises the components of a literature searching subsystem which is used for searching an outer database, obtaining a searching result, analyzing the searching result and preprocessing a literature resource which is uploaded by a user for using as a tumor medicament taking guidance evidence; a knowledge database subsystem which stores the tumor medicament taking guidance evidence and the related data of tumor medicament taking; a knowledge management subsystem which processes andupdates the tumor medicament taking guidance evidence and the related data of tumor medicament taking, thereby obtaining target knowledge; and a report processing subsystem which calls target knowledge according to variation data that are supplied by the user, performs interpretation, generates a tumor accurate medicament taking interpretation report and manages the report. The system and the method can realize medicament taking guidance in a multiple-gene-detecting-result layer of an individual and further have advantages of improving availability in medicament taking guidance, satisfying aclinical guidance requirement and assisting the clinical doctor in making a clinical medicament taking and treatment decision.

The present invention relates to a medical health data collection based intelligent health forecasting and decision-making system. The system is characterized by comprising the following steps: 1) data collection; 2) transmission of data to a cloud server, wherein a cloud ICVD paroxysm evaluation module processes the data; 3) doctor platform information processing; and 4) patient platform information processing. The cloud part of the scheme comprises a 10-year ischemic cardiovascular disease (abbreviated as ICVD) probability forecasting and doctor decision-making system. According to the scheme of the present invention, a cloud technology platform can assist doctors to collect health data of a patient, establish health records, and forecast a 10-year ICVD probability, so that a personalized health program is created for the patient, and the treatment decision-making system is established.

The invention provides a city operation management center system. The system includes: a city data opening and information service sub-system, which uniformly fuses and encapsulates user information resources; a city coordination processing and linkage command sub-system, which deeply mines business relationships between various departments, and establishes a complete coordination processing system of daily city running of and a linkage command system of emergency treatment; a cyberspace comprehensive-governance sub-system, which caries out comprehensive network security supervision on city key-information infrastructure running status, and realizes system response to a unified situation of city cyberspace security; city running simulation and overall-planning sub-system, which provides knowledge and intelligence support with data as drives for city development planning, major-affair decision-making and major-event treatment decision-making; and a city running display and monitoring and early-warning sub-system, which displays basic information of realizing city governance, provides key sign information of city running, and carries out macroscopic display and early-warning analysison city running status.

A method, system and article of manufacture for intelligence building in expert systems and, more particularly, for evaluating treatment decisions overriding recommended treatments that are generated by expert systems. One embodiment provides a method of evaluating treatment decisions, comprising receiving a specification of a decided treatment for a patient having a given disease. The decided treatment differs from a recommended treatment identified by an expert system in response to analysis of symptomatic data corresponding to the patient. The patient is monitored subsequent to being treated according to the decided treatment. The decided treatment is evaluated on the basis of data captured by the monitoring. On the basis of the evaluation, feedback with respect to the decided treatment and the recommended treatment is generated.

A system and method may generate a report to help decide among a plurality of treatment options for a medical condition. The system and method receive patient information and to generate a plurality of potential treatment options for the medical condition. The system and method also receive the patient's preference(s) for potential treatment outcomes of the treatment options, used to produce a preference value. The system and method also analyze indexed study data relating to the plurality of treatment options to produce based on the analysis a study score for each of the treatment options. For each treatment option, the system and method produce a treatment score based on at least the preference value and the study score, thus permitting generation of a report listing the treatment options and a) the treatment scores or b) the information derived from the treatment scores.

The invention relates to a stent delivery system integrating optical and ultrasonic image diagnosis and treatment functions. The stent delivery system is provided with a three-way connection, and the three-way connection is respectively connected with a connection end, a balloon tube and a protective tube. The connection end connects the device. The inside of the balloon tube is a protective tube, the proximal end of the balloon tube is connected to the propeller, the outside of the balloon is provided with a stent, the front end of the stent delivery system is provided with a probe, the protective tube at the front end of the probe is provided with a developing ring, and the front end of the protective tube is provided with a guide wire hole . The connector of the connection end is in the form of an integrated connector combining an electrical ferrule and an optical ferrule. The electrical ferrule and the optical ferrule are fixed inside the connector sheath. The probe integrates an acoustic probe and an optical probe, and both the acoustic probe and the optical probe are fixed on the shell. The system of the present invention has both diagnosis and treatment functions, can optimize and guide PCI treatment decision-making, and complete surgery at the same time, shorten operation time, improve operation success rate, and relieve patients' pain.

The invention relates to a prognosis prediction model for squamous cell carcinoma and application thereof. The prognosis prediction model is composed of biomarkers CFLAR, RGS19, PINK1, CTSD and related solutions. The invention also comprises application of a reagent for detecting the expression quantity of the biomarkers in preparation of a kit for evaluating the anti-tumor immunotherapy reactivity and prognosis survival of squamous cell carcinoma. According to the invention, screening and construction are carried out after whole transcriptome sequencing and machine learning of squamous cell carcinoma samples of large-sample anti-tumor immunotherapy, so that the reactivity of squamous cell carcinoma patients in anti-tumor immunotherapy can be efficiently and accurately predicted, effective guidance is provided for clinicians to make treatment decisions on squamous cell carcinoma patients, and the occurrence of invalid treatment is reduced, thereby reducing the treatment cost and discomfort experience of patients.

The invention provides a nasopharyngeal carcinoma database and a comprehensive diagnosis and treatment decision-making method based on the database, wherein the nasopharyngeal carcinoma database includes a large clinical databases and a gene database;the large clinical database records a first data formed by the clinical character digital information, and a second data extracted and recognized from the clinical image information; the first data, the second data and / or gene data in the nasopharyngeal carcinoma database are accompanied by time attributes; the first data, the second data and the gene data are all unitary data, while the nasopharyngeal carcinoma database comprises a multiple group database capable of storing the first data, the second data and the gene data; the data in thenasopharyngeal carcinoma database is used for supporting a diagnosis and treatment decision-making server to make diagnosis and treatment decisions based on a first model, a second model, a third model, a fourth model and / or a fifth model. The nasopharyngeal carcinoma database and the comprehensive diagnosis and treatment decision-making method based on the database can provide users with accurateintelligent diagnosis and decision-making service based on artificial intelligence, which has broad application prospects.

The invention provides compositions and methods for detecting thyroid hormone blocking immunoglobulin (TBI). The invention's methods are sensitive and specific for TBI, and may be used for the dual detection of both TBI and TSI. The invention's compositions and methods are useful for the diagnosis of diseases that are associated with the presence of TBI and / or TSI, for monitoring the progress of disease and / or treatment regimens, therapeutics, vaccines, etc., and for assisting clinicians in making treatment decisions.

Disclosed is an analytical test management system and method that can in certain embodiments reduce the likelihood that errors are made during the performance of combinations of analytical tests that together are used to provide an analytical result that can be the basis of a diagnosis or a treatment decision. In one embodiment, test orders submitted through a test order interface are received at a test manager module that decides whether the test order is for a simple test or whether the test order is for a combination of tests. If the test order is for a simple test, the test order is forwarded to an analyzer for processing. If the test order is for a combination of tests that together lead to a final result, the test order manager module assumes control over the test order and directs the analyzer according to secondary test requests, the results of which are used by the test order manager module to, for example, decide whether additional secondary test requests should be sent to the analyzer or make calculations used to provide the final result.

The disclosure provides population and non-population-based classifiers to categorize patients and cancers. The population-based classifiers disclosed integrate signatures, i.e., global scores related to the expression of genes in particular gene panels. The non-population-based classifiers are generated using machine-learning techniques (e.g., regression, random forests, or ANN). Each type of classifier stratifies patients and cancers according to tumor microenvironments (TME) as biomarker-positive or biomarker-negative, and treatment decisions are then guided by the presence / absence of a particular TME. Also provided are methods for treating a subject, e.g., a human subject, afflicted with cancer comprising administering a particular therapy depending on the classification of the cancer's TME according to the disclosed classifiers. Also provided are personalized treatments that can be administered to a subject having a cancer classified into a particular TME, and gene panels that can be used for identifying a human subject afflicted with a cancer suitable for treatment with a particular therapeutic agent.

The invention provides a tumor treatment auxiliary decision-making method based on reinforcement learning, and the method comprises the steps: constructing and training a patient state transition model and a treatment decision-making model, wherein the patient state transition model carries out the modeling of the state change of a tumor patient through a recurrent neural network, using a diagnosis and treatment scheme and examination indexes obtained in actual diagnosis and treatment as data sources, and simulating the state change of the tumor patient under a certain diagnosis and treatment scheme. The treatment decision model carrying out modeling on the process of treating a tumor patient through reinforcement learning, the patient state transfer model is used as a data source, a deep Q network (DQN) is constructed to serve as a strategy network, an excitation function is constructed on the basis of RECIST solid tumor curative effect evaluation standards and TNM tumor imageological staging standards, and iterative training is carried out. According to the method, the workload of tumor specialists can be reduced to a certain extent, the treatment means predicted by the model can serve as decision reference to reduce decision errors of doctors, and the doctors are assisted to specify feasible treatment schemes.

The invention provides an early prediction system for predicting the severity of an acute pancreatitis patient, and belongs to the field of prediction models. The prediction system is constructed by taking the age, respiratory rate, albumin, lactic dehydrogenase LDH, oxygen support and pleural effusion of a patient with acute pancreatitis as prediction indexes. The prediction system is simple in construction method and high in prediction accuracy and distinction degree, can accurately judge the early severity of acute pancreatitis patients, accurately judges the probability that the patients develop into severe acute pancreatitis, helps clinicians to obtain the maximum income when making clinical decisions, helps guide the clinicians to make individual treatment decisions, improves the survival rate of patients and is wide in application prospect.

Thousands of patients prone to irregular and sometimes life threatening heart rhythms have miniature heart-monitoring devices, such as defibrillators and cardioverters, implanted in their chests. These devices detect abnormal heart rhythms and automatically apply electrical therapy to restore normal heart function. Significant parts of these devices include the microprocessor and stored instructions, or algorithms, that govern how the devices interpret and react to electrical signals indicative of normal or abnormal heart rhythms. These algorithms generally use the time intervals between successive heart beats, or cardiac events, as a key factor in therapy decisions. To ensure accuracy of interval measurements, the inventor devised new methods for processing heart electrical signals, some of which ensure accurate interval measurements without unduly delaying therapy decisions or consuming significant battery power. One of these new methods detects an abnormal interval measurement and either disqualifies the abnormal interval from use in making therapy decisions or divides the abnormal interval into two or more other intervals, thereby facilitating identification and treatment of abnormal rhythmic conditions both efficiently and accurately.

The invention belongs to the technical field of intelligent medical treatment, and particularly relates to a model for predicting the RAS gene state of a patient suffering from advanced colorectal cancer liver metastasis based on radiomics characteristics and application of the model. According to the method, a model for predicting the RAS gene state of the advanced colorectal cancer liver metastasis patient based on the radiomics characteristics is successfully constructed, specifically, an enhanced CT image of the patient before initial treatment is collected, the radiomics characteristics are extracted, 12 radiomics characteristics are obtained through 1000 times of Lasso-Logistic analysis, and a radiomics prediction model is constructed through a multi-factor logistic regression method. According to the method, the enhanced CT image is utilized, the RAS gene state of the colorectal cancer liver metastasis patient can be economically, noninvasively and rapidly predicted, genetic typing is assisted, clinical doctors can be helped to make accurate individualized treatment decisions, and the method has great clinical significance.

The invention relates to the technical field of echocardiogram detection and analysis, is used for solving the problem that an existing echocardiogram treatment decision-making system cannot perform disease development trend matching for a patient according to the treatment rehabilitation progress of the disease of the patient, and particularly relates to a treatment decision-making system based on an echocardiogram detection report, which comprises a treatment platform, the treatment platform is in communication connection with a report analysis module, a trend analysis module, a treatment recommendation module and a comprehensive analysis module, and the report analysis module is used for analyzing diseases of a patient through echocardiogram detection data to obtain a patient coefficient of the patient; the trend analysis module is used for performing illness state trend analysis on the patient and performing screening to obtain a matching object, and the trend analysis model performs matching analysis on the matching object to obtain a trend object; the diagnosis result of the patient is analyzed and graded through the report analysis module in combination with the cardiogram detection report, and a response scheme is made in time through the treatment curve of a trend object to prevent disease deterioration.

The invention discloses a diagnosis and treatment decision making system based on artificial intelligence. The system comprises an interaction device and an upper computer; the interaction device acquires clinical patient information of a patient and sends the clinical patient information to the upper computer, and the clinical patient information comprises clinical diagnosis and treatment information and auxiliary examination information; the upper computer is used for carrying out standardized treatment on the clinical diagnosis and treatment information and the auxiliary examination information, and obtaining the standardized information in a preset format; the upper computer searches for a preset decision tree according to the standardized information, and obtains target diagnosis decision making information corresponding to the standardized information. The clinical patient information of the patient is recognized through the preset decision tree so that the target diagnosis decision making information can be output quickly and accurately; the clinical patient information is subjected to standardized processing in advance, so that the searching efficiency of the preset decision tree is further improved, and doctors can be assisted in carrying out rapid and standardized diagnosis and treatment.