In some examples, a computer system may receive medical records for a plurality of patients. The system may generate a plurality of data representations based on the medical records for the individual patients, each data representation representing at least a therapy performed and a quantified disability status of the individual patient. The system may select a subset of the data representations for which an improvement in the quantified disability status exceeds a threshold. Further, the system may receive patient information for a first patient and may generate a first data representation from the patient information. The system may compare the first data representation with the data representations in the subset to determine at least one therapy predicted to provide an improvement in the current quantified disability of the first patient. The system may send information related to the at least one therapy to a computing device.

Methods are provided for the prognosis, diagnosis and treatment of various pathological states, including cancer, chemotherapy resistance and dementia associated with Alzheimer's disease. The methods provided herein are based on the discovery that various proteins with a high level of sialylation are shown herein to be associated with disease states, such as, cancer, chemotherapy resistance and dementia associated with Alzheimer's disease. Such methods provide a lysosomal exocytosis activity profile comprising one or more values representing lysosomal exocytosis activity. Also provided herein, is the discovery that low lysosomal sialidase activity is associated with various pathological states. Thus, the methods also provide a lysosomal sialidase activity profile, comprising one or more values representing lysosomal sialidase activity. A lysosomal sialidase activity profile is one example of a lysosomal exocytosis activity profile.

Methods are provided for the prognosis, diagnosis and treatment of various pathological states, including cancer, chemotherapy resistance and dementia associated with Alzheimer's disease. The methods provided herein are based on the discovery that various proteins with a high level of sialylation are shown herein to be associated with disease states, such as, cancer, chemotherapy resistance and dementia associated with Alzheimer's disease. Such methods provide a lysosomal exocytosis activity profile comprising one or more values representing lysosomal exocytosis activity. Also provided herein, is the discovery that low lysosomal sialidase activity is associated with various pathological states. Thus, the methods also provide a lysosomal sialidase activity profile, comprising one or more values representing lysosomal sialidase activity. A lysosomal sialidase activity profile is one example of a lysosomal exocytosis activity profile.

Systems and techniques can determine candidate treatments for individuals diagnosed with a biological condition. The biological condition can include a neurodevelopmental condition and the candidate treatments can include one or more therapeutics. In one or more implementations, data, such as genetic data, morphological data, and levels of analytes, can be used to group individuals that have been diagnosed with a neurodevelopmental condition based on behavioral classifications. Biological pathways that are disrupted by the neurodevelopmental condition can also be identified along with one or more genes of the biological pathways whose expression is impacted by the neurodevelopmental condition. Therapeutics can be identified to treat individuals diagnosed with the neurodevelopmental condition based on genetic profiles of the therapeutics and genetic profiles of the individuals in which the neurodevelopmental condition is present.

Systems and techniques can determine candidate treatments for individuals diagnosed with a biological condition. The biological condition can include a neurodevelopmental condition and the candidate treatments can include one or more therapeutics. In one or more implementations, data, such as genetic data, morphological data, and levels of analytes, can be used to group individuals that have been diagnosed with a neurodevelopmental condition based on behavioral classifications. Biological pathways that are disrupted by the neurodevelopmental condition can also be identified along with one or more genes of the biological pathways whose expression is impacted by the neurodevelopmental condition. Therapeutics can be identified to treat individuals diagnosed with the neurodevelopmental condition based on genetic profiles of the therapeutics and genetic profiles of the individuals in which the neurodevelopmental condition is present.

A system for providing clinical decision support to a user is presented. The system comprises a Point-of-Care (POC) testing device comprising an integrated clinical decision support module. The POC testing device and the clinical decision support module are connected via a testing module-clinical decision support module interface. The system comprises a testing module between the user and the POC testing device. The testing module requests tests from the user to the POC testing device and sends completed test results from the POC testing device to the user and to the clinical decision support module via the internal interface. The system comprises outside data sources to provide external data via a communication connection to the clinical decision support module of the POC testing device. The clinical decision support module uses the external data and the completed test results to determine and provide clinical decision support information specifically tailored to the user.

A system for providing clinical decision support to a user is presented. The system comprises a Point-of-Care (POC) testing device comprising an integrated clinical decision support module. The POC testing device and the clinical decision support module are connected via a testing module-clinical decision support module interface. The system comprises a testing module between the user and the POC testing device. The testing module requests tests from the user to the POC testing device and sends completed test results from the POC testing device to the user and to the clinical decision support module via the internal interface. The system comprises outside data sources to provide external data via a communication connection to the clinical decision support module of the POC testing device. The clinical decision support module uses the external data and the completed test results to determine and provide clinical decision support information specifically tailored to the user.

The present invention relates to: a method for providing information for choosing a breast cancer treatment method by using a breast cancer ultrasonic image and gene information; a system for choosing a breast cancer treatment method by using a breast cancer ultrasonic image; and a method for providing information required for predicting the prognosis of a breast cancer patient.

A health management system, including: a health assessment module configured to obtain human health-related health parameter information of a user, and generate a health condition assessment result on the basis of the health parameter information; a health intervention module configured to generate a health management plan on the basis of the health condition assessment result; a human body model generation module configured to generate a human body model that can be displayed on a display interface; and a human body information display model configured to display, on the basis of a received display instruction, the human body model on the display interface based on human body tissue layers, human body systems, or human body parts. In addition, also provided are a human body information display method and a human body model generation method applicable to the health management system.

An object of the invention is to improve prediction accuracy of data including a low-frequency medical treatment practice. Provided is an information processing system including: a transition information generation unit configured to generate transition information of an event for each patient of a plurality of patients based on medical information of the plurality of patients; a medical treatment process classification unit configured to classify a process of a medical treatment practice included in the event into a plurality of groups based on a threshold value related to a frequency of the medical treatment practice according to the generated transition information; a medical treatment process granularity adjustment unit configured to aggregate items of the process of the medical treatment practice in at least a part of the groups; a prediction model generation unit configured to generate a prediction model for each of the groups; and an output unit configured to classify input data of medical information of a new patient into any one of the groups, and to output an occurrence of an event of the new patient using the prediction model.