A system and method are presented in which known genetic attributes associated with a condition are used to seed the determination of additional attributes which are associated with the condition. Based on the learning, the additional attributes (genetic, behavioral, or both) provide for an increased correlation between the combined attributes and the condition. For behavioral attributes, a measure of the impact of the behavioral attribute on the risk of the condition can be transmitted to another device or system.

Systems, methods and computer-readable media are provided for facilitating clinical decision support and managing patient population health by health-related entities including caregivers, health care administrators, insurance providers, and patients. Embodiments of the invention provide decision support services including providing timely contextual patient information including condition risks, risk factors and relevant clinical information that are dynamically updatable; imputing missing patient information; dynamically generating assessments for obtaining additional patient information based on context; data-mining and information discovery services including discovering new knowledge; identifying or evaluating treatments or sequences of patient care actions and behaviors, and providing recommendations based on this; intelligent, adaptive decision support services including identifying critical junctures in patient care processes, such as points in time that warrant close attention by caregivers; near-real time querying across diverse health records data sources, which may use diverse clinical nomenclatures and ontologies; improved natural language processing services; and other decision support services.

A method for in vitro predicting of the outcome of an individual having a multiple myeloma, including the steps of: a) measuring the expression level of at least 5 genes and/or proteins encoded by the 5 genes, the genes being selected in a group including NRP2, REEP1, SV2B, ARRB1, CACNA1G, FBLIM1, FGFR1, IRF6, ITGA9, NOVA2, PPP2R2C, SLC5A1, SORL1, SYT7 and THY1, in a biological sample obtained from the individual; b) calculating a score value from the expression level obtained at step a); c) classifying the individual as having a good prognosis status or a bad prognosis status, by comparing the score value obtained at step b) with a reference score value.

A method for in vitro predicting of the outcome of an individual having a multiple myeloma, including the steps of: a) measuring the expression level of at least 5 genes and/or proteins encoded by the 5 genes, the genes being selected in a group including NRP2, REEP1, SV2B, ARRB1, CACNA1G, FBLIM1, FGFR1, IRF6, ITGA9, NOVA2, PPP2R2C, SLC5A1, SORL1, SYT7 and THY1, in a biological sample obtained from the individual; b) calculating a score value from the expression level obtained at step a); c) classifying the individual as having a good prognosis status or a bad prognosis status, by comparing the score value obtained at step b) with a reference score value.

A computer-implemented method, computer program product and computing system for receiving a single-lead heartbeat waveform for a user; comparing one or more portions of the single-lead heartbeat waveform to one or more ML-generated waveform features to associate a heart health indicator with the single-lead heartbeat waveform; and providing the heart health indicator to a recipient.

A computer-implemented method, computer program product and computing system for receiving a single-lead heartbeat waveform for a user; comparing one or more portions of the single-lead heartbeat waveform to one or more ML-generated waveform features to associate a heart health indicator with the single-lead heartbeat waveform; and providing the heart health indicator to a recipient.

There is provided a system for monitoring transpulmonary pressure of a mechanically ventilated individual, comprising: a feeding tube, at least one esophageal body, a pressure sensor, and a memory having stored thereon code for: computing an estimate of esophageal wall pressure according to pressure in the esophageal body when inflated and contacting the inner wall of the esophagus, computing the transpulmonary pressure of the mechanically ventilated target individual according to the esophageal wall pressure, periodically inflating and deflating the esophageal body for periodic monitoring of the transpulmonary pressure of the mechanically ventilated target patient while the feeding tube is in use, and computing instructions for adjustment of parameter(s) of a mechanical ventilator that automatically ventilates the target individual according to the computed transpulmonary pressure, wherein the instructions for adjustment of parameter(s) of the mechanical ventilator are computed while the feeding tube is in place without removal of the feeding tube.

There is provided a system for monitoring transpulmonary pressure of a mechanically ventilated individual, comprising: a feeding tube, at least one esophageal body, a pressure sensor, and a memory having stored thereon code for: computing an estimate of esophageal wall pressure according to pressure in the esophageal body when inflated and contacting the inner wall of the esophagus, computing the transpulmonary pressure of the mechanically ventilated target individual according to the esophageal wall pressure, periodically inflating and deflating the esophageal body for periodic monitoring of the transpulmonary pressure of the mechanically ventilated target patient while the feeding tube is in use, and computing instructions for adjustment of parameter(s) of a mechanical ventilator that automatically ventilates the target individual according to the computed transpulmonary pressure, wherein the instructions for adjustment of parameter(s) of the mechanical ventilator are computed while the feeding tube is in place without removal of the feeding tube.

A method for image analysis of medical test results, comprising receiving, at a server, information from a mobile device regarding test results from a test performed using a testing device, wherein the testing device includes an alignment target disposed on the testing device and a plurality of immunoassay test strips, receiving at the server an image of the testing device from the mobile device, determining by the server RGB values for a plurality of pixels of the image, normalizing by the server the RGB values into a single value, comparing by the server the single value to a control value stored on the server, and providing by the server a risk indicator, wherein the risk indicator indicates a likelihood of a presence of a medical condition.

A method for image analysis of medical test results, comprising receiving, at a server, information from a mobile device regarding test results from a test performed using a testing device, wherein the testing device includes an alignment target disposed on the testing device and a plurality of immunoassay test strips, receiving at the server an image of the testing device from the mobile device, determining by the server RGB values for a plurality of pixels of the image, normalizing by the server the RGB values into a single value, comparing by the server the single value to a control value stored on the server, and providing by the server a risk indicator, wherein the risk indicator indicates a likelihood of a presence of a medical condition.