A method for dynamically managing a goal in a care plan of a patient is disclosed. The method includes receiving a selection of a type of the care plan for the patient, responsive to the selection of the type of the care plan, receiving a selection of a goal having a goal type to include in the care plan, generating the care plan including the goal having the goal type, and causing the care plan including the goal to be presented on a computing device of a medical personnel.

A method for dynamically managing a goal in a care plan of a patient is disclosed. The method includes receiving a selection of a type of the care plan for the patient, responsive to the selection of the type of the care plan, receiving a selection of a goal having a goal type to include in the care plan, generating the care plan including the goal having the goal type, and causing the care plan including the goal to be presented on a computing device of a medical personnel.

A method comprising receiving, for each of a plurality of subjects having a specified type of disease and receiving a specified therapy for treating the disease, a first biological signature obtained pre-treatment and a second biological signature obtained on-treatment; calculating, for each of the plurality of subjects, a set of values representing a ratio between the first and second biological signatures associated with the respective subject; at a training stage, training a machine learning model on a training set comprising: (i) the calculated sets of values, and (ii) labels associated with an outcome of the specified therapy in each of the subjects; to generate a classifier suitable for predicting a response in a target patient to said specified therapy.

A method comprising receiving, for each of a plurality of subjects having a specified type of disease and receiving a specified therapy for treating the disease, a first biological signature obtained pre-treatment and a second biological signature obtained on-treatment; calculating, for each of the plurality of subjects, a set of values representing a ratio between the first and second biological signatures associated with the respective subject; at a training stage, training a machine learning model on a training set comprising: (i) the calculated sets of values, and (ii) labels associated with an outcome of the specified therapy in each of the subjects; to generate a classifier suitable for predicting a response in a target patient to said specified therapy.

A method for autonomously generating a care plan personalized for a patient is disclosed. The method includes receiving a selection of a type of the care plan to implement for the patient, generating the care plan based on the type selected, wherein the care plan includes an action instruction based on a patient graph of the patient and a knowledge graph including ontological medical data, receiving patient data that indicates health related information associated with the patient, modifying the care plan to generate a modified care plan in real-time or near real-time based on the patient data, and causing the modified care plan to be presented on a computing device of a medical personnel.

Various methods and systems are provided for display of recommended treatment based on a patient's medical history and standardized guidelines. In one example, a computing system includes a display screen configured to display a patient medical path listing one or more of treatment guidelines and patient medical history, and to display abbreviated representations of at least one of the treatment guidelines and the patient medical history that can be reached directly from the displayed patient medical path. The abbreviated representations each display a limited list of data that is selectable to launch the treatment guidelines and/or the patient medical history and enable the selected data to be seen.

Various methods and systems are provided for display of recommended treatment based on a patient's medical history and standardized guidelines. In one example, a computing system includes a display screen configured to display a patient medical path listing one or more of treatment guidelines and patient medical history, and to display abbreviated representations of at least one of the treatment guidelines and the patient medical history that can be reached directly from the displayed patient medical path. The abbreviated representations each display a limited list of data that is selectable to launch the treatment guidelines and/or the patient medical history and enable the selected data to be seen.

A system and method for assessing disease progression receives digital health data about patients over a network from a plurality of diagnostic instruments, IoT devices, analytical software, systems, and electronic health records. Electronic Patient Reported Outcome (PRO) questionnaires are created by clinicians and periodically administered to patients on a remote computing device. The PROs and other digital health data are processed, analyzed, and scored in real time. Digital reports including the scores and other health metrics are instantaneously generated providing valuable hidden insights into disease progression and treatment efficacies in real-time. A clinical advisor generates an interactive dashboard comprising comprehensive information about patients and enables doctors to validate their clinical decisions and discover new treatment protocol idea. Reports useful for other industries may also be generated, such as for pharmaceutical companies, insurance companies, medical researchers, and regulatory agencies.

A system and method for assessing disease progression receives digital health data about patients over a network from a plurality of diagnostic instruments, IoT devices, analytical software, systems, and electronic health records. Electronic Patient Reported Outcome (PRO) questionnaires are created by clinicians and periodically administered to patients on a remote computing device. The PROs and other digital health data are processed, analyzed, and scored in real time. Digital reports including the scores and other health metrics are instantaneously generated providing valuable hidden insights into disease progression and treatment efficacies in real-time. A clinical advisor generates an interactive dashboard comprising comprehensive information about patients and enables doctors to validate their clinical decisions and discover new treatment protocol idea. Reports useful for other industries may also be generated, such as for pharmaceutical companies, insurance companies, medical researchers, and regulatory agencies.

A platform providing methods and systems for prevention and/or treatment of a health condition, where a method can include: simultaneously reducing severity symptoms of the health condition and comorbid conditions upon: receiving a set of samples from one or more subjects; receiving a biometric dataset from one or more subjects; receiving a lifestyle dataset from one or more subjects; returning a genomic single nucleotide polymorphism (SNP) profile and a baseline microbiome state upon processing the set of samples, the biometric dataset, and the lifestyle dataset with a set of transformation operations; generating personalized intervention plans for the one or more subjects upon processing the genomic SNP profile and the baseline microbiome state with a multi-omic model; and executing the personalized intervention plans for the one or more subjects.