SYSTEM AND METHOD FOR AUTOMATIC ANALYSIS OF TEXTS IN PSYCHOTHERAPY, COUNSELING, AND OTHER MENTAL HEALTH MANAGEMENT ACTIVITIES
A method of analyzing a patient's mental state, by automatically processing, integrating, and analyzing text-based and audio-based sources from the patient and clinical staff, and generating real-time outcomes and predictions. A system for processing, analyzing, and managing a patient's input including a data pool, model HUB, search service, topic modeling service, mental health related prediction service, and analytics all in electronic communication. A method of analyzing a patient, by processing, analyzing, and managing a patient's and clinical staff's text and audio input, and informing and augmenting diagnostic and prognostic processes, identifying improvement and deterioration of a patient's mental state, and identifying adverse events in psychotherapy, counseling, and other mental health management activities. A system for processing, analyzing, and managing clinical and diagnostic texts, and audio transcripts.
1 .- 38 . (canceled)
39 . A method of reducing bias in analyzing a patient's mental state so that treatment of the patient can be improved, wherein the patient is undergoing treatment for a mental disorder, the method comprising:
training a machine learning model with a dataset, the dataset comprising data from a population of patients who have previously undergone treatment for a mental disorder;
acquiring patient information during a treatment session wherein the patient data comprises at least one text-based source of patient information;
analyzing the patient data using the trained machine learning model;
outputting a score quantifying the mental state of the patient; and
determining whether the treatment should be modified based on the score.
40 . The method of claim 39 , further comprising presenting the score via a visual interface.
41 . The method of claim 39 , wherein the at least one text-based source of information includes the patient's diary, journal, worry script, transcript of patient-clinical staff discussions, written/transcribed answers to a structured set of questions, clinical staff's clinical notes from patient's treatment and therapy, initial assessment notes, progress notes, non-clinical notes from patient's treatment and therapy, drug administration notes, clinical and research staff notes, treatment plans, prescriptions, or a combination thereof.
42 . The method of claim 39 , wherein the acquired patient data further includes at least one audio-based source.
43 . The method of claim 39 , wherein the acquired patient information and score, become part of the dataset used to train the machine learning model.