Abstract: Novel tools and techniques are provided for implementing medical or medical-related diagnosis and treatment, and, more particularly, for implementing risk assessment for suicide and treatment based on interaction with virtual clinician, food intake tracking, and/or satiety determination. In various embodiments, a computing system might generate a virtual clinician capable of simulating facial expressions and body expressions, and might cause, using a display device and/or an audio output device, the generated virtual clinician to interact with a patient. The computing system might analyze the interactions between the virtual clinician and the patient (and in some cases, food intake data) to determine likelihood of risk of suicide by the patient, and, based on a determination that a likelihood of risk of suicide by the patient exceeds a first predetermined threshold value, might send an alert message to one or more healthcare professionals regarding the likelihood of risk of suicide by the patient.

Abstract: Novel tools and techniques are provided for implementing eating disorder diagnosis based on analysis of patient responses to a set of questions having closed-ended answer options. In various embodiments, a computing system might autonomously determine a diagnosis of whether the first patient has an eating disorder, based on logistic regression analysis of a first set of patient responses to the set of questions. If so, the computing system might autonomously identify a first set of weighted values and a second set of weighted values each corresponding to each of the received first set of patient responses from the first patient; might autonomously calculate a first probability of diagnosis of a first eating disorder and a second probability of diagnosis of a second eating disorder; might autonomously identify which eating disorder the first patient is likely to have; and might display the identified eating disorder.