OBJECTIVES: The International Society for Bipolar Disorders Big Data Task Force assembled leading researchers in the field of bipolar disorder (BD), machine learning, and big data with extensive experience to evaluate the rationale of machine learnin...
BACKGROUND: Symptomatology differences of major depressive disorder (MDD) in psychiatric and general hospitals in China leads to possible misdiagnosis. Looking at the symptomatology of first-visit patients with MDD in different mental health services...
IEEE journal of biomedical and health informatics
May 27, 2019
This paper presents a novel method for predicting suicidal ideation from electronic health records (EHR) and ecological momentary assessment (EMA) data using deep sequential models. Both EHR longitudinal data and EMA question forms are defined by asy...
BACKGROUND: Suicide is a great public health challenge. Two hundred million people attempt suicide in China annually. Existing suicide prevention programs require the help-seeking initiative of suicidal individuals, but many of them have a low motiva...
OBJECTIVE: The rapid proliferation of machine learning research using electronic health records to classify healthcare outcomes offers an opportunity to address the pressing public health problem of adolescent suicidal behavior. We describe the devel...
BACKGROUND: Suicide is a national public health crisis and a critical patient safety issue. It is the 10th leading cause of death overall and the second leading cause of death among adolescents and young adults (15-34 years old). Research shows 80% o...
Suicide accounts for nearly 800,000 deaths per year worldwide with rates of both deaths and attempts rising. Family studies have estimated substantial heritability of suicidal behavior; however, collecting the sample sizes necessary for successful ge...
We developed algorithms to identify pregnant women with suicidal behavior using information extracted from clinical notes by natural language processing (NLP) in electronic medical records. Using both codified data and NLP applied to unstructured cli...
BACKGROUND: Machine learning techniques offer promise to improve suicide risk prediction. In the current systematic review, we aimed to review the existing literature on the application of machine learning techniques to predict self-injurious thought...
Research into suicide prevention has been hampered by methodological limitations such as low sample size and recall bias. Recently, Natural Language Processing (NLP) strategies have been used with Electronic Health Records to increase information ext...
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