Latest AI and machine learning research in psychiatry for healthcare professionals.
Machine learning models are vital for forecasting and optimizing healthcare parameters, especially in the context of rising mental health issues in India and globally. With increasing demand for mental health services, effective resource management, like bed occupancy forecasting, is crucial to ensure proper patient care and reduce the burden on healthcare facilities. This study applies six machin...
This study aimed to compare and evaluate the prediction accuracy and risk of bias (ROB) of post-traumatic stress disorder (PTSD) predictive models. We conducted a systematic review and random-effect meta-analysis summarizing predictive model development and validation studies using machine learning in diverse samples to predict PTSD. Model performances were pooled using the area under the curve (A...
The long-standing practice of using manualized inventories and observational assessments to diagnose and track motor function in autism overlooks crit...
BACKGROUND: Patient engagement is a critical but challenging public health priority in behavioral health care. During telehealth sessions, health care...
BACKGROUND: Depression significantly impacts an individual's thoughts, emotions, behaviors, and moods; this prevalent mental health condition affects ...
Elderly patients undergoing maintenance hemodialysis (MHD) face a heightened risk of cognitive frailty (CF), which significantly compromises quality o...
Generative artificial intelligence (GenAI) shows potential for personalized care, psychoeducation, and even crisis prediction in mental health, yet re...
BACKGROUND: Postpartum depression (PPD) is a prevalent mental health issue with significant impacts on mothers and families. Exploring reliable predic...
INTRODUCTION: Bipolar disorder (BD) and major depressive disorder (MDD) have overlapping clinical presentations which may make it difficult for clinic...
Recent advances highlight the limitations of classification strategies in machine learning that rely on a single data source for understanding, diagno...
The Post COVID-19 condition (PCC) is a complex disease affecting health and everyday functioning. This is well reflected by a patient's inability to w...
BACKGROUND: The use of natural language processing (NLP) in mental health research is increasing, with a wide range of applications and datasets being...
BACKGROUND: We previously reported that machine learning could be used to predict conversion to psychosis in individuals at clinical high risk (CHR) f...
BACKGROUND: Major depressive disorder (MDD) comes along with an increased risk of recurrence and poor course of illness. Machine learning has recently...
BACKGROUND: With increasing adoption of remote clinical trials in digital mental health, identifying cost-effective and time-efficient recruitment met...
BACKGROUND: Artificial intelligence broadly refers to computer systems that simulate intelligent behaviour with minimal human intervention. Emphasizin...
Multifunctional hardware technologies for neuromorphic computing are essential for replicating the complexity of biological neural systems, thereby im...
BACKGROUND: Anhedonia and suicidal ideation are symptoms of major depressive disorder (MDD) that are not regularly captured in structured scales but m...
INTRODUCTION: Evaluating neurocognitive functions and diagnosing psychiatric disorders in older adults is challenging due to the complexity of symptom...
Major depressive disorder (MDD) is associated with substantial morbidity and mortality, yet its diagnosis and treatment rates remain low due to its di...