Psychiatric disorders are influenced by genetic and environmental factors. However, their study is hindered by limitations on precisely characterizing human behavior. New technologies such as wearable sensors show promise in surmounting these limitat...
Individuals with neuropsychiatric disorders experience both physical and mental difficulties, hindering their ability to live healthy lives and participate in daily activities. It is challenging to diagnose these disorders due to a lack of reliable d...
BACKGROUND: Machine Learning (ML) models have been used to predict common mental disorders (CMDs) and may provide insights into the key modifiable factors that can identify and predict CMD risk and be targeted through interventions. This systematic r...
IEEE journal of biomedical and health informatics
Dec 5, 2024
The global prevalence of mental health disorders is increasing, leading to a significant economic burden estimated in trillions of dollars. In automated mental health diagnosis, the scarcity and imbalance of clinical data pose considerable challenges...
OBJECTIVE: This paper investigates how state-of-the-art generative artificial intelligence (AI) image models represent common psychiatric diagnoses. We offer key lessons derived from these representations to inform clinicians, researchers, generative...
BMC medical informatics and decision making
Nov 22, 2024
BACKGROUND: There are numerous papers focusing on diagnosing mental health disorders using unimodal and multimodal approaches. However, our literature review shows that the majority of these studies either use unimodal approaches to diagnose a variet...
BACKGROUND: Mental health disorders are currently the main contributor to poor quality of life and years lived with disability. Symptoms common to many mental health disorders lead to impairments or changes in the use of language, which are observabl...
BACKGROUND: Assessing the complex and multifaceted symptoms of patients with acute psychiatric disorders proves to be significantly challenging for clinicians. Moreover, the staff in acute psychiatric wards face high work intensity and risk of burnou...
PURPOSE OF REVIEW: This review aims to evaluate the current psychiatric applications and limitations of machine learning (ML), defined as techniques used to train algorithms to improve performance at a task based on data. The review emphasizes the cl...
OBJECTIVES: Tools based on generative artificial intelligence (AI) such as ChatGPT have the potential to transform modern society, including the field of medicine. Due to the prominent role of language in psychiatry, e.g., for diagnostic assessment a...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.