Latest AI and machine learning research in patient safety / risk management for healthcare professionals.
Electroconvulsive therapy (ECT) is an effective treatment of severe manifestations of mental illness. Since delay in initiation of ECT can have detrimental effects, prediction of the need for ECT could improve outcomes via more timely treatment initiation. This study aimed to predict the need for ECT following admission to a psychiatric hospital. This cohort study was based on electronic health re...
Delirium is a serious and common condition in hospitalized patients, associated with increased morbidity, mortality, and healthcare costs. Early detection and management of delirium is crucial for improving patient outcomes. Clinical notes contain valuable information about a patient’s mental status that may not be captured by structured data alone. Natural language processing (NLP) techniques hav...
Diabetes represents an emerging global health crisis, with lower-middle-income countries experiencing a fast growth in prevalence. Diabetes care in th...
This paper delivers a rigorous mixed-methods synthesis of conversational AI applications in mental health therapy, analyzing 47 randomized controlled ...
Manual assignment of International Classification of Diseases (ICD) codes is error-prone. Transformer-based large language models (LLMs) have been pro...
Generative AI is a powerful resource for health professions education (HPE) researchers publishing their work. However, questions remain about its use...
Artificial intelligence (AI) is increasingly embedded in clinical trials, yet poor reproducibility remains a critical barrier to trustworthy and trans...
Artificial intelligence (AI) has potentially shown promise in interpreting ultrasound imaging through flexible pattern recognition and algorithmic lea...
The lack of understanding of how individuals communicate suicidal stress hinders global suicide intervention plans and practices. This study identifie...
Depression and anxiety are widespread mental health disorders, yet their diagnosis remains challenging. Digital phenotyping with wearable devices prov...
Documentation demands in psychiatric practice diminish time for direct patient care and are associated with clinician burnout. Ambient artificial inte...
This study investigated whether chronotype (biobehavioral preference for sleep and wake timing) across early adolescence impacts mental health symptom...
To analyze the frequency of self-disclosed use of AI in research manuscripts submitted to 49 biomedical journals and to identify types of AI tools use...
Economic evaluations of artificial intelligence (AI) in healthcare are expanding rapidly, yet underlying costing methods remains heterogenous, and fre...
Fragile X Syndrome (FXS) is the most common inherited cause of intellectual disability and syndromic autism, but diagnosis remains challenging due to ...
Urogenital schistosomiasis caused by Schistosoma haematobium remains endemic in sub-Saharan Africa. Diagnosis traditionally relies on urine microscopy...
We evaluated whether oxytocin improves social-emotional reciprocity in children and adolescents with autism spectrum disorder (ASD) by conducting a se...
Psychotropic medications are commonly used for children with neurodevelopmental conditions, but their effectiveness varies, making treatment selection...
Gender-neutral patient education materials often overlook critical sex-based differences in cardiovascular disease (CVD). Large Language Models (LLMs)...
Artificial intelligence (AI) models with medical images as input data are increasingly proposed to support clinical decisions in lung cancer screening...