Abstract Background: Natural Language Processing (NLP) is widely used to extract clinical
insights from Electronic Health Records (EHRs). However, the lack of annotated data …

Objective Natural language processing (NLP) combined with machine learning (ML)
techniques are increasingly used to process unstructured/free-text patient-reported outcome …

Depression is a global mental health problem, the worst case of which can lead to suicide.
An automatic depression detection system provides great help in facilitating depression self …

Depression is a common illness worldwide with doubtless severe implications. Due to the
absence of early identification and treatment for depression, millions of individuals …

Depressive symptoms identification on social media aims to identify posts from social media
expressing symptoms of depression. This can be beneficial for developing mental health …

AimsSeveral studies suggested that depression might worsen the clinical outcome of
diabetes mellitus; however, such association was confounded by duration of illness and …

Generally, seafarers face a higher risk of illnesses and accidents than land workers. In most
cases, there are no medical professionals on board seagoing vessels, which makes disease …

Purpose To compile validation findings of diagnosis codes and related algorithms for health
outcomes of interest from National Health Insurance (NHI) or electronic medical records in …

Depression is now a prevalent mental illness and multimodal data-based depression
detection is an essential topic of research. Internet of Medical Things devices can provide …

Autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) are
commonly comorbid with allergic and autoimmune diseases in children. The aim of the …