Background: With the increasing availability of data, computing resources, and easier-to-use
software libraries, machine learning (ML) is increasingly used in disease detection and …

Background Suicide is a global public health issue causing around 700,000 deaths
worldwide each year. Therefore, identifying suicidal thoughts and behaviors in patients can …

Parkinson's disease (PD) is a neurodegenerative disease that affects motor abilities with
increasing severity as the disease progresses. Traditional methods for diagnosing PD …

A personalized approach is strongly advocated for treatment selection in Multiple Sclerosis
patients due to the high number of available drugs. Machine learning methods proved to be …

Background and methods In this narrative review, we introduce key artificial intelligence (AI)
and machine learning (ML) concepts, aimed at headache clinicians and researchers …

Infective endocarditis (IE) is a severe infection of the inner lining of the heart, known as the
endocardium. It is characterized by a range of symptoms and has a complicated pattern of …

This paper focuses on ozone prediction in the atmosphere using a machine learning
approach. We utilize air pollutant and meteorological variable datasets from the El Paso …

The survival rate for sudden cardiac arrest (SCA) is low, and patients with long-term risks of
SCA are not adequately alerted. Understanding SCA's characteristics will be key to …

Background The frequency of hip and knee arthroplasty surgeries has been rising steadily in
recent decades. This trend is attributed to an aging population, leading to increased …

Objective Pediatric traumatic brain injury (pTBI) is a heterogeneous condition requiring the
development of clinical decision rules (CDRs) for the optimal management of these patients …