Latest AI and machine learning research in health policy for healthcare professionals.
Digital dermatology, which is defined as the use of digital technologies that leverage individual- and population-level skin data to improve the diagnosis, treatment, and prevention of skin diseases, has emerged as a critical frontier for bridging persistent gaps in dermatologic care. This transformation holds particular promise for addressing long-standing inequities linked to geography, income, ...
BACKGROUND: Mental health disorders are a growing public health concern among university students globally and in India, exacerbated by stigma and limited access to care. Mobile health (mHealth) apps offer a potential solution, but user engagement and cultural relevance remain key challenges. This pilot study evaluated Here for You, a mental health screening app co-designed with Indian university ...
BACKGROUND: Machine learning models are increasingly used to predict patients at risk of high health care usage for targeted interventions. OBJECTIVE:...
Novel advances in healthcare-related Internet of Things (IoT) systems have recently had significant impacts on clinical decision-support systems (CDSS...
INTRODUCTION: Advancements in biomedical research depend on the quality and availability of biological samples. Despite their sophisticated storage ca...
The algal-bacterial symbiotic communities within the submerged macrophyte phyllosphere exhibit significant potential for lake restoration. However, th...
A key challenge in medical decision making is learning treatment policies for patients with limited observational data. This challenge is particularly...
BACKGROUND: Despite the growing use of digital platforms for sexual health education, many tools fail to meet the needs of LGBTQ+ (lesbian, gay, bisex...
BACKGROUND: Diabetes is a chronic disease with a high global prevalence, increasing from 200 million people in 1990 to 830 million in 2022, with a hig...
Rapid and effective decision-making is critical in public health emergencies, where resource allocation must balance multiple objectives under uncerta...
BACKGROUND: Technological advancements and legislation have led to the widespread use of electronic health records (EHRs) in the 21st century. Along w...
BACKGROUND: Artificial intelligence (AI) health care chatbots are gaining widespread adoption worldwide. It is imperative to understand the service qu...
The deployment of artificial intelligence (AI) translation tools in healthcare is accelerating rapidly, yet regulatory frameworks lag dangerously behi...
Agentic artificial intelligence (AI) systems, designed to autonomously reason, plan, and invoke tools, have shown promise in healthcare, yet systemati...
BACKGROUND: Automated approaches to cognitive impairment screening may soon achieve sufficient levels of accuracy for clinical implementation but they...
Artificial intelligence (AI) is increasingly influencing medical education by enabling adaptive learning, AI-assisted assessment, and scalable instruc...
Access control and data privacy are two of the main necessities in managing electronic health records (EHRs) across distributed domain. There are priv...
BACKGROUND AND OBJECTIVES: Access to specialty surgical care is growing in many low-income countries, but it remains unclear how hospital workforces c...
While artificial intelligence (AI) models have been developed to support coronary revascularization decision-making, health economic evaluation of suc...
AIMS: Ultrasound is a highly sensitive method to detect developmental dysplasia of the hip (DDH). However, the cost of expert sonographers performing ...