Latest AI and machine learning research in prevention of medical errors for healthcare professionals.
Leveraging machine learning on electronic health records offers a promising method for early identification of individuals at risk for dementia and neurodegenerative diseases. Current risk algorithms heavily rely on age, highlighting the need for alternative models with strong predictive power, especially at age 65, a crucial time for early screening and prevention. This prospective study analyzed...
Pneumonia, primarily caused by Streptococcus pneumoniae, and tuberculosis (TB), caused by Mycobacterium tuberculosis, continue to present significant global health challenges. Pneumonia is responsible for 14% of deaths among children under five, resulting in 740,180 fatalities annually [1]. Similarly, TB caused 1.25 million deaths in 2022, including 161,000 among individuals with HIV [2]. Misdiagn...
This pragmatic randomized controlled trial aimed to assess the effect of a passive display of artificial intelligence (AI)-based predictive analytics ...
Influenza causes about 650,000 deaths worldwide each year, and the high mortality rate of severe cases is closely related to subjective bias in clinic...
Vaccination against infectious diseases prevents diseases, saves lives, and reduces healthcare costs. However, trust, accessibility, and public percep...
Objective Structured Clinical Examinations (OSCEs) are critical tools in medical education, designed to evaluate clinical competence by engaging stude...
Aligning the Theory of Mind (ToM) capabilities of Large Language Models (LLMs) with human cognitive processes enables them to imitate physician behavi...
The growing use of large language models for health communication raises important questions about patient preferences, trust, and satisfaction with A...
In the field of medical crowdfunding prediction, traditional statistical methods have long been the standard. Machine learning algorithms are popular ...
Radiology reports are primarily designed for healthcare professionals, often containing complex medical terminology hindering patients from understand...
Artificial intelligence (AI) is transforming precision medicine, particularly in cardiovascular disease prevention and management. This bibliometric a...
Metabolic biomarkers can potentially be used for early diagnosis, prognostic risk stratification and/or early treatment and prevention of individuals ...
Dental caries is the most common oral disease worldwide, affecting up to 90% of children globally. It can lead to pain, infection, and impaired qualit...
Multimorbidity, the co-occurrence of multiple chronic conditions in an individual, has become a global health challenge affecting populations in high-...
Assessing the risk of future atherosclerotic cardiovascular disease (ASCVD) is crucial in clinical practice, yet it continues to pose significant chal...
To characterize real-world LLM use by healthcare professionals and identify gaps between actual usage and research focus. We analyzed chat interaction...
Large language models (LLMs) offer promise for enhancing clinical care by automating documentation, supporting decision-making, and improving communic...
Artificial intelligence (AI) is rapidly transforming healthcare, but its benefits are not reaching all patients equally. Children remain overlooked wi...
Non-communicable diseases (NCDs) account for ∼71% of all deaths globally, including 15 million premature deaths each year (deaths between 30-69 years ...
The interaction between physical activity and sleep with cardiovascular disease remains poorly understood, despite both being key risk factors. This s...