Latest AI and machine learning research in primary care for healthcare professionals.
This study evaluates the reliability and participants' responses to a contactless artificial intelligence (AI) device powered by Remote Photoplethysmography (rPPG) technology for screening vital signs. The contactless AI-based device was compared with automated devices and the manual method as part of its validation for potential healthcare screening applications in dental clinics. A survey was co...
BACKGROUND: Natural language processing and large language model systems are increasingly used to support mental health documentation, screening, and follow-up planning. In counseling contexts, model outputs may influence diagnostic framing, risk recognition, and clinical record content. Static performance metrics and fluent generated summaries are not sufficient to support safe implementation wit...
INTRODUCTION: Average glandular dose (Dg) is the primary metric for assessing radiation risk in screening mammography. Although Dg analysis is commonl...
Endodontic care has traditionally focused on the management of local disease conditions and long-term function. As the burden of pulpal and periapical...
OBJECTIVE: To predict patient satisfaction 6 months after small-incision lenticule extraction (SMILE) surgery from preoperative clinical data demonstr...
OBJECTIVE: Artificial intelligence (AI) is increasingly utilized for screening within ophthalmology, yet its application in rural communities remains ...
Attention toward Chat Generative Pre-trained Transformer (ChatGPT) has greatly increased, including in the medical field, but concerns about its probl...
Prior evidence suggests that ion channel dysfunction plays a significant role in the pathogenesis of asthma, which provides a theoretical basis for th...
The intensification of worldwide urbanization and industrial growth has led to a rise in the release of toxic substances into the environment. Antibio...
BACKGROUND: Cardiac transthyretin amyloidosis (ATTR-CA) is frequently underdiagnosed and commonly presents as heart failure with preserved ejection fr...
Study DesignScoping review.ObjectivesTo map spine literature on large language models, characterize reported use cases, and identify evidence gaps lim...
Diabetic retinopathy (DR) is a leading cause of preventable blindness worldwide. The rising prevalence of diabetes has strained conventional screening...
BACKGROUND: Artificial intelligence (AI) uses in the field of bariatric and metabolic surgery (BMS) have evolved over the past few years. However, pub...
BACKGROUND: Voice-based deep learning models for Parkinson disease (PD) and dementia screening report areas under the curve (AUCs) of 0.85-0.97, but r...
BACKGROUND: Literature reviews rely on rigorous title and abstract screening by researchers, which is time-consuming. AI-assisted literature screening...
BACKGROUND: Sunitinib resistance remains a major clinical challenge in renal cell carcinoma, and the underlying molecular mechanisms are incompletely ...
BACKGROUND: To examine global research activity in the application of artificial intelligence, large language models, machine learning, and deep learn...
BACKGROUND: Preserving functional independence is critical in older patients with heart failure (HF), yet tools predicting long-term functional trajec...
PURPOSE: To evaluate the diagnostic outcomes of single-view asymmetries (SVAs) recalled from screening mammography and to explore the association betw...
OBJECTIVES: To construct a machine learning-based predictive model for fatty liver in patients with Wilson disease (WD). METHODS: Clinical data retros...