Latest AI and machine learning research in cultural competence for healthcare professionals.
Burn injuries and chronic wounds impose a substantial and growing global health and economic burden, particularly in low- and middle-income countries and among aging populations with diabetes, vascular disease, and immobility. Conventional wound assessment depends heavily on visual inspection, manual measurements, and clinician experience, leading to variability in burn-depth estimation, wound siz...
GenAI has become a crucial channel for health information, and people are increasingly relying on and uncritically accepting AI-generated health content. This automation bias in the AI era has triggered a global AI-driven infodemic. Therefore, activating users' proactive discernment of misinformation is essential to maintaining cognitive sovereignty and collaborative governance. Based on the Elabo...
BACKGROUND: Pulmonary edema is a life-threatening condition caused by fluid accumulation in the lungs that impairs gas exchange. Machine learning mode...
OBJECTIVE: The application of artificial intelligence/machine learning (AI/ML) to magnetic resonance imaging (MRI) promises to enhance and support cli...
Despite diagnosis accuracy has been much improved by depending more on deep learning for disease classification, it raises serious concerns about pati...
As urban areas host a large portion of the world's population, high-resolution gridded meteorological data within cities is required to answer impactf...
Image forgery (IF) is a critical issue that can lead to the misinterpretation of visual information. Conventional strategies for IF detection are prim...
PURPOSE OF REVIEW: Right ventricular size and function are vital to risk stratification in pulmonary hypertension, valvular disease, and congenital he...
BACKGROUND: Heart failure is not only a prevalent disease with a high mortality rate, but also generates high costs for healthcare systems. By trainin...
Purpose To evaluate the pooled diagnostic accuracy of externally tested AI models for malignancy classification of lung nodules on chest CT. Materials...
BACKGROUND: Radiographic bone age estimation is routinely performed in children to evaluate short stature, early or late puberty, and endocrine disord...
BACKGROUND: Suicide is a critical global public health issue, with millions experiencing suicidal ideation (SI) each year. Global estimates suggest th...
OBJECTIVE: There is a critical scarcity of domain-specific, clinically grounded Natural Language Processing (NLP) resources for African languages. In ...
As artificial intelligence (AI) technology expands into decision-making domains such as recruitment, concerns over fairness, transparency, and public ...
Accurate and scalable soybean crop health monitoring remains a major challenge in precision agriculture due to environment variability, inconsistent l...
OBJECTIVES: To evaluate the accuracy of an artificial intelligence (AI) model developed by DentalMonitoring for assessing occlusal parameters from pat...
BACKGROUND: Accurate surgical case duration estimation (CDE) is critical for operating room efficiency, staffing, resource allocation, and patient saf...
Artificial intelligence is emerging as a transformative and rapidly developing technology, with growing implications for the healthcare sector, includ...
Previously, we reported a dual combination based on 4-hydroxycoumarin and dodecanedioic acid that could synergistically bind to human serum albumin (H...
Recent advancements in blood-brain barrier permeability (BBBP) prediction of drug compounds have highlighted the growing role of machine learning, par...