Latest AI and machine learning research in primary care for healthcare professionals.
Background: Heart failure (HF) is a major contributor to inpatient hospital utilization, with persistently high 30-day readmission rates. Existing prediction tools are frequently restricted to primary-diagnosis HF admissions, potentially excluding clinically relevant HF-related hospitalizations. Objectives: To develop and validate risk prediction models using machine learning (ML)-based risk predi...
Treatment of advanced head and neck squamous cell carcinoma (HNSCC) often involves radiotherapy combined with chemotherapy, targeted therapy, or immunotherapy. However, due to its anatomical and molecular heterogeneity, identifying the most effective treatment for each patient remains a major clinical challenge. To address this need, we developed a high-throughput organoid-based drug screening pla...
Metabolomic aging clocks estimate biological age by modeling metabolite concentrations, thereby capturing aging signals from healthspan and adverse ou...
Transcription factors (TFs) regulate gene expression by binding to specific DNA sequences. Widely used models of TF-DNA binding, such as position weig...
Purpose: In clinical practice, accurate prediction of disease risk must be accompanied by transparent, human-understandable explanations to support di...
Background: Obesity significantly increases the risk of prognosis and clinical outcomes in pancreatic ductal adenocarcinoma (PDAC). While research on ...
AI-assisted clinical care may compound, rather than correct, existing health inequities. We applied Omar and colleagues' validated four-domain emergen...
Rheumatic heart disease (RHD) remains a major public health concern across low- and middle-income countries in the Global South. Early detection throu...
Disease screening is critical for early detection and timely intervention in clinical practice. However, most current screening models for medical ima...
Knee osteoarthritis (KOA) is among the musculoskeletal disorders that considerably restrict joint mobility, cause severe chronic pain and impact negat...
In routine care, individuals identified a priori as high-risk are usually tested for conditions more frequently. Protected attributes, such as sex or ...
Medication adherence among patients with diabetes remains suboptimal in low and middle income countries, including Nigeria. Emerging digital health in...
Pre-visit planning has the potential to reduce EHR documentation burden while improving workflow efficiency, care quality, and patient-provider engage...
Early detection of Rheumatic Heart Disease (RHD) is essential in reducing its associated mortality and late complications. In resource-limited setting...
Accurate gene annotation is crucial for inference of biological knowledge from genomes. However, non-canonical genes such as orphan or single-exon gen...
Disease is a heterogeneous process that involves multiple organs and cell types. Understanding how genomic variation contributes to disease requires a...
BACKGROUND: Aortic dissection (AD) is a life-threatening emergency with high mortality. Although elevated body mass index (BMI) is associated with bot...
Systematic Reviews (SRs) are the gold standard for evidence synthesis, but the manual title and abstract screening of thousands of references creates ...
The rapid rise of large language models (LLMs) and foundation models has accelerated efforts to build artificial intelligence (AI) agents for mental h...
As Large Language Model (LLM) agents transition from single-session tools to persistent systems managing longitudinal healthcare journeys, their memor...