Primary Care

Artificial Intelligence Driven Virtual Screening and Molecular Docking Approaches Identified LIFR, BTG2, EPHX2, and PAK3 as Targets and BI-2536, AP-24534, and AZ-628 as Repurposed Drugs for PDAC.

Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive and lethal tumors worldwide, with limited effective treatments. Globally, the incidence of pancreatic cancer is expected to rise to 18.6 per 100,000 by 2050, with an average annual growth rate of 1.1%, implying that PDAC would represent a considerable public health burden. Identifying prognostic markers is critical for making th...

Development of a machine learning-based model for prediction of diabetes risk in patients with metabolic dysfunction-associated steatotic liver disease (MASLD).

BACKGROUND: Metabolic dysfunction-associated steatotic liver disease (MASLD) is a leading chronic liver disorder closely linked to diabetes mellitus (DM) and its cardiovascular and renal complications. Early identification of diabetes risk in this population is essential for timely intervention. OBJECTIVE: To develop machine learning (ML) models to predict diabetes risk in individuals with MASLD a...

HpMiX: A Disease ceRNA biomarker prediction framework driven by graph topology-constrained Mixup and hypergraph residual enhancement.

The competing endogenous RNA (ceRNA) regulatory network (CENA) plays a critical role in elucidating the molecular mechanisms of diseases. However, exi...

Correlation between oral disease and neurodegenerative disorders: Role of biological proteins for the modulation of oral-brain axis and gut-brain axis.

Biological proteins play a crucial role at the intersection of oral health and neuroscience, offering promising opportunities for improved diagnosis, ...

Distinguishing a drug use disorder from drug use in a high-risk sample of youth: A random forest classification and explanatory analysis.

Although many adolescents and young adults experiment with drugs, a subset may develop a drug use disorder (DUD). Few studies have used machine learni...

Mechanistic insights into heart failure progression and therapeutic target discovery through plasma microRNA profiling: Findings from HOMAGE.

BACKGROUND: Identifying early pathobiological mechanisms associated with the onset and progression of heart failure (HF) could guide development of pr...

Augmenting Braden Scores With Predictive Modeling to Reduce Hospital-Acquired Pressure Injuries: A Clinical Pilot Study.

OBJECTIVE: To evaluate the efficacy of a machine learning predictive model integrating the Braden Scale with patient demographic and care-related feat...

An Artificial Intelligence-Driven Platform for Practice Question Generation.

PROBLEM: High-stakes licensing exams such as the USMLE play a critical role in medical education, influencing both trainee progression and patient out...

CCTA as a Screening Tool (Invited Commentary).

Coronary computed tomography angiography (CCTA) has evolved into a key non-invasive tool for evaluating coronary artery disease, offering high sensiti...

Advanced Technologies for the Diagnosis of Pulmonary Tuberculosis Using Exhaled Breath Samples: A Systematic Scoping Review.

OBJECTIVES: Non-invasive methods based on exhaled breath samples have emerged as promising alternatives for the diagnosis of pulmonary tuberculosis, e...

NIPSNAP3B elevates mitochondrial biogenesis to attenuate lipid accumulation in childhood obesity via AMPK pathway.

OBJECTIVE: Childhood obesity (CO) has become a global epidemic, leading to rising burden of many diseases and premature death. Thus, this study was co...

Physiological foundation modeling for subclinical disease assessment: a prospective pilot.

OBJECTIVE: Clinical studies struggle to locate the right patients, in part because many remain undiagnosed or lack relevant labels. We develop and pro...

Optimisation and Technological Advances in Cardiovascular Magnetic Resonance to improve Access and Screening.

Cardiovascular magnetic resonance (CMR) can comprehensively assess cardiac function and structure, with a unique capability for tissue characterisatio...

Collaborative breakthroughs in precision diagnosis and treatment of nasopharyngeal cancer: Biomarker‑driven screening and endoscopic minimally invasive surgery reshape the new paradigm of early intervention (Review).

The management of nasopharyngeal carcinoma (NPC), a malignancy with pronounced geographic prevalence in Southeast Asia, is undergoing a paradigm shift...

Diagnostic Accuracy of Artificial Intelligence-Enabled Retinal Biomarkers for Detecting Type 2 Diabetes and Prediabetes Among Asian Indians [DART Study].

PURPOSE: To identify retinal microvascular features that distinguish normoglycemia from diabetes mellitus (DM)[Study-1] and prediabetes (PreDM)[Study-...

Why Metrological Traceability Matters in Medical Laboratory Diagnostics.

Application of the results provided by medical laboratories plays an essential role in medical decision-making. This is not limited to diagnosis and m...

Multidimensional analysis and predictive modeling of cognitive decline risk in the United States using propensity score matching and machine learning.

Cognitive decline, an early indicator of neurodegenerative disorders, presents a growing public health challenge. This study aimed to integrate causal...

Organ-on-a-chip in oral medicine: Emerging approaches and applications.

OBJECTIVES: Organ-on-a-chip (OoC), as a highly biomimetic microphysiological system, is demonstrating significant potential in oral medicine research ...

Predictive model of cognitive dysfunction among the patients with systemic lupus erythematosus.

BACKGROUND: Cognitive dysfunction (CD) is a frequent but often underrecognized clinical feature in systemic lupus erythematosus (SLE) patients. It mar...

Are diagnostic technologies for alzheimer's disease and dementia cost-effective? A systematic review of economic evaluations.

BACKGROUND: Alzheimer's disease (AD) and dementia pose a significant clinical and economic burden globally. Early diagnosis and intervention can poten...