Primary Care

Lightweight liquid neural networks decipher salivary metabolic fingerprinting for high-risk periodontitis screening in diabetes.

Type 2 diabetes (T2DM) and periodontitis are bidirectionally linked diseases that both involve chronic inflammation; their co‑occurrence represents a high‑risk clinical condition requiring timely identification. In this proof‑of‑concept, dual‑center feasibility study (n = 426), we evaluate a rapid, non‑invasive approach for identifying individuals with co‑occurring periodontitis and T2DM by integr...

Enhancing prediabetes and diabetes detection through a machine learning-enabled self-assessment approach.

OBJECTIVES: Reliable, accessible, noninvasive self-assessment screening for prediabetes/diabetes is lacking, leading to missed opportunities for early intervention. We aimed to develop and externally validate a machine learning (ML)-derived self-assessment system to predict the likelihood of prevalent prediabetes or diabetes using easily accessible health parameters. STUDY DESIGN AND SETTING: We a...

Community-based early-stage chronic kidney disease screening using explainable machine learning for low-resource settings.

BACKGROUND: Early detection of chronic kidney disease (CKD) is essential for preventing progression to end-stage renal disease. However, existing scre...

Transcranial Doppler ultrasonography in geriatric anesthesia: moving toward personalized brain protection strategies.

The increasing volume of geriatric surgical procedures presents a critical challenge: protecting the aging brain from perioperative complications such...

Quantitative Coronary Atherosclerotic Plaque Burden From CCTA and the Benefit From Lipid-Lowering Medication.

BACKGROUND: We hypothesized that quantification of coronary atherosclerotic plaque burden by artificial intelligence-guided quantitative computed tomo...

Retinal image-based cardiovascular risk prediction using AI-CRS: a multi-modal deep learning framework.

This study presents AI-CRS, an AI-driven deep learning framework for cardiovascular risk assessment using retinal images. By combining convolutional n...

mHealth-Enabled Stroke Screening for Pediatric Sickle Cell Disease in Low-Resource Settings: Systematic Literature Review of Critical Barriers, Emerging Technologies, and AI-Driven Solutions.

BACKGROUND: Sickle cell disease (SCD) is a genetic blood disorder affecting millions globally, with life-threatening complications, and most patients ...

Targeted Real-Time Assessment of Chronic Pain (TRAC-Pain) in Youth: Protocol for a Digital Biosignature Development Through a Prospective Observational Cohort Study.

BACKGROUND: Approximately 1 in 5 children and adolescents live with chronic pain, with musculoskeletal (MSK) pain being one of the most prevalent subt...

Mpox Awareness and Knowledge Among Residents of the Northern Border Region, Saudi Arabia: Implications for Community Preparedness.

In August 2024, the World Health Organization declared the ongoing mpox upsurge in Africa a Public Health Emergency of International Concern, undersco...

Is scaffold hopping possible in machine learning using the electronic-structure-informatics (ESI) descriptor set? an application to natural-product-based drug discovery of α-glucosidase inhibitors.

The electronic-structure informatics (ESI) descriptor set was applied to discover novel α-glucosidase inhibitors from a natural product (NP) database....

Digital health and machine learning in population health and wellness management: A scoping and bibliometric review of effectiveness, equity, and implementation challenges.

Machine learning (ML) in digital health applications is becoming more popular for the general management of population wellness and the promotion of l...

Development and validation of a nomogram for predicting advanced chronic kidney disease.

The objective of this study was to develop and validate a nomogram for predicting advanced chronic kidney disease (CKD) through the utilization of rou...

Mining Heterogeneous Individual Factors in Sustained Compliance With Major Epidemic Prevention and Control Policies.

In major epidemic prevention and control, sustained public compliance with policies is crucial. This study is based on three-phase survey data from 48...

Co-repression of Yap1 and Sox9 Abrogates Established Cholangiocarcinoma by Eliminating Transcriptional Compensation.

BACKGROUND/AIMS: Intrahepatic cholangiocarcinoma (iCCA) represents an unmet clinical need due to its increasing incidence, aggressive biology, and lim...

Artificial intelligence for nursing data visibility in health technology assessment: policy architecture and implementation considerations.

Background: Health technology assessment (HTA) increasingly informs reimbursement, adoption, scale-up, and disinvestment decisions, yet many evidentia...

Prediction model for frailty risk in ischemic stroke patients: Application and validation of support vector machines and nomograms.

This study aimed to develop a prediction model based on nomograms and support vector machines (SVM) to assess frailty risk in ischemic stroke patients...

Synthetic data-augmented machine learning for 30-day readmission prediction in patients with chronic conditions: a retrospective real-world study.

OBJECTIVES: To develop and evaluate an explainable machine learning framework enhanced with synthetic data generation to predict unplanned 30-day hosp...

Accelerating tuberculosis diagnosis in Mozambican prisons using digital chest X-rays with computer-aided detection: a longitudinal, comprehensive health intervention.

BACKGROUND: Mozambique has a high burden of tuberculosis (TB) and in 2021, an estimated 18,000 persons with TB nationwide were not diagnosed. Estimate...

EfficientNet-driven deep learning for accurate detection of faults in photovoltaic cells.

The global transition to renewable energy resources has driven the need for potent international practice attention on optimized Photovoltaic (PV) sys...

Prospectively screening for venous thromboembolism in patients with esophagectomy for cancer improves survival: The complexity of simplicity.

BACKGROUND: We implemented a prospective screening program to detect deep venous thromboembolism and define its prevalence in patients with esophageal...