Primary Care

Predicting suicidal ideation from depression screening data: A network-augmented machine learning approach.

BACKGROUND: Suicidal ideation is often assessed using a single self-report item in routine screening. We developed a model that combines machine learning with symptom-network analytics to infer an auxiliary signal relevant to suicidal ideation from routine depressive-symptom data. METHODS: Adults from the National Health and Nutrition Examination Survey (N = 44,922) were used to predict ideation (...

Microneedle-based theranostics for melanoma: Advances and outlook.

Melanoma represents a highly aggressive malignancy that poses persistent challenges for clinical diagnosis and treatment. Although surgical intervention remains the primary therapeutic approach, the potential risk of postoperative recurrence and surgical complications underscores the critical importance of adjuvant therapies. Microneedles (MNs), as a promising drug delivery device, utilize micron-...

Ameliorative effect of Rhus verniciflua Stokes on high-fat diet-induced obesity and advanced analysis with machine learning and deep learning-based network pharmacology.

AIMS: Obesity and metabolic dysfunction-associated steatotic liver disease (MASLD) arise from impaired redox and energy homeostasis, yet current thera...

Using artificial intelligence to predict sexual health outcomes in endometriosis: a decision tree model algorithm.

BACKGROUND: Endometriosis profoundly impairs sexual function through complex interactions between pain, hormonal disturbances, psychological distress,...

Negligible impact of perifissural nodules in an AI-first reader workflow from UK lung screening trial.

OBJECTIVE: To evaluate the effect of perifissural nodules (PFNs) on radiologist workload within an AI-first reader workflow for lung cancer screening,...

Severe COVID-19 in the Republic of Korea: Epidemiology, Risk Factors, Therapeutics, and Prognostic Models From Nationwide Data.

Severe coronavirus disease 2019 (COVID-19) has posed ongoing clinical and public health challenges worldwide, with Korea providing a unique perspectiv...

ToxPLTC: Peptide Toxicity Prediction by Integrating Pretrained T5 Protein Language Model and Text Convolutional Neural Network.

Peptide-based therapeutics show promising potential in treating a range of diseases, such as diabetes, cancer, and chronic pain. However, critical cha...

Artificial intelligence in cancer screening: a narrative review of current evidence and future directions.

INTRODUCTION: Cancer remains one of the leading causes of death worldwide, with outcomes improving significantly when the disease is detected at an ea...

FTO-CHRM3 axis regulates multiple myeloma progression: a machine learning-based identification.

BACKGROUND: Fat Mass and Obesity-Associated (FTO) is linked to multiple myeloma (MM) progression, but its action mechanisms are poorly understood. MET...

Digital twin technologies for supporting self-care in adults with diet-related chronic conditions: a systematic review.

BACKGROUND: Diet-related chronic conditions are major contributors to global morbidity and mortality. Effective management of these conditions require...

Sex Differences in the Associations Between Visceral Adiposity and Hepatic Insulin Clearance in Type 2 Diabetes Mellitus: A Quantitative CT Study.

AIMS: To investigate sex-related differences in the association of body fat distribution with hepatic insulin clearance (HIC) in type 2 diabetes melli...

Development and validation of a risk prediction model for diabetic peripheral neuropathic pain in type 2 diabetes: A machine learning and statistical approach.

OBJECTIVE: To identify independent risk factors for diabetic peripheral neuropathic pain (DPNP), construct a nomogram prediction model, and quantify t...

Can ensemble methods improve predictive performance of existing models estimating chronic kidney disease among patients with diabetes?

BACKGROUND: Clinical prediction models often suffer from poor model transportability and/or subgroup performance resulting from using a single data so...

Palmatine ameliorates MASLD in type 2 diabetes by modulating hepatic apoptosis and inflammation.

Type 2 diabetes mellitus (T2DM) is a major risk factor for metabolic dysfunction-associated steatotic liver disease (MASLD), and their convergence pre...

Feature reduction using swarm optimization and random forest classifiers for early diabetes risk prediction.

Diabetes is a chronic metabolic disorder caused by excessive blood sugar levels, which leads to severe damage to other organs. Type 2 diabetes is, mor...

Epidemiology of Peripheral Artery Disease, Risk Factors, and Trends.

Peripheral artery disease (PAD) affects more than 230 million people worldwide, with a disproportionate burden in low- and middle-income countries. PA...

Validation of an AI-assisted screening tool for lameness detection in dairy cattle: A field-based study for preventive herd health management.

Lameness is a major welfare and economic challenge in the dairy industry, requiring effective surveillance tools for herd-level management. While visu...

Evaluating the accuracy of screening titles and abstracts for progressing to full-text screening by one vs two independent reviewers: part 1 of a meta-research study of rapid review methodological trade-offs.

OBJECTIVES: To determine the accuracy for progressing records to full-text screening using one vs two reviewers to screen title and abstracts in 3 rev...

Repurposing Azilsartan medoxomil attenuates periodontitis by targeting SERPINB9 to promote apoptosis of IL1B+ macrophages.

Periodontitis (PD) is a common chronic inflammatory disease characterized by progressive destruction of periodontal tissues and is associated with sys...

Application of Artificial Intelligence in Chronic Pain: Bibliometric Analysis.

BACKGROUND: In recent years, artificial intelligence (AI) has demonstrated great potential in the field of managing chronic pain (CP). AI can optimize...