Preventive Care

Predicting mortality risk in pediatric severe pneumonia using a CNN-BiLSTM model with dynamic clinical indicators.

BACKGROUND: Severe pneumonia is a leading cause of mortality in children under 5 years old, and there is currently a lack of reliable biomarkers for early warning of adverse outcomes in the ICU. This study aimed to explore effective prognostic biomarkers for severe pneumonia and apply a deep learning model to predict in-hospital mortality in children with severe pneumonia, thereby supporting clini...

Artificial Intelligence for Digital Breast Tomosynthesis Screening with and without prior Examinations in BreastScreen Norway.

Purpose To evaluate the performance of an artificial intelligence (AI) model for digital breast tomosynthesis (DBT) with and without prior screening examinations, using independent double reading by radiologists as the reference standard. Materials and Methods This retrospective study included women screened at [BLINDED], 2018-2019. The AI model (Transpara v2.1) provided continuous malignancy risk...

Equitable Digital Frailty Screening for Marginalized Older Adults Using Audio Computer-Assisted Self-Interview: Collaborative Development Guide and User Testing Study.

BACKGROUND: Older adults facing social or structural marginalization for reasons such as lower literacy, digital exclusion, financial constraints, res...

Transforming Pediatric Care Through AI: Bridging the Digital Divide in Health Informatics.

Health informatics and artificial intelligence (AI) technologies are increasingly influencing pediatric health care delivery across diverse health sys...

Multi-omics precision diagnosis of brucellosis: Advances in biomarker discovery and clinical application.

Brucellosis, a neglected zoonosis caused by intracellular Brucella bacteria, remains a formidable global public health challenge, especially in develo...

Exploring human GABA transporter 3 binders for epilepsy through quantum reactivity analysis, molecular dynamics, machine learning prediction, and network pharmacology.

CONTEXT: Drug-resistant epilepsy (DRE) remains a major therapeutic challenge, affecting millions of patients globally who do not respond to convention...

NerveAI- a machine learning algorithm for detection of nerve pain in the head and neck.

Nerve pain screening in patients with headache disorders requires specialized clinical knowledge that is frequently not readily accessible at the init...

Machine learning-based prediction of diabetic retinopathy using clinlabomics: a multi-center study.

BACKGROUND: Diabetic retinopathy (DR) is a leading cause of vision loss, yet conventional retinal screening remains costly and resource-intensive. Thi...

A TyG-UHR-based machine learning model for screening lean MAFLD: development and external validation.

BACKGROUND: Lean metabolic dysfunction-associated fatty liver disease (MAFLD) is increasingly recognized but often goes unnoticed during health checku...

Cardiovascular Risk Stratification in Youth-Onset Type 2 Diabetes Using Machine Learning.

BACKGROUND: The rising incidence of youth-onset type 2 diabetes mellitus (T2DM), along with the risk of early cardiovascular complications, is concern...

AI-Driven Discovery of an Allosteric Thrombin-Targeting Anticoagulant Peptide from Traditional Chinese Medicine Dilong (Pheretima aspergillum).

ETHNOPHARMACOLOGICAL RELEVANCE: Dilong, the dried body of Pheretima aspergillum, is a classic traditional Chinese medicine that has been clinically us...

Combining Machine Learning Models and Screening to Enhance Suicide Risk Identification for American Indian Patients: Retrospective Cohort Study.

BACKGROUND: American Indian and Alaska Native communities experience disproportionately high suicide rates. While machine learning (ML) models leverag...

An exploratory study of multi-channel CNN for early detection of lung cancer from longitudinal healthcare records.

Lung cancer remains the leading cause of cancer-related mortality worldwide, with poor survival rates due to late-stage detection. Current low-dose co...

Clinician engagement shapes the impact of AI-based ECG screening for chronic liver disease in primary care.

Artificial intelligence (AI)-based screening tools show promise for early identification of chronic liver disease (CLD), yet their effectiveness in re...

When to stop reviewing: validation of stop criteria in ASReview.

BACKGROUND: Systematic reviews are essential for evidence-based research, but they often require a great deal of time and effort. Although title and a...

A robust machine learning framework for predicting contact angle in nano-assisted chemical EOR.

Wettability alteration through nano-assisted chemical Enhanced Oil Recovery (nano-cEOR) critically governs capillary pressure and multiphase flow in p...

Deep learning prediction of nocturnal hypertension for patients intolerant to ambulatory blood pressure monitoring.

BACKGROUND: Ambulatory blood pressure monitoring (ABPM) plays an irreplaceable role in the diagnosis and management of hypertension. However, more tha...

Risk classification of oral potentially malignant disorders (OPMDs) using explainable machine learning through a community-based cross-sectional study in rural India.

BACKGROUND: Oral cancer is a major public health problem among the population of India. In rural setting whereby there is exposure to high-risk factor...

An integrated AI-driven vaccine design process: a systematic review of workflows from generative design to translational prediction.

Traditional vaccine development faced significant hurdles, including lengthy timelines and high costs, which hindered rapid responses to pathogens. Al...

Artificial intelligence algorithm for real-time detection and counting of Trypanosoma cruzi parasites using smartphone microscopy.

Chagas disease affects 6-7 million people worldwide and causes approximately 12,000 deaths annually. Diagnostic methods vary by disease stage, with se...