Primary Care

Machine learning and neural network algorithms for prediction of C5 palsy after posterior surgery for ossification of posterior longitudinal ligament.

PURPOSE: C5 palsy (C5P) is one of the main postoperative complications of ossification of the posterior longitudinal ligament (OPLL). However, an accurate predictive tool for C5P remains to be developed. Forecasting this potentially avoidable consequence preoperatively can improve patient management, shared decision-making, and counseling. METHODS: Electronic medical records and radiographic measu...

A modular deep learning architecture for interpretable disease prediction across tabular clinical and biometric datasets.

Accurate disease prediction using clinical datasets is essential for improving early diagnosis and clinical decision-support systems; however, many existing deep learning approaches are disease-specific, computationally intensive, and difficult to generalize across heterogeneous biomedical datasets. This study addresses this challenge by proposing a unified and dataset-aware deep learning framewor...

Plasma proteomic profiles reveal proteins and characteristic patterns associated with hypertension: A prospective cohort study.

BACKGROUND: Longitudinal proteomic studies on hypertension remain scarce. We evaluated the epidemiological associations of circulating proteins with h...

Managing multidrug resistant Gram-negative bacteraemia in immunocompromised hosts.

PURPOSE OF REVIEW: Multidrug-resistant Gram-negative bloodstream infections (MDR-GNBSI) are increasingly frequent in immunocompromised hosts, particul...

Human organoids: Fit for drug discovery?

Organoids are self-organizing three-dimensional (3D) in vitro tissues derived from pluripotent stem cells (PSCs) that recapitulate key structural and ...

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...

Beyond Weight Loss: Obesogenic Memory as Biological Hysteresis in Adipose Tissue Revealed by AI Semantic Mapping With an Exportable Core Corpus.

BACKGROUND: Obesity is commonly viewed as a reversible condition primarily driven by excess body weight. Increasing evidence, however, suggests that a...

Screening for diabetes mellitus in the US population using neural network-based modeling and complex survey designs.

Complex survey designs are widely used in medical cohort studies. Developing risk score models that adequately account for the sampling design is esse...

The Last Mile Problem: A Critical Assessment of Physics-Based and AI Tools for Small Molecule Binding Prediction in Virtual Screening.

Docking-based virtual screening (VS) is essential for hit finding in the initial stage of drug or probe discovery. However, it remains prone to high f...

Ethical risk prevention in client generative artificial intelligence (genAI) use: Applying the primary risk-management model.

As clients increasingly use generative artificial intelligence for emotional support, psychologists now deal with unfamiliar ethical challenges that g...

Deep learning-powered quantification of endocrine cells and CD3+ T cells in the natural history of type 1 diabetes.

AIMS/HYPOTHESIS: Histopathological analysis in type 1 diabetes presents challenges in achieving precise characterisation with cellular quantification ...

Transcription Factor SPI1 Mediates Chronic Neuropathic Pain by Activating NLRC4 Transcription to Drive Microglial Activation and Inflammation.

Microglial polarization plays a key role in the process of chronic neuropathic pain (CNP). This study aims to investigate the molecular mechanism by w...

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...

Automated Approaches of Text Simplification of Patient Education Materials: Scoping Review.

BACKGROUND: Patient education materials (PEMs) often exceed the American Medical Association's (AMA) recommended sixth-grade reading grade level (RGL)...

Advancements and challenges in blood pressure monitoring using pulse wave propagation: a comprehensive review and ISO 81060-2 based statistical analysis.

Cardiovascular diseases, particularly hypertension, remain a major global health burden, highlighting the need for accurate and accessible blood press...

Financial incentives increase uptake and perceived effectiveness of autonomous medical AI, yet patients still seek human reconfirmation.

Artificial intelligence (AI) is increasingly used for diagnostic screening. In diabetic retinopathy screening, autonomous AI systems can identify dise...

Commercial AI for CT lung cancer screening: product capabilities, coverage of nodule management tasks and supporting evidence.

OBJECTIVES: To characterize the capabilities of CE-marked AI products for lung nodule analysis in lung cancer screening (LCS), quantify their coverage...

Smartphone-based lightweight AI system for real-time multiple anterior segment disease screening: development and real-world validation.

BACKGROUND: Anterior segment diseases are a major global cause of preventable blindness, especially in regions with limited access to specialized opht...

A Machine-Learning Assisted Genetic Risk Score Identifies Improved Weight Loss After Endoscopic Sleeve Gastroplasty.

BACKGROUND AND AIMS: Obesity remains an epidemic associated with significant health consequences. Endoscopic sleeve gastroplasty (ESG) can lead to sig...

Integrative transcriptomic and machine learning approach reveals key DDR genes and predictors of ami risk in the Bangladeshi population.

Acute Myocardial Infarction (AMI) is a significant contributor to cardiovascular death, with rising prevalence in Bangladesh. Although DNA damage cont...