Alternative Medicine

Bias, External Validation, and Real-World Implementation of Artificial Intelligence Models in Cardiovascular Medicine.

Artificial intelligence (AI) and machine learning (ML) have demonstrated strong diagnostic and prognostic performance across cardiovascular medicine. However, translation into equitable real-world benefit is limited by algorithmic bias, inadequate external validation, and unclear implementation pathways. This State-of-the-Art Review evaluates these challenges using the Total Product Life Cycle (TP...

Progress of Traditional Chinese Medicine in Targeting Ferroptosis to Combat Cerebral Ischemia-Reperfusion Injury.

Cerebral ischemia-reperfusion injury (CIRI) often results in significant morbidity and mortality. The effectiveness of current reperfusion therapies is hindered by substantial secondary damage, which highlights the need for novel molecular targets and neuroprotective strategies. Ferroptosis, a form of programmed cell death driven by iron dysregulation and lipid peroxidation, has emerged as a key p...

Reconfiguring biofortification strategies to transform food systems and address micronutrient deficiency of the 21st century.

Despite achieving substantial progress in caloric food security, micronutrient deficiencies remain a major global health challenge, highlighting a per...

Integrative machine learning and gene regulatory network analysis identifies novel genes for leafy head formation in Brassica rapa and B. oleracea.

Leafy head formation is a crucial developmental process in Brassica crops. Here, an integrative approach combining machine learning and gene regulator...

Integrative single-cell and spatial transcriptomics analysis reveals a baicalein-responsive 10-gene signature for non-small cell lung cancer.

BACKGROUND: Non‑small cell lung cancer (NSCLC) remains a leading cause of cancer‑related mortality worldwide. Baicalein, a natural flavonoid, has show...

Making Machine Learning Clinically Useful in Thrombosis and Hemostasis: A Roadmap for Diagnostic Translation.

Artificial intelligence (AI), most often in the form of machine learning (ML), attracts high expectations across medicine and is often discussed as a ...

Pediatric and adolescent nutritional and metabolic assessment in the precision era.

PURPOSE OF REVIEW: To summarize recent methodological and technological advances in assessing nutritional and metabolic status among pediatric and ado...

EXPRESS: Transcriptome profiling and experimental validation identify FOS, RAC2, and TYROBP as potential biomarkers for Fu's subcutaneous needling in neuropathic pain treatment.

BACKGROUND: This study aimed to explore potential biomarkers and mechanisms underlying in the treatment of neuropathic pain(NP) with Fu's subcutaneous...

PEARL: integrative multi-omics classification and omics feature discovery via deep graph learning.

MOTIVATION: Integrating multi-omics data provides valuable insights into biological processes by capturing information across multiple molecular layer...

A Hierarchical Multimodal Framework for Sedation Monitoring in ICU Patients.

In the intensive care unit (ICU), monitoring sedation levels is crucial. Clinicians often rely on intermittent behavioral scales like the Richmond Agi...

Artificial Intelligence in Medicine: Basic Knowledge, Applications, Ethics and Perspectives.

BACKGROUND: Artificial intelligence (AI) is rapidly transforming medicine through advanced diagnostic, prognostic, and decision-support systems. OBJEC...

Enhydrin from yacon attenuates atherosclerosis by modulating the FABP5/PPARγ/ABCA1 axis: An integrated multi-omics and in vivo validation.

Dysregulated lipid metabolism drives atherosclerosis (AS). Yacon, an Andean lipid-modulating tuber, exerts anti-AS potential, but mechanisms remain un...

UV spectroscopy associated with machine learning as a complementary tool for the diagnosis of Ehrlichia canis in dogs.

Canine ehrlichiosis, caused by Ehrlichia canis, is a tick-borne disease with a global distribution that significantly affects the clinical and epidemi...

Performance of Large Language Models on the Brazilian National Medical Education Examination: Comparative Benchmark Study.

BACKGROUND: Large language models (LLMs) are rapidly incorporated into medical education and examination preparation; yet, most benchmarking evidence ...

Integrative multi-omics, machine learning, and experimental validation reveal that TPM1 suppresses M2 macrophage polarization and enhances chemosensitivity in acute myeloid leukemia.

BACKGROUND: Acute myeloid leukemia (AML) remains a therapeutic challenge due to chemoresistance and immunosuppression. This study aimed to discover no...

Clinical governance of artificial intelligence in internal medicine: a literature-informed five-pillar framework for complex care.

Most artificial intelligence (AI) governance frameworks in healthcare address model development, reporting standards, or regulation in broad terms, bu...

Multimodal phenotypic classification of generalized anxiety and panic using structural MRI data and psychosocial factors: machine learning results from the German National Cohort (NAKO) study.

Anxiety disorders are common and impairing mental health conditions. Using data from 26,378 adults in the German National Cohort Study (NAKO), we inve...

A hybrid SE-ResNet50 deep learning framework for high-accuracy and explainable cotton leaf disease classification.

Cotton production is highly vulnerable to foliar diseases and pest-induced damage, which significantly reduce yield and compromise fiber quality. Rapi...

A case-aware feature modulation framework for defect classification in power lines.

Conductors and grounded transmission towers are separated by non-conductive overhead transmission line insulators are known as materials. They frequen...

Full-Body AI Agent: A Perspective on Multi-Scale Collaborative AI for Systemic Biology and Precision Medicine.

Artificial intelligence (AI) is increasingly applied to biomedical research, but most current systems remain limited to specific tasks, data types, or...