Alternative Medicine

Must Every Dental Student Become Digitally Competent? Lessons From Prosthodontic Education in Southeast Asia.

INTRODUCTION: Digital technologies, including intraoral scanners, computer-aided design/computer-aided manufacturing (CAD/CAM), cone-beam computed tomography, artificial intelligence and additive manufacturing, are reshaping contemporary dental practise. Dental schools must therefore determine how digital competence should be defined and integrated into undergraduate curricula while preserving cor...

Effectiveness of Socially Assistive Robots in Promoting Positive Emotional Responses and Alleviating Postoperative Pain Among Children: Quantitative Study.

BACKGROUND: Pain remains a critical issue among hospitalized children and may negatively affect postoperative recovery. In addition to pharmacological pain management, nonpharmacological approaches have been used to support pediatric care. Among these emerging approaches, socially assistive robots (SARs) may offer an opportunity to support children during hospitalization. However, limited evidence...

An autonomous multimodal AI agent for evidence-grounded ophthalmic diagnosis.

Multimodal ophthalmic diagnosis requires integrating fundus photography, B-scan ultrasonography, and medical evidence, yet most artificial intelligenc...

Beyond the guidelines: Vascular function as the central determinant and therapeutic target in hypertension.

Hypertension has traditionally been defined and managed according to brachial blood pressure levels. Although this pressure-centric strategy has signi...

Integrative Multi-Omics Analysis Identifies Key Molecular Targets Linking Bisphenol A Exposure to Gestational Diabetes Mellitus.

Bisphenol A (BPA) exposure is associated with gestational diabetes mellitus (GDM); however, the underlying molecular mechanisms remain elusive. This s...

AI-Empowered Nuclear Medicine Education, Part 3: Practical AI Applications for Learners.

Expanding clinical volumes, evolving radiopharmaceuticals, and new imaging technologies shape the training environment for nuclear medicine (NM) learn...

Altered default mode network homogeneity in chronic insomnia disorder: modulation by modified suanzaoren decoction and estazolam, and machine learning classification.

OBJECTIVE: Chronic Insomnia Disorder (CID) is characterized by maladaptive self-referential thinking linked to default mode network (DMN) dysfunction....

Precision Endodontics-Advancing Towards Omics-Guided Personalisation: A Narrative Review.

AIM: To critically evaluate the emerging contribution of genomics, transcriptomics, proteomics, metabolomics and microbiomics to the development of pr...

Automated Differentiation of Oral Red-White Lesions: An Interpretable Deep Learning Approach Combining Ensemble Architectures and Saliency Maps.

INTRODUCTION: Oral Potentially Malignant Disorders (OPMDs), including Leukoplakia and Erythroplakia, carry significant risks of malignant transformati...

A deep learning framework for multi-lead ECG arrhythmia classification with CAM interpretability and LLM-driven clinical guidance.

Cardiac arrhythmias remain a major cause of morbidity and mortality, requiring accurate and interpretable automated diagnosis. This reserach presents ...

Digital health technologies in oncology services: a scoping review of clinical implementation, organisational evidence gaps, and policy implications.

INTRODUCTION: Digital health technologies are increasingly used across oncology services, but the available evidence remains concentrated on patient-f...

Integrative network pharmacology, transcriptomics, and molecular docking identify candidate Centella asiatica constituents and targets in neurodegenerative diseases.

BACKGROUND: Neurodegenerative diseases, including Alzheimer's disease (AD), Parkinson's disease (PD), and Huntington's disease (HD), are progressive d...

Non-invasive individual identification of adult Pleurodeles waltl using Deep Learning.

Reliable individual identification is essential for long-term tracking and reproducible laboratory animal studies. In amphibians, invasive marking met...

Integrative Analysis Reveals Interactions Between Gut Microbiota-Derived Metabolites and the Brain in Parkinson's Disease.

Parkinson's disease (PD) is a neurodegenerative disorder increasingly associated with gut microbiota alterations, yet the mechanisms by which microbia...

EXPLAIN COVIDNET: EXPLAINABLE AI FOR TRANSPARENT AND RELIABLE X-RAY SCREENING.

Recently, deep learning has emerged as a prominent branch of AI, gaining attention for its high accuracy and wide-ranging application in various domai...

Aligning deep learning and interpretable models for blood cell classification: A dual-model framework for explainability.

Blood smear examination involves classifying cells by morphology under a microscope, a labour-intensive process prone to subjective variation. Recent ...

Predicting medication non-adherence using machine learning: Incorporating Complementary and Alternative Medicine (CAM) beliefs in Malaysian chronic disease patients.

Medication non-adherence among chronic disease patients remains a major contributor to poor health outcomes and medication wastage, particularly in mu...

Risk Stratification in Cardiovascular Medicine for Prognostic Assessment and Therapeutic Decision-Making: From Atrial Fibrillation to the Broader Disease Spectrum.

Risk stratification using validated scoring systems is fundamental to contemporary cardiovascular medicine, underpinning diagnosis, treatment selectio...

Accelerated brain aging and anterior white matter hyperintensity burden in chronic post-stroke aphasia: a lesion-aware MRI analysis.

BACKGROUND AND PURPOSE: Chronic post-stroke aphasia is heterogeneous, and focal lesion models do not fully explain persistent language impairment. We ...

iNaturalist mammal observations classified by evidence type.

Ecologists show growing interest in observational data generated by citizen scientists. For mammals, the largest citizen science platform is iNaturali...