Preventive Care

Implementation of a prospective video databank for artificial intelligence model development, validation and clinical outcomes research in gastrointestinal endoscopy.

BACKGROUND AND AIMS: High-quality, annotated datasets are fundamental to clinical research and artificial intelligence (AI) model development. Existing endoscopic databanks are predominantly retrospective, image-based, or lacking patient consent and structured prospective clinical annotations, limiting scientific reproducibility and regulatory-compliant AI validation. This study establishes a pros...

Pioneering detonation pressure in energetic materials.

Accurate prediction of detonation performance is a critical challenge in the design and screening of energetic materials due to the complex and nonlinear interactions among their physicochemical and molecular descriptors. In this study, a comprehensive data-driven framework based on machine learning (ML) algorithms is developed to predict detonation pressure using a curated dataset of 222 distinct...

Predicting Risk Factors of Pressure Injury for Perioperative Patients Through Machine Learning With SHapley Additive exPlanations Based on Hospital Information System.

OBJECTIVE: Perioperative pressure injuries (PIs) are a common complication of surgical hospitalization that can lead to serious health problems, compr...

Machine learning-powered audio-omics processing method as an auxiliary diagnostic approach for advanced nasopharyngeal carcinoma.

PURPOSE: Nasopharyngeal carcinoma (NPC) is located in the nasopharyngeal mucosa and is a malignant tumour of the head and neck, and approximately 70% ...

A machine learning-based screening tool for classifying post-traumatic stress disorder in firefighters: Firefighter Latent Risk Evaluation (FLARE).

BACKGROUND: The prevalence of post-traumatic stress disorder (PTSD) among South Korean firefighters is likely to be under-reported because of stigma a...

Development and evaluation of an explainable machine learning selection pipeline for predicting neoadjuvant chemoradiotherapy response in locally advanced rectal cancer.

BACKGROUND: The selection of appropriate machine learning (ML) methods for clinical research remains challenging, particularly when both predictive pe...

Smartphone-based offline AI for multi-disease retinal screening: Real-world accuracy.

ObjectiveTo evaluate the diagnostic accuracy of a multi-disease offline artificial intelligence system (Medios-AI, MAI), integrated into a smartphone-...

Exploring Non-Embodied AI-Based Digital Companions for Older Adults in Aging and Care Contexts: Protocol for a Scoping Review.

BACKGROUND: Conversational artificial intelligence (AI) technologies are increasingly positioned as a response to social isolation, loneliness, and un...

Beyond the Cuff: Deep Learning-Based Analysis of Handheld Doppler Signals to Detect Masked Peripheral Ischemia in Diabetic Patients with Normal Ankle-Brachial Index.

OBJECTIVE: The Ankle-Brachial Index (ABI) remains the primary screening tool for Peripheral Arterial Disease (PAD). However, its diagnostic performanc...

Facilitating structure-based drug discovery with an artificial intelligence-driven virtual screening platform.

Structure-based virtual screening (VS) via molecular docking is a pivotal approach for hit identification. Many artificial intelligence (AI)-powered p...

Advanced machine learning-based screening for primary aldosteronism with plasma steroids, potassium, and renin.

Commonly used screening tests for primary aldosteronism (PA) provide suboptimal diagnostic accuracy, particularly with antihypertensive medication use...

Supporting Literature Reviews: A Comparison Between Human and Generative Artificial Intelligence Screening for a Scoping Review.

Scoping reviews are used to map the literature within a field or discipline, summarize existing evidence, and identify gaps in knowledge. Conducting a...

NeuroCypher ASD: Machine Learning with Knowledge Graph-Based Representation for ASD Screening in Toddlers.

Autism Spectrum Disorder (ASD) screening often relies on structured questionnaires. Yet these data are not always easy to interpret or use in practice...

Preoperative considerations for nonoperating room anesthesia.

PURPOSE OF THE REVIEW: This review aims to address the unique challenges in nonoperating room anesthesia (NORA) locations, emphasizing the importance ...

Association between non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio (NHHR) and the characteristics of carotid artery plaques: a retrospective study and machine learning model construction.

BACKGROUND: Low-echo plaques are closely related to stroke. Non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio (NH...

Compression Equations in Pharmaceutical Tableting: From Classical Compaction Models to Data-Driven and Mechanistic Approaches.

Powder compaction is a critical step in pharmaceutical tablet manufacturing, yet its multiscale and path-dependent nature makes accurate prediction of...

Artificial Intelligence in Health Technology Assessment Submissions: A Targeted Review of Global Policy and Practice.

OBJECTIVES: Artificial intelligence (AI) has the potential of revolutionizing healthcare, including health technology assessments (HTAs). Although its...

Quantifying the Economic Value of AI-Assisted Diabetic Retinopathy Screening: A Meta-Analysis Using the Incremental Net Benefit Framework.

OBJECTIVE: To quantitatively synthesize the economic value of artificial intelligence (AI)-assisted screening for diabetic retinopathy (DR), a leading...

Predicting High-Risk Colorectal Polyps in African Americans Using Pre-colonoscopy Clinical Features: Machine Learning Model Development and Temporal Validation.

PURPOSE: Risk stratification for advanced colorectal polyps typically relies on colonoscopy and/or pathology findings. However, there is growing inter...

Artificial intelligence in pediatric endoscopy for hereditary polyposis syndromes: promises and challenges.

PURPOSE OF REVIEW: Children with hereditary polyposis syndromes require long-term endoscopic surveillance to reduce risks of gastrointestinal complica...