Product Alert

Ethical engagement with artificial intelligence in faculty research education: evaluation of the New Knowledge Help (NKH) approach.

BACKGROUND: Artificial intelligence (AI) offers new opportunities in healthcare research; however, faculty often lack structured training on its effective and ethical use. Existing faculty development initiatives frequently emphasise tool awareness rather than supporting ethical, reflective, and process-oriented engagement with AI. The New Knowledge Help (NKH) approach was developed as a pedagogic...

Beyond the Model: Practical Insights from Monitoring Predictive Models Across Diverse Clinical Workflows.

OBJECTIVES: To support the artificial intelligence (AI) lifecycle in an integrated academic health system, we implemented a modular monitoring system to oversee electronic health record (EHR) vendor-provided clinical predictive models. This case study describes the lessons learned using this modular system to support sustainable oversight of the deployed predictive models across their lifecycle. M...

Post-swallowing voice-based aspiration screening in dysphagia using a deep learning approach: insights from audio segmentation.

Dysphagia presents a serious risk of aspiration that requires continuous monitoring. This study introduces standardized 2 s voice segments for aspirat...

Optimizing Post-printing Drying Conditions for Point-of-Care Manufacturing of SSE-3D Printed Medicines.

Post-printing drying conditions could affect the quality of oral use printlets elaborated by semi-solid extrusion (SSE) 3D printing, yet their systema...

ToxiGuard: an AOP-guided mechanistically interpretable framework for multi-organ toxicity prediction.

Accurate prediction of organ-specific toxicity with mechanistic interpretability remains a central challenge in chemical safety assessment and transla...

Artificial Intelligence Remote Patient Monitoring for Predicting Overall Survival for Patients Undergoing Radical Cystectomy for Bladder Cancer: Exploratory Analysis of the Prospective Trial.

BACKGROUND: Previous studies have highlighted the benefits of using artificial intelligence-powered remote patient monitoring (AI RPM) in detecting he...

KmalPred: a deep learning framework for lysine malonylation site prediction using protein language model representations.

BACKGROUND: Lysine malonylation (Kmal) is a reversible post-translational modification involved in metabolic regulation and other essential biological...

Deep learning Algorithm for Wound assessment after total kNee (DAWN) arthroplasty : a prospective study protocol.

AIMS: This study aims to develop and internally validate an AI approach based on a deep learning (DL) algorithm to classify wound photographs as eithe...

Minimum Foot Clearance Prediction in Stroke Survivors: A Transformer-Based Approach.

A decrease in Minimum Foot Clearance (MFC), which represents the minimum vertical distance of the foot from the ground surface during the swing phase ...

Effectiveness and students' perception of tutor-guided AI navigation in undergraduate medical education in Sri Lanka: a quasi-experimental study.

BACKGROUND: The integration of Artificial Intelligence (AI), particularly Large Language Models (LLMs) such as ChatGPT, into undergraduate medical edu...

Comparing Facial Attractiveness and Professional Acceptance Between Real and AI-Generated Orthodontic Treatment Outcome Images.

BACKGROUND: Facial attractiveness influences social and professional perceptions, including competence and employability. With the increasing use of a...

HybridTrust: on-device federated learning with crypto-agile security for legacy and quantum-safe medical devices.

The process of migration of IoMT systems in healthcare into post-quantum cryptographic systems is expected to be a gradual one. Here, existing ECC-bas...

Interpretable machine learning using accumulated local effects to characterise predictors of subclinical leaflet thrombosis after self-expanding transcatheter aortic valve implantation.

OBJECTIVES: Subclinical leaflet thrombosis is an early form of bioprosthetic valve dysfunction after transcatheter aortic valve implantation. Predicti...

Efficacy and safety evaluation of artificial intelligence-identified antimicrobial peptides targeting avian pathogenic Escherichia coli in broiler chickens.

BACKGROUND: The overuse of antibiotics in both veterinary and human medicine has resulted in the emergence of antibiotic-resistant bacteria, prompting...

CRISP: Enhancing ASE Workflows With Advanced Molecular Simulation Post-Processing.

Molecular simulations are invaluable for analysing molecular systems, but existing post-processing tools are often limited by a lack of customization,...

Artificial intelligence for left ventricular strain.

PURPOSE OF REVIEW: To review recent advances in artificial intelligence (AI) for left ventricular (LV) strain echocardiography, with emphasis on studi...

Design and evaluation of a resilient IBN architecture: Integrating post-quantum cryptography with adaptive threat detection using machine learning.

As the domain of network security keeps on evolving rapidly, especially in sensitive areas such as healthcare systems, the demand for reliable device ...

Generative AI-Assisted Microlearning for Erectile Dysfunction Myth Reduction: Single-Center Pre-Post Quasi-Experimental Study.

BACKGROUND: Erectile dysfunction (ED) is strongly influenced by persistent misconceptions that delay help-seeking and limit engagement with effective ...

Use of Commercially Available Large Language Models to Generate Information Leaflets on Post-Intensive Care Syndrome: Clinical Utility Assessment.

BACKGROUND: Patients and their families without medical knowledge may find professional health care information difficult to understand. The use of la...

Integrated machine learning-bayesian receptor modelling framework for uncertainty-aware source apportionment in a non-stationary fluoride-contaminated coastal aquifer.

Fluoride contamination in coastal aquifers is difficult to evaluate because its mobilisation is controlled by overlapping and seasonally dynamic non-s...