Staffing & Scheduling

Predicting Vaping Cessation in Young Adults: A Machine Learning and Explainable Artificial Intelligence (XAI) Approach to Public Health Intervention

The public health impact of vaping in the United States reflects a complex balance of potential benefits and emerging risks. While e-cigarettes can substantially reduce exposure to toxic combustion byproducts and may aid in smoking cessation for adult tobacco users, evidence links e-cigarette use to respiratory and cardiovascular injury, raising concerns about long-term health outcomes in vapers. ...

A Scoping Review of Algorithmic Equity, Data Diversity, and Inclusive Design in the Transformer Era of Clinical NLP

The rapid digitization of healthcare has positioned transformer-based natural language processing (NLP) models as powerful tools for managing clinical textual data. Yet their integration into practice raises unresolved questions of equity and inclusivity criteria. This scoping review synthesizes 56 studies published between 2017 and 2024 to evaluate how equity is addressed across three dimensions:...

Synthetic Anatomy: Deep Learning Models for Virtual Population Generation–A Review

In-silico trials (ISTs) represent a transformative approach in medical research, leveraging computer modelling and simulation to evaluate products vir...

Predicting future cognitive impairment in preclinical Alzheimer’s disease using multimodal imaging: a multisite machine learning study

Predicting the likelihood of developing Alzheimer’s disease (AD) dementia in at-risk individuals is important for the design of and optimal recruitmen...

Finding the Goldilocks zone for toddler accelerometry: how many days are needed for a reliable estimate of physical activity using machine learning?

Accelerometers are used to measure sedentary time (SED) and physical activity (PA) in toddlers, but they may struggle to wear them for extended period...

Effect of a mobile health intervention optimised with artificial intelligence on blood pressure and other cardiovascular risk factors in adults with high blood pressure: Rationale and design of My Intelligent Cardiac Assistant (MICArdiac) Randomised Controlled Trial

Control of blood pressure (BP) continues to be a challenge globally. Clinical trials have shown home BP monitoring and text-message interventions to l...

The Cognitive Safety Net: Comparing Human and AI Diagnostic Reasoning during Complex Clinical Situations

Diagnostic error in high-stakes clinical environments remains a significant cause of preventable harm. While a new generation of customisable digital ...

AI-Simulated Clinical Consultations: Assessing the Potential of ChatGPT to Support Medical Training

Simulated medical scenarios are useful for evaluating and developing clinical competencies but scheduling them is expensive and time-consuming. Large ...

Topological Entropy and Homology Reveal Interpretable and Real-Time Neural Signatures in Pediatric EEG

Decoding neural states from pediatric EEG in naturalistic settings remains challenging due to signal noise, motion artifacts, and intersubject variabi...

Developing Predictive Algorithms for Patient Retention Using Machine Learning and Deep Learning to Improve HIV Care in Uganda

Achieving high retention of people living with HIV (PLHIV) in care remains a challenge in Uganda, despite substantial progress towards UNAIDS 95-95-95...

Patient2Sentence: Semantic Compression of Clinical Trial Eligibility Using Large Language Models

Clinical decision-making generates vast unstructured data that remain underexploited for trial recruitment. We present Patient2Sentence (P2S), a frame...

Entity-centric evaluation of large language model responses for medical question-answering tasks

Develop a metric for evaluating the clinical alignment and informativeness of large language model (LLM)-generated responses in medical question-answe...

Continuous Multimodal AI with Wearable Vital Signs Predicts Postoperative Complications in the General Ward

Surgery is inherently associated with complications, making early detection the cornerstone of timely intervention and improved outcomes. Artificial i...

Prognosis After First-Trimester Threatened Miscarriage: A Systematic Review, Prognostic Accuracy Meta-Analysis, And Prediction Modelling Review

Threatened miscarriage represents one of the most prevalent obstetric emergencies globally. Nevertheless, women experiencing first-trimester bleeding ...

Machine learning-based prediction of future dementia using routine clinical MRI brain scans and healthcare data

Early identification of dementia risk is essential for preventive care and timely enrolment into disease-modifying interventions. Current approaches r...

A double-blind, crossover, non-inferiority randomized controlled trial where primary care providers and patients compare human- and AI-generated digital health messages: the AI-CARE study protocol

Primary care is facing multiple crises, including an increase in health misinformation. Digital health messaging by primary care providers has been sh...

The Economics of Accuracy for Medical Reasoning with Large Language Models

Deploying large language models (LLMs) in clinical settings is limited by security, reliability, latency, and accessibility concerns that favor smalle...

Performance of a Chinese Cognitive Decline Risk Model in a Japanese Cohort: A Validation Study

To develop a simple risk prediction model for cognitive decline in a Chinese older adult cohort, and to evaluate its performance and transportability ...

Explainable Machine Learning for Early Detection of Mild Cognitive Impairment, Fall Risk, and Frailty Using Sensor-Based Motor Function Data

This study aimed to design and evaluate an explainable machine learning (ML) framework that integrates sensor-based motor assessments with demographic...

DMSA: A Decentralized Microservice Architecture for Edge Networks

The dispersed node locations and complex topologies of edge networks, combined with intricate dynamic microservice dependencies, render traditional ...