Surveillance

Global emission factor dataset for Scope 3 machine learning applications.

The accurate and transparent estimation of greenhouse gas emissions is essential for corporate sustainability reporting and machine learning applications. Existing emission-factor datasets have restrictive licenses, insufficient spatiotemporal granularity, or outdated information, limiting their reproducibility and utility across disciplines. We present ExioML, an open-source dataset derived from ...

Machine learning-based COVID-19 prognostic models lag behind in reporting quality: findings from a TRIPOD/TRIPOD + AI systematic review.

BACKGROUND: Reporting of COVID-19 prognostic models frequently falls short of established standards. The TRIPOD checklist and its 2024 AI extension (TRIPOD + AI) provide a comprehensive framework for assessing reporting quality. We therefore evaluated and compared reporting completeness in conventional versus machine-learning models. METHODS: Studies reporting the development, and internal and ext...

Fairness Correction in COVID-19 Predictive Models Using Demographic Optimization: Algorithm Development and Validation Study.

BACKGROUND: COVID-19 forecasting models have been used to inform decision-making around resource allocation and intervention decisions, such as hospit...

Predicting genetic evolution of viruses to identify suitable vaccines using artificial intelligence.

The evolution of the viruses is rapidly becoming a global challenge to the creation of vaccines since the new variants are often capable of escaping t...

Bias and Oversight in Clinical AI: A Review of Decision Support Tools and Equity Frameworks.

Artificial intelligence (AI) decision support tools (DSTs) are increasingly used across clinical settings to improve efficiency and support decision-m...

Forecasting Local Surges in COVID-19 Hospitalizations through Adaptive Decision Tree Classifiers.

IntroductionDuring the COVID-19 pandemic, many communities across the United States experienced surges in hospitalizations, which strained the local h...

Transforming clinical toxicology in Singapore: four decades of progress and beyond.

By examining key milestones, challenges and future directions, this review chronicles the evolution of clinical toxicology in Singapore into a recogni...

Simplifying Depression Diagnosis: Single-Channel EEG and Deep Learning Approaches.

Major depressive disorder (MDD) or depression is a chronic mental illness that significantly impacts individuals' well-being and is often diagnosed at...

Assessing the Role of Artificial Intelligence in Caries Detection and Clinical Decision-Making: A Scoping Review.

BACKGROUND AND OBJECTIVE: Artificial Intelligence (AI) support is expected to increase accuracy and improve treatment plans in dentistry. Nevertheless...

Data pipeline quality: development and validation of a quality assessment tool for data-driven algorithms and artificial intelligence in healthcare.

OBJECTIVES: To develop and validate a tool for standardised quality assessment of data-driven algorithms in healthcare, focusing on the underlying dat...

ML-Assisted Olfactory Epidemiology Survey Urbanizing China: A Population-Based Study in Yancheng.

OBJECTIVES: Urbanization-related air pollution may be associated with olfactory dysfunction (OD) in China, yet population studies are lacking. METHODS...

Psychopathology profiles and longitudinal correlates of nonsuicidal self-injury in youth: a machine-learning approach.

Nonsuicidal self-injury (NSSI) in youth is clinically heterogeneous. We aimed to identify distinct psychopathology-based profiles among children and a...

Electronic health record use in physiotherapy: adoption, perceived relevance and utilisation patterns-a cross-sectional study.

OBJECTIVES: This study aims to assess electronic health record (EHR) use in physiotherapy, identify factors influencing its adoption and evaluate phys...

Evaluation of trajectory analysis for disease risk assessment: a scoping review.

OBJECTIVES: Increasingly, structured longitudinal electronic health records (EHRs) are being harnessed to predict risk of having present but as yet un...

Use of Automation Technologies and Data Mining in Speech Recognition for Autism.

INTRODUCTION: Early identification of autism spectrum disorder (ASD) is critical for improving long-term outcomes, and speech offers a noninvasive sou...

Simulation-based evaluation of ChatGPT for healthcare associated infection surveillance using validated case scenarios.

BACKGROUND: Surveillance for healthcare-associated infections is central to infection prevention but remains complex, resource-intensive, and variable...

Implementation and current status of frailty assessment in Japanese hospitals: Processes, epidemiology, and future directions.

Frailty has become a pressing health concern in Japan as it has entered a super-aged society. Early identification of frailty is essential to preventi...

Predicting nonresponse to sexual identity question in youth risk behavior surveillance: A machine learning analysis of complex survey data.

PURPOSE: To compare seven machine learning (ML) models developed to predict non-response to the sexual identity question in the 2023 Youth Risk Behavi...

How ready are we to use artificial intelligence in our fight against Antimicrobial resistance? An ESGAID and EAAS perspective.

INTRODUCTION: Antimicrobial resistance (AMR) remains one of the greatest threats to global health, requiring innovative approaches to antibiotic disco...

Mapping the Scientific Landscape of Artificial Intelligence in Endodontics: A Bibliometric Analysis.

INTRODUCTION: The aim of this bibliometric study was to systematically map the evolution, structural characteristics and methodological profile of art...