Surveillance

Spatiotemporal models of dengue epidemiology in the Philippines: Integrating remote sensing and interpretable machine learning.

Previous dengue epidemiological analyses have been limited in spatiotemporal extent or covariate dim...

Artificial Intelligence and the National Violent Death Reporting System: A Rapid Review.

As the awareness on violent deaths from guns, drugs, and suicides emerges as a public health crisis ...

Machine learning in epidemiology: Neural networks forecasting of monkeypox cases.

This study integrates advanced machine learning techniques, namely Artificial Neural Networks, Long ...

Timing Matters: A Machine Learning Method for the Prioritization of Drug-Drug Interactions Through Signal Detection in the FDA Adverse Event Reporting System and Their Relationship with Time of Co-exposure.

INTRODUCTION: Current drug-drug interaction (DDI) detection methods often miss the aspect of tempora...

Diagnostic Utility of Artificial Intelligence-assisted Transperineal Biopsy Planning in Prostate Cancer Suspected Men: A Prospective Cohort Study.

BACKGROUND AND OBJECTIVE: Accurate magnetic resonance imaging (MRI) reporting is essential for trans...

DEMA: A Deep Learning-Enabled Model for Non-Invasive Human Vital Signs Monitoring Based on Optical Fiber Sensing.

Optical fiber sensors are extensively employed for their unique merits, such as small size, being li...

Part I: prostate cancer detection, artificial intelligence for prostate cancer and how we measure diagnostic performance: a comprehensive review.

MRI has firmly established itself as a mainstay for the detection, staging and surveillance of prost...

The AI ethics of digital COVID-19 diagnosis and their legal, medical, technological, and operational managerial implications.

The COVID-19 pandemic has given rise to a broad range of research from fields alongside and beyond t...

Making the black box more transparent: improving the reporting of artificial intelligence studies in healthcare.

Human Activity Recognition Based on Deep Learning and Micro-Doppler Radar Data.

Activity recognition is one of the significant technologies accompanying the development of the Inte...

Energy Expenditure Prediction from Accelerometry Data Using Long Short-Term Memory Recurrent Neural Networks.

The accurate estimation of energy expenditure from simple objective accelerometry measurements provi...

Phylogenetic and Molecular Characteristics of Wild Bird-Origin Avian Influenza Viruses Circulating in Poland in 2018-2022: Reassortment, Multiple Introductions, and Wild Bird-Poultry Epidemiological Links.

Since 2020, a significant increase in the severity of H5N highly pathogenic avian influenza (HPAI) e...

Redefining Healthcare With Artificial Intelligence (AI): The Contributions of ChatGPT, Gemini, and Co-pilot.

Artificial Intelligence (AI) in healthcare marks a new era of innovation and efficiency, characteriz...

AImedReport: A Prototype Tool to Facilitate Research Reporting and Translation of Artificial Intelligence Technologies in Health Care.

Application of deep learning on mammographies to discriminate between low and high-risk DCIS for patient participation in active surveillance trials.

BACKGROUND: Ductal Carcinoma In Situ (DCIS) can progress to invasive breast cancer, but most DCIS le...

The application value of deep learning-based nomograms in benign-malignant discrimination of TI-RADS category 4 thyroid nodules.

Thyroid nodules are a common occurrence, and although most are non-cancerous, some can be malignant....

Explainable artificial intelligence models for predicting risk of suicide using health administrative data in Quebec.

Suicide is a complex, multidimensional event, and a significant challenge for prevention globally. A...

Application of computer vision and deep learning models to automatically classify medically important mosquitoes in North Borneo, Malaysia.

Mosquito-borne diseases have emerged in North Borneo in Malaysia due to rapid changes in the forest ...

Automatic ARDS surveillance with chest X-ray recognition using convolutional neural networks.

OBJECTIVE: This study aims to design, validate and assess the accuracy a deep learning model capable...

Integrating Clinical Guidelines With ChatGPT-4 Enhances Its' Skills.

Navigating clinical guidelines can be complex for real-time health care decision making. Our study e...

Automatic categorization of self-acknowledged limitations in randomized controlled trial publications.

OBJECTIVE: Acknowledging study limitations in a scientific publication is a crucial element in scien...