Public Health & Policy

Latest AI and machine learning research in public health & policy for healthcare professionals.

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Novel fuzzy deep learning approach for automated detection of useful COVID-19 tweets.

Coronavirus (COVID-19) is a newly discovered viral disease from the SARS-CoV-2 family. This has caus...

Identification of key genes in spontaneous cerebral hemorrhage and prevention of disease damage: LASSO and SVM regression.

Prevention is more important than treatment, and the incidence of intracerebral hemorrhage can be ef...

A computationally-inexpensive strategy in CT image data augmentation for robust deep learning classification in the early stages of an outbreak.

Coronavirus disease 2019 (COVID-19) has spread globally for over three years, and chest computed tom...

Exploring the artificial intelligence "Trust paradox": Evidence from a survey experiment in the United States.

Advances in Artificial Intelligence (AI) are poised to transform society, national defense, and the ...

Individual health-disease phase diagrams for disease prevention based on machine learning.

Early disease detection and prevention methods based on effective interventions are gaining attentio...

A deep learning-based drug repurposing screening and validation for anti-SARS-CoV-2 compounds by targeting the cell entry mechanism.

The recent outbreak of Corona Virus Disease 2019 (COVID-19) caused by severe acute respiratory syndr...

Pediatric Injury Surveillance From Uncoded Emergency Department Admission Records in Italy: Machine Learning-Based Text-Mining Approach.

BACKGROUND: Unintentional injury is the leading cause of death in young children. Emergency departme...

Modeling Epidemiology Data with Machine Learning Technique to Detect Risk Factors for Gastric Cancer.

PURPOSE: Gastric cancer (GC) ranks as the 7th most common cancer worldwide and a leading cause of ca...

Types, functions and mechanisms of robot-assisted intervention for fall prevention: A systematic scoping review.

BACKGROUND: Any individual may experience accidental falls, particularly older adults. Although robo...

On the use of aspect-based sentiment analysis of Twitter data to explore the experiences of African Americans during COVID-19.

According to data from the U.S. Center for Disease Control and Prevention, as of June 2020, a signif...

Protocol for the automatic extraction of epidemiological information via a pre-trained language model.

The lack of systems to automatically extract epidemiological fields from open-access COVID-19 cases ...

New possibilities for medical support systems utilizing artificial intelligence (AI) and data platforms.

In Japan, there is a growing initiative to construct centralized databases and platforms that can ag...

Integrating Artificial Intelligence and Wearable IoT System in Long-Term Care Environments.

With the rapid advancement of information and communication technology (ICT), big data, and artifici...

The use of digital health in heart rhythm care.

INTRODUCTION: Digital health is a broad term that includes telecommunication technologies to collect...

Automatic retinoblastoma screening and surveillance using deep learning.

BACKGROUND: Retinoblastoma is the most common intraocular malignancy in childhood. With the advanced...

Harnessing artificial intelligence in the post-COVID-19 era: A global health imperative.

Despite the World Health Organization's declaration that the COVID-19 global emergency has ended, th...

Validation of a Salivary miRNA Signature of Endometriosis - Interim Data.

BACKGROUND: The discovery of a saliva-based micro–ribonucleic acid (miRNA) signature for endometrios...

Health system-scale language models are all-purpose prediction engines.

Physicians make critical time-constrained decisions every day. Clinical predictive models can help p...

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