Public Health & Policy

How Big Data and Artificial Intelligence Can Help Better Manage the COVID-19 Pandemic.

SARS-CoV2 is a novel coronavirus, responsible for the COVID-19 pandemic declared by the World Health...

Finding warning markers: Leveraging natural language processing and machine learning technologies to detect risk of school violence.

INTRODUCTION: School violence has a far-reaching effect, impacting the entire school population incl...

Current Developments in Digital Quantitative Volume Estimation for the Optimisation of Dietary Assessment.

Obesity is a global health problem with wide-reaching economic and social implications. Nutrition su...

Machine Learning Algorithms in Suicide Prevention: Clinician Interpretations as Barriers to Implementation.

OBJECTIVE: Machine learning algorithms in electronic medical records can classify patients by suicid...

Towards a fully automated surveillance of well-being status in laboratory mice using deep learning: Starting with facial expression analysis.

Assessing the well-being of an animal is hindered by the limitations of efficient communication betw...

Predicting COVID-19 Incidence Through Analysis of Google Trends Data in Iran: Data Mining and Deep Learning Pilot Study.

BACKGROUND: The recent global outbreak of coronavirus disease (COVID-19) is affecting many countries...

PredyCLU: A prediction system for chronic leg ulcers based on fuzzy logic; part II-Exploring the arterial side.

Peripheral arterial disease (PAD) and its most severe form, critical limb ischaemia (CLI), are very ...

How Artificial Intelligence Will Impact Colonoscopy and Colorectal Screening.

Artificial intelligence may improve value in colonoscopy-based colorectal screening and surveillance...

Artificial intelligence-assisted prediction of preeclampsia: Development and external validation of a nationwide health insurance dataset of the BPJS Kesehatan in Indonesia.

BACKGROUND: We developed and validated an artificial intelligence (AI)-assisted prediction of preecl...

Machine learning and the future of Medicare fraud detection.

The Role and Promise of Artificial Intelligence in Medical Toxicology.

Artificial intelligence (AI) refers to machines or software that process information and interact wi...

Prediction of the Vaccine-derived Poliovirus Outbreak Incidence: A Hybrid Machine Learning Approach.

Recently, significant attention has been devoted to vaccine-derived poliovirus (VDPV) surveillance d...

Deep learning approaches for sleep disorder prediction in an asthma cohort.

OBJECTIVE: Sleep is a natural activity of humans that affects physical and mental health; therefore,...

Recent Trends and Future Direction of Dental Research in the Digital Era.

The digital transformation in dental medicine, based on electronic health data information, is recog...

AI-Driven Tools for Coronavirus Outbreak: Need of Active Learning and Cross-Population Train/Test Models on Multitudinal/Multimodal Data.

The novel coronavirus (COVID-19) outbreak, which was identified in late 2019, requires special atten...

Could automated machine-learned MRI grading aid epidemiological studies of lumbar spinal stenosis? Validation within the Wakayama spine study.

BACKGROUND: MRI scanning has revolutionized the clinical diagnosis of lumbar spinal stenosis (LSS). ...

Deep learning algorithm for surveillance of pneumothorax after lung biopsy: a multicenter diagnostic cohort study.

OBJECTIVES: Pneumothorax is the most common and potentially life-threatening complication arising fr...

Soft Clustering for Enhancing the Diagnosis of Chronic Diseases over Machine Learning Algorithms.

Chronic diseases represent a serious threat to public health across the world. It is estimated at ab...

Using Natural Language Processing to improve EHR Structured Data-based Surgical Site Infection Surveillance.

Surgical Site Infection surveillance in healthcare systems is labor intensive and plagued by underre...

Ensuring trustworthy use of artificial intelligence and big data analytics in health insurance.

Technological advances in big data (large amounts of highly varied data from many different sources ...

Development of an early-warning system for high-risk patients for suicide attempt using deep learning and electronic health records.

Suicide is the tenth leading cause of death in the United States (US). An early-warning system (EWS)...