Public Health

The development of a prediction model based on deep learning for prognosis prediction of gastrointestinal stromal tumor: a SEER-based study.

Accurately predicting the prognosis of Gastrointestinal stromal tumor (GIST) patients is an importan...

Assisting the infection preventionist: Use of artificial intelligence for health care-associated infection surveillance.

BACKGROUND: Health care-associated infection (HAI) surveillance is vital for safety in health care s...

Development of a deep learning-based surveillance system for forest fire detection and monitoring using UAV.

This study presents a surveillance system developed for early detection of forest fires. Deep learni...

Development and validation of a random forest algorithm for source attribution of animal and human Typhimurium and monophasic variants of Typhimurium isolates in England and Wales utilising whole genome sequencing data.

Source attribution has traditionally involved combining epidemiological data with different pathogen...

Prevalence and Risk Factors of Chronic Kidney Disease in the General Population in Abidjan, Côte d'Ivoire: A Cross-sectional Study.

Chronic kidney disease (CKD) is a major cause of morbidity and mortality worldwide, but few studies ...

Parallel prediction of dengue cases with different risks in Mexico using an artificial neural network model considering meteorological data.

In 2022, Mexico registered an increase in dengue cases compared to the previous year. On the other h...

Deep self-supervised machine learning algorithms with a novel feature elimination and selection approaches for blood test-based multi-dimensional health risks classification.

BACKGROUND: Blood test is extensively performed for screening, diagnoses and surveillance purposes. ...

Review of the application of the most current sophisticated image processing methods for the skin cancer diagnostics purposes.

This paper presents the most current and innovative solutions applying modern digital image processi...

Construction of an aerolysin-based multi-epitope vaccine against an machine learning and artificial intelligence-supported approach.

, a gram-negative coccobacillus bacterium, can cause various infections in humans, including septic ...

Disinformation and trust in vaccines in the era of artificial intelligence: the necessity of implementing statistical recommendations.

Predicting the incidence of infectious diarrhea with symptom surveillance data using a stacking-based ensembled model.

BACKGROUND: Infectious diarrhea remains a major public health problem worldwide. This study used sta...

Epidemiology of Epstein-Barr Virus Chronic High Viral Load in Kidney Transplant Recipients.

BACKGROUND: Epstein-Barr virus (EBV) chronic high viral load (CHVL) may be defined by >16 000 copies...

Addressing bias in artificial intelligence for public health surveillance.

Components of artificial intelligence (AI) for analysing social big data, such as natural language p...

Inference of annealed protein fitness landscapes with AnnealDCA.

The design of proteins with specific tasks is a major challenge in molecular biology with important ...

Immunization against inhibin DNA vaccine as an alternative therapeutic for improving follicle development and reproductive performance in beef cattle.

The objective of the present study was to investigate the potential role of immunization against INH...

Monitoring Mental Health: Legal and Ethical Considerations of Using Artificial Intelligence in Psychiatric Wards.

Artificial intelligence (AI) is being tested and deployed in major hospitals to monitor patients, le...

An artificial intelligence algorithm for co-clustering to help in pharmacovigilance before and during the COVID-19 pandemic.

AIMS: Monitoring drug safety in real-world settings is the primary aim of pharmacovigilance. Frequen...

How Socio-economic Inequalities Cluster People with Diabetes in Malaysia: Geographic Evaluation of Area Disparities Using a Non-parameterized Unsupervised Learning Method.

Accurate assessments of epidemiological associations between health outcomes and routinely observed ...

Survival prediction of glioblastoma patients using modern deep learning and machine learning techniques.

In this study, we utilized data from the Surveillance, Epidemiology, and End Results (SEER) database...

Use of a Novel Artificial Intelligence System Leads to the Detection of Significantly Higher Number of Adenomas During Screening and Surveillance Colonoscopy: Results From a Large, Prospective, US Multicenter, Randomized Clinical Trial.

INTRODUCTION: Adenoma per colonoscopy (APC) has recently been proposed as a quality measure for colo...

Scoping Review of Deep Learning Techniques for Diagnosis, Drug Discovery, and Vaccine Development in Leishmaniasis.

, a single-cell parasite prevalent in tropical and subtropical regions worldwide, can cause varying ...