Public Health

Evaluation of machine learning algorithms for the prognosis of breast cancer from the Surveillance, Epidemiology, and End Results database.

INTRODUCTION: Many researchers used machine learning (ML) to predict the prognosis of breast cancer (BC) patients and noticed that the ML model had good individualized prediction performance.

Racial Health Disparities and Black Heterogeneity in COVID-19: A Case Study of Miami Gardens.

The COVID-19 pandemic is a critical public health concern that has disproportionately affected the Black community in the United States. The purpose of this study was to examine the risk and protective factors faced by residents in the City of Miami Gardens during the COVID-19 pandemic, with emphases placed on racial health disparities and Black heterogeneity. Using convenience and snowball sampli...

Implementing machine learning methods with complex survey data: Lessons learned on the impacts of accounting sampling weights in gradient boosting.

Despite the prominent use of complex survey data and the growing popularity of machine learning methods in epidemiologic research, few machine learnin...

The effect of the pandemic on European narratives on smart cities and surveillance.

This article presents an analysis of European smart city narratives and how they evolved under the pressure of the COVID-19 pandemic. We start with Jo...

Opportunities and challenges in application of artificial intelligence in pharmacology.

Artificial intelligence (AI) is a machine science that can mimic human behaviour like intelligent analysis of data. AI functions with specialized algo...

Research on the Application of Artificial Intelligence in Public Health Management: Leveraging Artificial Intelligence to Improve COVID-19 CT Image Diagnosis.

Since the start of 2020, the outbreak of the Coronavirus disease (COVID-19) has been a global public health emergency, and it has caused unprecedented...

Systematic Review of Advanced AI Methods for Improving Healthcare Data Quality in Post COVID-19 Era.

At the beginning of the COVID-19 pandemic, there was significant hype about the potential impact of artificial intelligence (AI) tools in combatting C...

Computational biology: Role and scope in taming antimicrobial resistance.

BACKGROUND: Infectious diseases pose many challenges due to increasing threat of antimicrobial resistance, which necessitates continuous research to d...

A reliable and low-cost deep learning model integrating convolutional neural network and transformer structure for fine-grained classification of chicken Eimeria species.

Chicken coccidiosis is a disease caused by Eimeria spp. and costs the broiler industry more than 14 billion dollars per year globally. Different chick...

A Smartphone-Based Platform Assisted by Artificial Intelligence for Reading and Reporting Rapid Diagnostic Tests: Evaluation Study in SARS-CoV-2 Lateral Flow Immunoassays.

BACKGROUND: Rapid diagnostic tests (RDTs) are being widely used to manage COVID-19 pandemic. However, many results remain unreported or unconfirmed, a...

Smartwatch Sensors with Deep Learning to Predict the Purchase Intentions of Online Shoppers.

In the past decade, the scale of e-commerce has continued to grow. With the outbreak of the COVID-19 epidemic, brick-and-mortar businesses have been a...

Equipment Identification and Localization Method Based on Improved YOLOv5s Model for Production Line.

Intelligent video surveillance based on artificial intelligence, image processing, and other advanced technologies is a hot topic of research in the u...

Using natural language processing to identify opioid use disorder in electronic health record data.

BACKGROUND: As opioid prescriptions have risen, there has also been an increase in opioid use disorder (OUD) and its adverse outcomes. Accurate and co...

Geographical classification of malaria parasites through applying machine learning to whole genome sequence data.

Malaria, caused by Plasmodium parasites, is a major global health challenge. Whole genome sequencing (WGS) of Plasmodium falciparum and Plasmodium viv...

Analyzing factors contributing to COVID-19 mortality in the United States using artificial intelligence techniques.

Having started since late 2019, COVID-19 has spread through far many nations around the globe. Not being known profoundly, the novel virus of the Coro...

Spatio-temporally smoothed deep survival neural network.

The analysis of registry data has important implications for cancer monitoring, control, and treatment. In such analysis, (semi)parametric models, suc...

Epidemiological Features of Acute Myeloid Leukemia in Five Regions of the Republic of Kazakhstan: Population Study.

OBJECTIVE: The aim of the study was to assess the main epidemiological characteristics of AML (morbidity, survival, distribution by AML variants and a...

Integrative transcriptome analysis of SARS-CoV-2 human-infected cells combined with deep learning algorithms identifies two potential cellular targets for the treatment of coronavirus disease.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) quickly spread worldwide, leading coronavirus disease 2019 (COVID-19) to hit pandemic lev...

An autonomous decision-making framework for gait recognition systems against adversarial attack using reinforcement learning.

Gait identification based on Deep Learning (DL) techniques has recently emerged as biometric technology for surveillance. We leveraged the vulnerabili...

Identification of agricultural quarantine materials in passenger's luggage using ion mobility spectroscopy combined with a convolutional neural network.

As economic globalization intensifies, the recent increase in agricultural products and travelers from abroad has led to an increase in the probabilit...