Public Health

Prostate MRI and artificial intelligence during active surveillance: should we jump on the bandwagon?

OBJECTIVE: To review the components of past and present active surveillance (AS) protocols, provide an overview of the current studies employing artificial intelligence (AI) in AS of prostate cancer, discuss the current challenges of AI in AS, and offer recommendations for future research.

Cracking AlphaFold2: Leveraging the power of artificial intelligence in undergraduate biochemistry curriculums.

AlphaFold2 is an Artificial Intelligence-based program developed to predict the 3D structure of proteins given only their amino acid sequence at atomic resolution. Due to the accuracy and efficiency at which AlphaFold2 can generate 3D structure predictions and its widespread adoption into various aspects of biochemical research, the technique of protein structure prediction should be considered fo...

Abnormal Behavior Recognition Based on 3D Dense Connections.

Abnormal behavior recognition is an important technology used to detect and identify activities or events that deviate from normal behavior patterns. ...

Machine learning-based QSAR and LB-PaCS-MD guided design of SARS-CoV-2 main protease inhibitors.

The global outbreak of the COVID-19 pandemic caused by the SARS-CoV-2 virus had led to profound respiratory health implications. This study focused on...

Leveraging advances in data-driven deep learning methods for hybrid epidemic modeling.

Mathematical modeling of epidemic dynamics is crucial to understand its underlying mechanisms, quantify important parameters, and make predictions tha...

Prediction of hepatic metastasis in esophageal cancer based on machine learning.

This study aimed to establish a machine learning (ML) model for predicting hepatic metastasis in esophageal cancer. We retrospectively analyzed patien...

Deep learning models for predicting the survival of patients with medulloblastoma based on a surveillance, epidemiology, and end results analysis.

Medulloblastoma is a malignant neuroepithelial tumor of the central nervous system. Accurate prediction of prognosis is essential for therapeutic deci...

A tree-based explainable AI model for early detection of Covid-19 using physiological data.

With the outbreak of COVID-19 in 2020, countries worldwide faced significant concerns and challenges. Various studies have emerged utilizing Artificia...

Predicting chronic wasting disease in white-tailed deer at the county scale using machine learning.

Continued spread of chronic wasting disease (CWD) through wild cervid herds negatively impacts populations, erodes wildlife conservation, drains resou...

Characterization of the prevalence of Salmonella in different retail chicken supply modes using genome-wide and machine-learning analyses.

Salmonella is a foodborne pathogen that causes salmonellosis, of which retail chicken meat is a major source. However, the prevalence of Salmonella in...

Empowering standardization of cancer vaccines through ontology: enhanced modeling and data analysis.

BACKGROUND: The exploration of cancer vaccines has yielded a multitude of studies, resulting in a diverse collection of information. The heterogeneity...

A Paper-Based Multiplexed Serological Test to Monitor Immunity against SARS-COV-2 Using Machine Learning.

The rapid spread of SARS-CoV-2 caused the COVID-19 pandemic and accelerated vaccine development to prevent the spread of the virus and control the dis...

A versatile automated pipeline for quantifying virus infectivity by label-free light microscopy and artificial intelligence.

Virus infectivity is traditionally determined by endpoint titration in cell cultures, and requires complex processing steps and human annotation. Here...

An emerging network for COVID-19 CT-scan classification using an ensemble deep transfer learning model.

Over the past few years, the widespread outbreak of COVID-19 has caused the death of millions of people worldwide. Early diagnosis of the virus is ess...

Falls Prevention Using AI and Remote Surveillance in Nursing Homes.

The older population of United States is growing, with more adults having complicated medical conditions being admitted into nursing facilities and as...

A Machine Learning Approach to Identify Key Residues Involved in Protein-Protein Interactions Exemplified with SARS-CoV-2 Variants.

Human infection with the coronavirus disease 2019 (COVID-19) is mediated by the binding of the spike protein of the severe acute respiratory syndrome ...

Utilization of machine learning for dengue case screening.

Dengue causes approximately 10.000 deaths and 100 million symptomatic infections annually worldwide, making it a significant public health concern. To...

Machine learning in infectious diseases: potential applications and limitations.

Infectious diseases are a major threat for human and animal health worldwide. Artificial Intelligence (AI) combined algorithms including Machine Learn...

Deep learning models for predicting the survival of patients with hepatocellular carcinoma based on a surveillance, epidemiology, and end results (SEER) database analysis.

Hepatocellular carcinoma (HCC) is a common malignancy with poor survival and requires long-term follow-up. Hence, we collected information on patients...

Machine Learning-Based Prediction of Helicobacter pylori Infection Study in Adults.

BACKGROUND Helicobacter pylori has a high infection rate worldwide, and epidemiological study of H. pylori is important. Artificial intelligence has b...