Infectious Disease

Rapid prediction of key residues for foldability by machine learning model enables the design of highly functional libraries with hyperstable constrained peptide scaffolds.

Peptides are an emerging modality for developing therapeutics that can either agonize or antagonize cellular pathways associated with disease, yet peptides often suffer from poor chemical and physical stability, which limits their potential. However, naturally occurring disulfide-constrained peptides (DCPs) and de novo designed Hyperstable Constrained Peptides (HCPs) exhibiting highly stable and d...

Deep learning pipeline for accelerating virtual screening in drug discovery.

In the race to combat ever-evolving diseases, the drug discovery process often faces the hurdles of high-cost and time-consuming procedures. To tackle these challenges and enhance the efficiency of identifying new therapeutic agents, we introduce VirtuDockDL, which is a streamlined Python-based web platform utilizing deep learning for drug discovery. This pipeline employs a Graph Neural Network to...

Machine-learning methodologies to predict disease progression in chronic hepatitis B in Africa.

BACKGROUND: Little is known about the determinants of disease progression among African patients with chronic HBV infection.

A Single-Cell Interrogation System from Scratch: Microfluidics and Deep Learning.

Live-cell imaging using fluorescence microscopy enables researchers to study cellular processes in unprecedented detail. These techniques are becoming...

Machine learning-based model for predicting the occurrence and mortality of nonpulmonary sepsis-associated ARDS.

OBJECTIVE: The objective was to establish a machine learning-based model for predicting the occurrence and mortality of nonpulmonary sepsis-associated...

Small Molecule Inhibitors of Topoisomerase I Identified by Machine Learning and In Vitro Assays.

Tuberculosis (TB) caused by is a leading infectious cause of death globally. The treatment of patients becomes much more difficult for the increasing...

Applications of artificial intelligence for chemical analysis and monitoring of pharmaceutical and personal care products in water and wastewater: A review.

Specifying and interpreting the occurrence of emerging pollutants is essential for assessing treatment processes and plants, conducting wastewater-bas...

Role of artificial intelligence in early diagnosis and treatment of infectious diseases.

Infectious diseases remain a global health challenge, necessitating innovative approaches for their early diagnosis and effective treatment. Artificia...

Neural network-based predictions of antimicrobial resistance phenotypes in multidrug-resistant from whole genome sequencing and gene expression.

Whole genome sequencing (WGS) potentially represents a rapid approach for antimicrobial resistance genotype-to-phenotype prediction. However, the chal...

An antimicrobial drug recommender system using MALDI-TOF MS and dual-branch neural networks.

Timely and effective use of antimicrobial drugs can improve patient outcomes, as well as help safeguard against resistance development. Matrix-assiste...

Machine learning algorithms for prediction of measles one vaccination dropout among 12-23 months children in Ethiopia.

INTRODUCTION: Despite the availability of a safe and effective measles vaccine in Ethiopia, the country has experienced recurrent and significant meas...

Prediction of acute respiratory infections using machine learning techniques in Amhara Region, Ethiopia.

Many studies have shown that infectious diseases are responsible for the majority of deaths in children under five. Among these children, Acute Respir...

A new approach for sex prediction by evaluating mandibular arch and canine dimensions with machine-learning classifiers and intraoral scanners (a retrospective study).

In circumstances where antemortem information concerning the deceased individual is unavailable, forensic experts prepare biological profiling for uni...

A Systematic Review and Meta-Analysis of the Efficacy of Biosecurity in Disease Prevention and Control in Livestock Farms in Africa.

In Africa, livestock production plays a crucial role for sustainable food security and economic growth. However, the development of this sector has be...

A comprehensive study on tuberculosis prediction models: Integrating machine learning into epidemiological analysis.

Tuberculosis (TB), the second leading infectious killer globally, claimed the lives of 1.3 million individuals in 2022, after COVID-19, surpassing the...

Automatic face detection based on bidirectional recurrent neural network optimized by improved Ebola optimization search algorithm.

Face detection is a multidisciplinary research subject that employs fundamental computer algorithms, image processing, and patterning. Neural networks...

Advantages of Metabolomics-Based Multivariate Machine Learning to Predict Disease Severity: Example of COVID.

The COVID-19 outbreak caused saturations of hospitals, highlighting the importance of early patient triage to optimize resource prioritization. Herein...

Critical care studies using large language models based on electronic healthcare records: A technical note.

The integration of large language models (LLMs) in clinical medicine, particularly in critical care, has introduced transformative capabilities for an...

Machine learning-based prediction of bioactivity in HIV-1 protease: insights from electron density analysis.

To develop a model for predicting the biological activity of compounds targeting the HIV-1 protease and to establish factors influencing enzyme inhib...

Hyperspectral imaging analysis for early detection of tomato bacterial leaf spot disease.

Recent advancements in hyperspectral imaging (HSI) for early disease detection have shown promising results, yet there is a lack of validated high-res...