Infectious Disease

Predicting viral proteins that evade the innate immune system: a machine learning-based immunoinformatics tool.

Viral proteins that evade the host's innate immune response play a crucial role in pathogenesis, sig...

Hyperspectral imaging and deep learning for parasite detection in white fish under industrial conditions.

Parasites in fish muscle present a significant problem for the seafood industry in terms of both qua...

Machine learning for improved medical device management: A focus on defibrillator performance.

BackgroundPoorly regulated and insufficiently maintained medical devices (MDs) carry high risk on sa...

Statistical inference and neural network training based on stochastic difference model for air pollution and associated disease transmission.

A polluted air environment can potentially provoke infections of diverse respiratory diseases. The d...

A multi-layer neural network approach for the stability analysis of the Hepatitis B model.

In the present study, we explore the dynamics of Hepatitis B virus infection, a significant global h...

Graph-based machine learning model for weight prediction in protein-protein networks.

Proteins interact with each other in complex ways to perform significant biological functions. These...

Molecular mechanism underlying effect of D93 and D289 protonation states on inhibitor-BACE1 binding: exploration from multiple independent Gaussian accelerated molecular dynamics and deep learning.

BACE1 has been regarded as an essential drug design target for treating Alzheimer's disease (AD). Mu...

Personalized cancer vaccine design using AI-powered technologies.

Immunotherapy has ushered in a new era of cancer treatment, yet cancer remains a leading cause of gl...

Endemic area of emerging tick-borne Yezo virus infections discovered in China.

Leveraging large-scale Mycobacterium tuberculosis whole genome sequence data to characterise drug-resistant mutations using machine learning and statistical approaches.

Tuberculosis disease (TB), caused by Mycobacterium tuberculosis (Mtb), is a major global public heal...

Prediction of viral oncoproteins through the combination of generative adversarial networks and machine learning techniques.

Viral oncoproteins play crucial roles in transforming normal cells into cancer cells, representing a...

In silico formulation optimization and particle engineering of pharmaceutical products using a generative artificial intelligence structure synthesis method.

Pharmaceutical drug dosage forms are critical for ensuring the effective and safe delivery of active...

Pioneering Klebsiella Pneumoniae Antibiotic Resistance Prediction With Artificial Intelligence-Clinical Decision Support System-Enhanced Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry: Retrospective Study.

BACKGROUND: The rising prevalence and swift spread of multidrug-resistant gram-negative bacteria (MD...

Development and Validation of Deep Learning-Based Infectivity Prediction in Pulmonary Tuberculosis Through Chest Radiography: Retrospective Study.

BACKGROUND: Pulmonary tuberculosis (PTB) poses a global health challenge owing to the time-intensive...

The Role of Artificial Intelligence in Accelerating Vaccine Development: Challenges and Opportunities in Pandemic Preparedness.

Artificial intelligence (AI) has been studied and applied to medicines and vaccine development. Howe...

An Integrated TCN-CrossMHA Model for Predicting circRNA-RBP Binding Sites.

Circular RNA (circRNA) has the capacity to bind with RNA binding protein (RBP), thereby exerting a s...

Bacterial profile-based body fluid identification using a machine learning approach.

BACKGROUND: Identifying the origins of biological traces is critical for the reconstruction of crime...

Pred-AHCP: Robust Feature Selection-Enabled Sequence-Specific Prediction of Anti-Hepatitis C Peptides via Machine Learning.

Every year, an estimated 1.5 million people worldwide contract Hepatitis C, a significant contributo...

Interaction-Based Inductive Bias in Graph Neural Networks: Enhancing Protein-Ligand Binding Affinity Predictions From 3D Structures.

Inductive bias in machine learning (ML) is the set of assumptions describing how a model makes predi...

KnowVID-19: A Knowledge-Based System to Extract Targeted COVID-19 Information from Online Medical Repositories.

We present KnowVID-19, a knowledge-based system that assists medical researchers and scientists in e...

Rapid bacterial identification through volatile organic compound analysis and deep learning.

BACKGROUND: The increasing antimicrobial resistance caused by the improper use of antibiotics poses ...