Infectious Disease

Characterizing Secretion System Effector Proteins With Structure-Aware Graph Neural Networks and Pre-Trained Language Models.

The Type III Secretion Systems (T3SSs) play a pivotal role in host-pathogen interactions by mediatin...

Neural Networks Based Smart E-Health Application for the Prediction of Tuberculosis Using Serverless Computing.

The convergence of the Internet of Things (IoT) with e-health records is creating a new era of advan...

Machine learning, network pharmacology, and molecular dynamics reveal potent cyclopeptide inhibitors against dengue virus proteins.

The dengue virus is a major global health hazard responsible for an estimated 390 million diseases y...

Internal Medicine Year in Review 2023.

The year 2023 marked a significant change for Internal Medicine, as the number of submissions relate...

Artificial intelligence with mass spectrometry-based multimodal molecular profiling methods for advancing therapeutic discovery of infectious diseases.

Infectious diseases, driven by a diverse array of pathogens, can swiftly undermine public health sys...

Improving viral annotation with artificial intelligence.

Viruses of bacteria, "phages," are fundamental, poorly understood components of microbial community ...

Bridging gaps: a neural network approach for cross-species scRNA-seq analysis in COVID-19.

Enhancing Patient Selection in Sepsis Clinical Trials Design Through an AI Enrichment Strategy: Algorithm Development and Validation.

BACKGROUND: Sepsis is a heterogeneous syndrome, and enrollment of more homogeneous patients is essen...

Prediction of infectious diseases using sentiment analysis on social media data.

As the influence and risk of infectious diseases increase, efforts are being made to predict the num...

Combination therapy synergism prediction for virus treatment using machine learning models.

Combining different drugs synergistically is an essential aspect of developing effective treatments....

An Explainable Graph Neural Framework to Identify Cancer-Associated Intratumoral Microbial Communities.

Microbes are extensively present among various cancer tissues and play critical roles in carcinogene...

Fuzzy lattices assisted EJAYA Q-learning for automated pulmonary diseases classification.

This work proposes a novel technique called Enhanced JAYA (EJAYA) assisted Q-Learning for the classi...

A Holistic, Multi-Level, and Integrative Ethical Approach to Developing Machine Learning-Driven Decision Aids.

Transparency, Evaluation and Going From "Ethics-Washing" to Enforceable Regulation: On Machine Learning-Driven Clinician Decision Aids.

Integrated epigenomic exposure signature discovery.

The epigenome influences gene regulation and phenotypes in response to exposures. Epigenome assessm...

Predicting Response to Neuromodulators or Prokinetics in Patients With Suspected Gastroparesis Using Machine Learning: The "BMI, Infectious Prodrome, Delayed GES, and No Diabetes" Model.

INTRODUCTION: Pharmacologic therapies for symptoms of gastroparesis (GP) have limited efficacy, and ...

A machine learning model to predict liver-related outcomes after the functional cure of chronic hepatitis B.

BACKGROUND & AIMS: The risk of hepatocellular carcinoma (HCC) and hepatic decompensation persists af...

MAPRS: An intelligent approach for post-prescription review based on multi-label learning.

Antimicrobial resistance (AMR) is a major threat to public health worldwide. It is a promising way t...

Special supplement issue on quality assurance and enrichment of biological and biomedical ontologies and terminologies.

Ontologies and terminologies serve as the backbone of knowledge representation in biomedical domains...

Comparative study of machine-and deep-learning based classification algorithms for biomedical Raman spectroscopy (RS): case study of RS based pathogenic microbe identification.

One key aspect pushing the frontiers of biomedical RS is dedicated machine- or deep- learning (ML or...

Use of artificial intelligence algorithms to analyse systemic sclerosis-interstitial lung disease imaging features.

The use of artificial intelligence (AI) in high-resolution computed tomography (HRCT) for diagnosing...