Infectious Disease

Understanding gut microbiome-based machine learning platforms: A review on therapeutic approaches using deep learning.

Human beings possess trillions of microbial cells in a symbiotic relationship. This relationship benefits both partners for a long time. The gut microbiota helps in many bodily functions from harvesting energy from digested food to strengthening biochemical barriers of the gut and intestine. But the changes in microbiota composition and bacteria that can enter the gastrointestinal tract can cause ...

[CHARACTERIZATION OF THE ADAPTIVE IMMUNE REPERTOIRE USING NEXT GENERATION SEQUENCING: RECENT DISCOVERIES IN THE FIELD OF PRIMARY IMMUNODEFICIENCY, AND THE UPCOMING FUTURE].

A powerful adaptive immune system, which includes cellular (T lymphocytes) and humoral (B lymphocytes) immunity, depends on its ability to recognize and protect against millions of different foreign antigens. It does so through an enormous diverse array of T-cell and B-cell receptors, collectively referred to as the adaptive immune repertoire. Using high-throughput sequencing as next generation se...

[Effect of enzybiotics on the healing of Staphylococcus aureus-infected skin wounds in a pig model].

INTRODUCTION: Staphylococcus aureus is a gram-positive, facultatively anaerobic coccus capable of causing infectious diseases in animals and humans. E...

Deep Learning-based Fibrosis Extent on Computed Tomography Predicts Outcome of Fibrosing Interstitial Lung Disease Independent of Visually Assessed Computed Tomography Pattern.

Radiologic pattern has been shown to predict survival in patients with fibrosing interstitial lung disease. The additional prognostic value of fibros...

Multitask Deep Learning for Joint Detection of Necrotizing Viral and Noninfectious Retinitis From Common Blood and Serology Test Data.

PURPOSE: Necrotizing viral retinitis is a serious eye infection that requires immediate treatment to prevent permanent vision loss. Uncertain clinical...

Technology in Medicine: Improving Clinical Documentation.

The association between electronic health record (EHR) documentation and physician burnout is well-known. A combination of insufficient time to comple...

Accurate diagnosis of COVID-19 from lung CT images using transfer learning.

OBJECTIVE: In this study, it is aimed to classify data by feature extraction from tomographic images for the diagnosis of COVID-19 using image process...

Artificial Intelligence Approach for Severe Dengue Early Warning System.

Dengue fever is a viral infectious disease transmitted through mosquito bites, and has symptoms ranging from mild flu-like symptoms to deadly complica...

ViralZone 2024 provides higher-resolution images and advanced virus-specific resources.

ViralZone (http://viralzone.expasy.org) is a knowledge repository for viruses that links biological knowledge and databases. It contains data on virio...

CADD v1.7: using protein language models, regulatory CNNs and other nucleotide-level scores to improve genome-wide variant predictions.

Machine Learning-based scoring and classification of genetic variants aids the assessment of clinical findings and is employed to prioritize variants ...

Coracle-a machine learning framework to identify bacteria associated with continuous variables.

SUMMARY: We present Coracle, an artificial intelligence (AI) framework that can identify associations between bacterial communities and continuous var...

Large-scale genomic survey with deep learning-based method reveals strain-level phage specificity determinants.

BACKGROUND: Phage therapy, reemerging as a promising approach to counter antimicrobial-resistant infections, relies on a comprehensive understanding o...

RNAVirHost: a machine learning-based method for predicting hosts of RNA viruses through viral genomes.

BACKGROUND: The high-throughput sequencing technologies have revolutionized the identification of novel RNA viruses. Given that viruses are infectious...

Protein-protein and protein-nucleic acid binding site prediction via interpretable hierarchical geometric deep learning.

Identification of protein-protein and protein-nucleic acid binding sites provides insights into biological processes related to protein functions and ...

An infection prediction model developed from inpatient data can predict out-of-hospital COVID-19 infections from wearable data when controlled for dataset shift

The COVID-19 pandemic highlighted the importance of early detection of illness and the need for health monitoring solutions outside of the hospital se...

Using Large Language Models for sentiment analysis of health-related social media data: empirical evaluation and practical tips.

Health-related social media data generated by patients and the public provide valuable insights into patient experiences and opinions toward health is...

Optimizing Medication Querying Using Ontology-Driven Approach with OMOP: with an application to a large-scale COVID-19 EHR dataset.

Efficient querying for medication information in Electronic Health Record (EHR) datasets is crucial for effective patient care and clinical research. ...

Does Cohort Selection Affect Machine Learning from Clinical Data?

This study investigates cohort selection and its effects on the quality of machine learning (ML) models trained on clinical data, focusing on measurem...

Emulation of a Target Trial to Estimate the Effect of Selective Serotonin Reuptake Inhibitors on the Development of Antimicrobial-Resistant Infections using Electronic Health Record Data and Causal Machine Learning.

Antimicrobial resistance is a significant public health concern. The use of selective serotonin reuptake inhibitors (SSRIs), medications commonly pres...

Enhancing Antibiotic Stewardship: A Machine Learning Approach to Predicting Antibiotic Resistance in Inpatient Care.

Antibiotics have been crucial in advancing medical treatments, but the growing threat of antibiotic resistance challenges these achievements and empha...