Article

Integrative analysis of clinical health records, imaging and pathogen genomics identifies personalized predictors of disease prognosis in tuberculosis

2022-07-21

Abstract excerpt

Tuberculosis (TB) afflicts over 10 million people every year and its global burden is projected to increase dramatically due to multidrug-resistant TB (MDR-TB). The Covid-19 pandemic has resulted in reduced access to TB diagnosis and treatment, reversing decades of progress in disease management globally. It is thus crucial to analyze real-world multi-domain information from patient health records to determine per...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: d1015dd9-1338-5f10-8d75-056f71539603
DOI: 10.1101/2022.07.20.22277862

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Integrative analysis of clinical health records, imaging and pathogen genomics identifies personalized predictors of disease prognosis in tuberculosisDOI 10.1101/2022.07.20.22277862Read

Analysis of a Large Patient-Level Dataset to Predict Outcome of Treatment for Drug-Resistant TuberculosisSemantic proximity Read

Radiologist observations of chest X-rays (CXR) predict sputum smear microscopy status in TB Portals, a real-world database of tuberculosis (TB) casesSemantic proximity Read

Comparative analysis of genomic variability for drug-resistant strains of Mycobacterium tuberculosis: The special case of Belarus.Semantic proximity Read

Clinical and bacterial determinants of unfavorable tuberculosis treatment outcomes: an observational study in GeorgiaSemantic proximity Read

Clinical and bacterial determinants of unfavorable tuberculosis treatment outcomes: an observational study in Georgia.Semantic proximity Read

Bringing TB genomics to the clinic: A comprehensive pipeline to predict antimicrobial susceptibility from genomic data, validated and accredited to ISO standardsSemantic proximity Read

Personalized Tuberculosis Treatment Recommendation System (PTTRS) version 1: A Precision-Medicine Based Application for Recommending Personalized Treatment to Tuberculosis PatientsSemantic proximity Read

Machine learning-based analysis of drug resistance mutations in Mycobacterium tuberculosis.Semantic proximity Read

Machine learning and structural analysis of Mycobacterium tuberculosis pan-genome identifies genetic signatures of antibiotic resistanceSemantic proximity Read

A bioinformatic analysis of Mycobacterium tuberculosis and host genomic dataSemantic proximity Read

Genome-Wide Analysis of MDR and XDR Tuberculosis from Belarus: Machine-Learning Approach.Semantic proximity Read

Cohort profile: St. Michael’s Hospital Tuberculosis Database (SMH-TB), a retrospective cohort of electronic health record data and variables extracted using natural language processingSemantic proximity Read