ArticleFrontiers in genetics2019
Machine Learning Predicts Accurately
Article in Frontiers in genetics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
48 citing papers in PubMed, 86 citations in OpenAlex.
- Global Research Trends and Insights on AI Usage in Tuberculosis: Bibliometric Analysis.JMIR medical informatics · 2026Article
- Explainable prediction of MDR/RR-TB in tuberculosis-diabetes mellitus multimorbidity: a machine learning model developed and validated in a dual-center study.BMC infectious diseases · 2026Article
- Comprehensive Approaches to Protein Detection and Analysis in Mycobacterium tuberculosis.Advances in experimental medicine and biology · 2026Review
- Machine learning-based lineage prediction from antimicrobial susceptibility testing phenotypes forMicrobial genomics · 2026Article
- Identification of risk factors for latent tuberculosis infection in Xinjiang using machine learning.BMC public health · 2025Article
- Unveiling meropenem resistance and co-resistance patterns in Klebsiella pneumoniae and Acinetobacter baumannii: a global genome analysis using ML/DL and association mining.BMC microbiology · 2025Article
- Reimagining Tuberculosis Control in the Era of Genomics: The Case for Global Investment inPathogens (Basel, Switzerland) · 2025Review
- Whole-genome phenotype prediction with machine learning: open problems in bacterial genomics.Bioinformatics (Oxford, England) · 2025Article
- Predicting Drug Resistance inDiagnostics (Basel, Switzerland) · 2025Article
- Applications and prospects of artificial intelligence in the auxiliary diagnosis of pediatric pulmonary tuberculosis.Frontiers in microbiology · 2025Review
- Feature selection and aggregation for antibiotic resistance GWAS inFrontiers in microbiology · 2025Article
- Computational analyses of drug resistance mutations in katG and emb complexes in Mycobacterium tuberculosis.Proteins · 2025Article
- Machine learning-based prediction of antibiotic resistance in Mycobacterium tuberculosis clinical isolates from Uganda.BMC infectious diseases · 2024Article
- Leveraging large-scale Mycobacterium tuberculosis whole genome sequence data to characterise drug-resistant mutations using machine learning and statistical approaches.Scientific reports · 2024Article
- AI-Driven Thoracic X-ray Diagnostics: Transformative Transfer Learning for Clinical Validation in Pulmonary Radiography.Journal of personalized medicine · 2024Article
- Quantitative drug susceptibility testing for Mycobacterium tuberculosis using unassembled sequencing data and machine learning.PLoS computational biology · 2024Article
- Combating antimicrobial resistance in malaria, HIV and tuberculosis.Nature reviews. Drug discovery · 2024Review
- Tackling the Antimicrobial Resistance "Pandemic" with Machine Learning Tools: A Summary of Available Evidence.Microorganisms · 2024Review
- Prediction of pyrazinamide resistance inJAC-antimicrobial resistance · 2024Article
- Assessing computational predictions of antimicrobial resistance phenotypes from microbial genomes.Briefings in bioinformatics · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 3 institutions in 3 countries.
Funding
Abstract
PubMed holds no abstract for this paper.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.