ReviewClinical infectious diseases : an official publication of the Infectious Diseases Society of America2018
Machine Learning for Healthcare: On the Verge of a Major Shift in Healthcare Epidemiology.
Review in Clinical infectious diseases : an official publication of the Infectious Diseases Society of America, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07081737 (The Future of Pain Management), which is not on this map. Cited by 193 papers, 1 of them a synthesis that pooled it.
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.
The Future of Pain Management: Can Person-centred and Precision AI-Based Decision Support Enhance Interdisciplinary Rehabilitation for Chronic Pain?
Who cites it
193 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Machine Learning in Medical Emergencies: a Systematic Review and Analysis.Journal of medical systems · 2021Pooled it
- Two-year death prediction models among patients with Chagas Disease using machine learning-based methods.PLoS neglected tropical diseases · 2022Trial
- Improving random forest predictions in small datasets from two-phase sampling designs.BMC medical informatics and decision making · 2021Trial
- Operationalizing Precision Medicine in Drug Development: Predictive Biomarkers, Companion Diagnostics, and Regulatory Pathways.Clinical pharmacology and therapeutics · 2026Review
- Longitudinal Clinical and Minimally Invasive Readouts Enable Early Assessment of Disease Trajectory in Preclinical Infection Models.Pathogens (Basel, Switzerland) · 2026Article
- Artificial Intelligence in Infectious Diseases and Clinical Microbiology.Infectious diseases & clinical microbiology · 2026Review
- Artificial intelligence in emergency medicine: from algorithmic performance to real-world clinical integration - understanding the implementation gap.International journal of emergency medicine · 2026Review
- AI for Prognosis Among People Living With HIV: Protocol for a Systematic Review and Meta-Analysis.JMIR research protocols · 2026Article
- Advancing Tumor Treatment Through Artificial Intelligence and Mathematical Modeling: A Comprehensive Review.Health science reports · 2026Article
- Diagnostic performance of artificial intelligence-based imaging and liquid biopsy combined with clinical evaluation for distinguishing benign and malignant pulmonary nodules: a diagnostic network meta-analysis.International journal of surgery (London, England) · 2026Article
- Polycystic Ovary Syndrome Prediction Using Machine Learning: A Comparative Analysis of Classification Algorithms.EJIFCC · 2026Article
- Evolving Approaches to Bacterial Identification: A Review of Classical and Modern Techniques.International journal of molecular sciences · 2026Review
- Improving the Precision of Etiological Diagnosis in Bacterial Infections Using Molecular Technologies: A Comparative Analysis of Platforms, AI Integration, and Point-of-Care Deployment.International journal of molecular sciences · 2026Review
- A Risk Model Incorporating the Novel Inflammatory Biomarker CD64 for Predicting Bloodstream Infection in Suspected Cases.Antibiotics (Basel, Switzerland) · 2026Article
- Comparative performance of machine learning models in predicting childhood diarrhea: implications for public health surveillance.The Journal of the Egyptian Public Health Association · 2026Article
- Modeling Factors Associated With Diarrhea Caused by Cryptosporidium Species Using Machine Learning Methods.Journal of clinical laboratory analysis · 2026Article
- Artificial Intelligence in Adult Cardiovascular Medicine and Surgery: Real-World Deployments and Outcomes.Journal of personalized medicine · 2026Review
- Author response to Zhicheng Du's letter to the editor entitled "Comment on: from conventional scores to explainable AI: a six-method comparative framework for failure prediction in percutaneous nephrolithotomy".World journal of urology · 2026Article
- Multidimensional analysis of clinical pharmacist intervention impact on hospital length of stay in pulmonary tuberculosis: a random forest-driven retrospective study.BMC infectious diseases · 2026Article
- Baseline indices of cardiorespiratory fitness for predicting acute mountain sickness: an interpretable four-task ensemble model.Frontiers in public health · 2026Article
133 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
The increasing availability of electronic health data presents a major opportunity in healthcare for both discovery and practical applications to improve healthcare. However, for healthcare epidemiologists to best use these data, computational techniques that can handle large complex datasets are required. Machine learning (ML), the study of tools and methods for identifying patterns in data, can help. The appropriate application of ML to these data promises to transform patient risk stratification broadly in the field of medicine and especially in infectious diseases. This, in turn, could lead to targeted interventions that reduce the spread of healthcare-associated pathogens. In this review, we begin with an introduction to the basics of ML. We then move on to discuss how ML can transform healthcare epidemiology, providing examples of successful applications. Finally, we present special considerations for those healthcare epidemiologists who want to use and apply ML.
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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.