ReviewCell2020
How Machine Learning Will Transform Biomedicine.
Review in Cell, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 309 papers, 4 of them syntheses 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
309 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- Performance Evaluation of Deep Learning for the Detection and Segmentation of Thyroid Nodules: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2025Pooled it
- Diagnostic accuracy of machine learning for endometriosis: a systematic review and meta-analysis.Frontiers in endocrinology · 2025Pooled it
- Machine Learning for Detecting Atrial Fibrillation from ECGs: Systematic Review and Meta-Analysis.Reviews in cardiovascular medicine · 2024Pooled it
- Machine Learning and Prediction in Fetal, Infant, and Toddler Neuroimaging: A Review and Primer.Biological psychiatry · 2023Pooled it
- Prediction of Medical Disputes Between Health Care Workers and Patients in Terms of Hospital Legal Construction Using Machine Learning Techniques: Externally Validated Cross-Sectional Study.Journal of medical Internet research · 2023Trial
- Machine learning-based risk factors for acute-on-chronic liver failure in alcohol-associated liver disease.Annals of medicine · 2026Observational
- An interpretable machine learning model for early prediction of subsequent observed CRRT initiation in patients with sepsis-associated acute kidney injury.Clinical and experimental medicine · 2026Observational
- Single-cell and machine learning-based neural regulation signature for prognosis prediction and immunotherapy response in lung adenocarcinoma.Translational oncology · 2026Article
- Development of a real-world, therapeutic drug monitoring-informed model to predict teicoplanin daily dose in pediatric intensive care unit patients with bacterial infections.International journal of clinical pharmacy · 2026Article
- Development and external validation of a machine learning model for predicting postoperative hydrocephalus in 1,073 posterior fossa tumor patients.Neurosurgical review · 2026Article
- Machine learning for predicting macrophage activation syndrome in adult patients with Still's disease.Journal of translational autoimmunity · 2026Article
- STC2-mediated calcium homeostasis dysregulation in the osteosarcoma microenvironment: Insights from single-cell sequencing and machine learning.Translational oncology · 2026Article
- An interpretable machine learning model for predicting survival in pancreatic cancer via SHAP: a multicenter study.Journal of gastroenterology · 2026Article
- Development and validation of an artificial intelligence-based model for predicting teicoplanin plasma concentrations in intensive care unit patients with pulmonary infections: a retrospective study.International journal of clinical pharmacy · 2026Article
- Personalized prediction of initial valproic acid dose in children with epilepsy using machine learning techniques.International journal of clinical pharmacy · 2026Article
- Development and internal validation of a prognostic model for esophageal cancer liver metastases using the Surveillance, Epidemiology, and End Results database.Journal of thoracic disease · 2026Article
- Article
- Preoperative prediction of cervical cancer recurrence using explainable MRI radiomics: a SHAP-Guided machine learning study.Abdominal radiology (New York) · 2026Article
- Deciphering the predictors of endometrial nonbenign lesions in asymptomatic postmenopausal women via explainable machine learning.Menopause (New York, N.Y.) · 2026Article
- Ensemble Machine Learning Model for Real-Time Valproic Acid Prediction in Epilepsy Treatment.Pharmacopsychiatry · 2026Article
249 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
4 authors.
Funding
Abstract
This Perspective explores the application of machine learning toward improved diagnosis and treatment. We outline a vision for how machine learning can transform three broad areas of biomedicine: clinical diagnostics, precision treatments, and health monitoring, where the goal is to maintain health through a range of diseases and the normal aging process. For each area, early instances of successful machine learning applications are discussed, as well as opportunities and challenges for machine learning. When these challenges are met, machine learning promises a future of rigorous, outcomes-based medicine with detection, diagnosis, and treatment strategies that are continuously adapted to individual and environmental differences.
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.