ArticleNPJ digital medicine2020
Developing a delivery science for artificial intelligence in healthcare.
Article in NPJ digital medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 79 papers, 3 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
79 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Transforming liver transplant allocation with artificial intelligence and machine learning: a systematic review.BMC medical informatics and decision making · 2025Pooled it
- Implementation of Machine Learning Applications in Health Care Organizations: Systematic Review of Empirical Studies.Journal of medical Internet research · 2024Pooled it
- Inclusion of Clinicians in the Development and Evaluation of Clinical Artificial Intelligence Tools: A Systematic Literature Review.Frontiers in psychology · 2022Pooled it
- Risk Stratification for Diabetic Retinopathy Screening Order Using Deep Learning: A Multicenter Prospective Study.Translational vision science & technology · 2023Trial
- Evaluation of domain generalization and adaptation on improving model robustness to temporal dataset shift in clinical medicine.Scientific reports · 2022Trial
- From Bench to Bedside: The Path Toward Real-World Translation for Artificial Intelligence in Pancreatic Cancer Detection.Korean journal of radiology · 2026Review
- Prospective validation and real-time implementation of an automated machine learning postoperative mortality prediction model.British journal of anaesthesia · 2026Article
- Acceptable accuracy for medical AI: a survey of physicians and the general population in Sweden.BMJ health & care informatics · 2026Article
- From Artificial Intelligence to Robotics: How to Navigate Technological Innovation in Radiology With the Gartner Hype Cycle.Academic radiology · 2026Review
- Early Prediction of Delirium in Postcardiac Surgery Patients: Machine Learning Model Development and External Validation.JMIR medical informatics · 2026Article
- A framework for using AI to drive care model transformation: building cars rather than faster horses.npj health systems · 2026Article
- Impediments to transforming the healthcare delivery system: shifting the paradigm from provider centric to patient centric.Frontiers in health services · 2026Article
- A roadmap for artificial intelligence in pain medicine: current status, opportunities, and requirements.Current opinion in anaesthesiology · 2025Review
- Use of artificial intelligence in neurological disorders diagnosis: A scientometric study.World journal of methodology · 2025Article
- Transforming beef quality through healthy breeding: a strategy to reduce carcinogenic compounds and enhance human health: a review.Mammalian genome : official journal of the International Mammalian Genome Society · 2025Review
- Bridging the Regulatory Divide: A Dual-Pathway Framework Using SRA Approvals and AI Evaluation to Ensure Drug Quality in Developing Countries.Pharmaceuticals (Basel, Switzerland) · 2025Review
- Diagnostic framework to validate clinical machine learning models locally on temporally stamped data.Communications medicine · 2025Article
- AI-Assisted vs Unassisted Identification of Prostate Cancer in Magnetic Resonance Images.JAMA network open · 2025Article
- An analytic research and review of the literature on practice of artificial intelligence in healthcare.European journal of medical research · 2025Review
- Implementing a transmural model of early palliative care in advanced dementia: the use of a hybrid effectiveness-implementation study design.BMC geriatrics · 2025Article
19 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
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial Intelligence (AI) has generated a large amount of excitement in healthcare, mostly driven by the emergence of increasingly accurate machine learning models. However, the promise of AI delivering scalable and sustained value for patient care in the real world setting has yet to be realized. In order to safely and effectively bring AI into use in healthcare, there needs to be a concerted effort around not just the creation, but also the delivery of AI. This AI "delivery science" will require a broader set of tools, such as design thinking, process improvement, and implementation science, as well as a broader definition of what AI will look like in practice, which includes not just machine learning models and their predictions, but also the new systems for care delivery that they enable. The careful design, implementation, and evaluation of these AI enabled systems will be important in the effort to understand how AI can improve healthcare.
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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.