ArticleProceedings of machine learning research2021
Mind the Performance Gap: Examining Dataset Shift During Prospective Validation.
Article in Proceedings of machine learning research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.
What it found
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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.
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Who cites it
20 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Algorithms on the rise: a machine learning-driven survey of prostate cancer literature.Frontiers in oncology · 2025Pooled it
- The Underutilized Ocular Fundus in Emergency Departments: Current Progress and Future Prospect of Imaging and Artificial Intelligence for Patient Care.Ophthalmology science · 2026Review
- Autonomous Agents for Auditable Cardiovascular Artificial Intelligence Development.medRxiv : the preprint server for health sciences · 2026Article
- Tumor-anchored deep feature random forests for out-of-distribution detection in lung cancer segmentation.Transactions on machine learning research · 2026Article
- Predictive Modeling for Clostridioides difficile Infection: Current State of the Science, Clinical Applications, and Future Directions.Infectious disease clinics of North America · 2025Review
- Medical machine learning operations: a framework to facilitate clinical AI development and deployment in radiology.European radiology · 2025Review
- Development of Machine Learning Systems to Predict Cancer-Related Symptoms With Validation Across a Health Care System.JCO clinical cancer informatics · 2025Article
- Detecting and Remediating Harmful Data Shifts for the Responsible Deployment of Clinical AI Models.JAMA network open · 2025Article
- Guiding Clostridioides difficile Infection Prevention Efforts in a Hospital Setting With AI.JAMA network open · 2025Article
- A roadmap to implementing machine learning in healthcare: from concept to practice.Frontiers in digital health · 2025Article
- Applications of Machine Learning on Electronic Health Record Data to Combat Antibiotic Resistance.The Journal of infectious diseases · 2024Review
- Enhancing the diagnosis of functionally relevant coronary artery disease with machine learning.Nature communications · 2024Article
- Article
- Data drift in medical machine learning: implications and potential remedies.The British journal of radiology · 2023Review
- DEPLOYR: a technical framework for deploying custom real-time machine learning models into the electronic medical record.Journal of the American Medical Informatics Association : JAMIA · 2023Article
- Prospective evaluation of data-driven models to predict daily risk ofInfection control and hospital epidemiology · 2023Article
- Prediction of Postoperative Deterioration in Cardiac Surgery Patients Using Electronic Health Record and Physiologic Waveform Data.Anesthesiology · 2022Article
- Dynamic prediction of work status for workers with occupational injuries: assessing the value of longitudinal observations.Journal of the American Medical Informatics Association : JAMIA · 2022Article
- Radiotherapy Standardisation and Artificial Intelligence within the National Cancer Institute's Clinical Trials Network.Clinical oncology (Royal College of Radiologists (Great Britain)) · 2022Article
- Open questions and research gaps for monitoring and updating AI-enabled tools in clinical settings.Frontiers in digital health · 2022Article
Corrections and comments
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Authors and funding
11 authors.
Funding
Abstract
Once integrated into clinical care, patient risk stratification models may perform worse compared to their retrospective performance. To date, it is widely accepted that performance will degrade over time due to changes in care processes and patient populations. However, the extent to which this occurs is poorly understood, in part because few researchers report prospective validation performance. In this study, we compare the 2020-2021 ('20-'21) prospective performance of a patient risk stratification model for predicting healthcare-associated infections to a 2019-2020 ('19-'20) retrospective validation of the same model. We define the difference in retrospective and prospective performance as the
Identifiers
42211431PMC13213727What 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.