ReviewJournal of healthcare informatics research2022
Conformal Prediction in Clinical Medical Sciences.
Review in Journal of healthcare informatics research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 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
21 citing papers in PubMed.
- Longitudinal Digital Phenotyping of Traditional Chinese Medicine Constitution From Routine Health Examination Records: Retrospective Clinical Informatics Study.JMIR medical informatics · 2026Article
- Perforator-Aware Explainable Microsurgical Intelligence for Basilar Trunk Aneurysm Reconstruction: A Human-Centred Clinical AI Framework for Precision Neurovascular Surgery-A Retrospective Single-Centre Study.Journal of clinical medicine · 2026Article
- Toward universal representations of the living: Physiological invariance for transportable medical AI.PLOS digital health · 2026Review
- Reliable Uncertainty Under Class Imbalance and Distribution Shift: Class-Conditional Conformal Prediction of Multiple Sclerosis.medRxiv : the preprint server for health sciences · 2026Article
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- Article
- Integrating conformal prediction with machine learning for uncertainty-aware risk stratification in coronary artery disease.Frontiers in cardiovascular medicine · 2026Article
- Novel nested conformal prediction analysis to unravel complexity in patient subtyping.Frontiers in artificial intelligence · 2026Article
- Deep Conformal Supervision: Leveraging Intermediate Features for Robust Uncertainty Quantification.Journal of imaging informatics in medicine · 2025Article
- Uncertainty-Aware Deep Learning Characterization of Knee Radiographs for Large-Scale Registry Creation.The Journal of arthroplasty · 2025Article
- Error Reduction in Leukemia Machine Learning Classification With Conformal Prediction.JCO clinical cancer informatics · 2025Article
- Enhancing prediction of primary site recurrence in head and neck cancer using radiomics and uncertainty estimation.Frontiers in artificial intelligence · 2025Article
- Reliable machine learning models in genomic medicine using conformal prediction.Frontiers in bioinformatics · 2025Review
- Uncertainty Quantification and Flagging of Unreliable Predictions in Predicting Mass Spectrometry-Related Properties of Small Molecules Using Machine Learning.International journal of molecular sciences · 2024Article
- Artificial intelligence uncertainty quantification in radiotherapy applications - A scoping review.Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology · 2024Article
- Recommendations to promote fairness and inclusion in biomedical AI research and clinical use.Journal of biomedical informatics · 2024Article
- Reliable anti-cancer drug sensitivity prediction and prioritization.Scientific reports · 2024Article
- Artificial Intelligence Uncertainty Quantification in Radiotherapy Applications - A Scoping Review.medRxiv : the preprint server for health sciences · 2024Article
- A Novel Dual Layer Cascade Reliability Framework for an Informed and Intuitive Clinician-AI Interaction In Diagnosis of Colorectal Cancer Polyps.IEEE journal of biomedical and health informatics · 2024Article
- The IHI Rochester Report 2022 on Healthcare Informatics Research: Resuming After the CoViD-19.Journal of healthcare informatics research · 2023Article
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 use of machine learning (ML) and artificial intelligence (AI) applications in medicine has attracted a great deal of attention in the medical literature, but little is known about how to use Conformal Predictions (CP) to assess the accuracy of individual predictions in clinical applications. We performed a comprehensive search in SCOPUS® to find papers reporting the use of CP in clinical applications. We identified 14 papers reporting the use of CP for clinical applications, and we briefly describe the methods and results reported in these papers. The literature reviewed shows that CP methods can be used in clinical applications to provide important insight into the accuracy of individual predictions. Unfortunately, the review also shows that most of the studies have been performed in isolation, without input from practicing clinicians, not providing comparisons among different approaches and not considering important socio-technical considerations leading to clinical adoption.
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.