ArticleBiomedicines2023
Sample Size Analysis for Machine Learning Clinical Validation Studies.
Article in Biomedicines, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 35 papers.
What it found
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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.
Data-driven Clustering in Hemorrhoid Surgery: Retrospective Monocentric Study for the Identification of Clinical Phenotypes
CArdiovascular Risk Assessment Via Multimodal Data Analysis Enabling Personalised Prevention Strategies Targeting MEnopausaL Women - Observational Study
Who cites it
35 citing papers in PubMed.
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- Machine Learning-Based Predictive Model for Functional Independence in Spinal Cord Injury: Protocol for a Predictive Rule Development and Validation Study.JMIR research protocols · 2026Article
- Explainable Lightweight AI for the Identification of Right-Sided Cardiac Dysfunction in a Saudi Arabian Diabetic Cohort.Journal of clinical medicine · 2026Article
- Sample size calculation for training ensemble machine learning models on health data.Patterns (New York, N.Y.) · 2026Article
- Article
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- Identification of key factors for early detection of rheumatoid arthritis in primary care using machine learning.Scientific reports · 2026Article
- Building Hybrid Pharmacometric-Machine Learning Models in Oncology Drug Development: Current State and Recommendations.CPT: pharmacometrics & systems pharmacology · 2026Review
- Identifying key determinants of cumulative live birth in women with ovarian endometrioma undergoing ethanol sclerotherapy followed byFrontiers in cell and developmental biology · 2026Article
- AI-Based Severity Classification of Dementia Using Gait Analysis.Sensors (Basel, Switzerland) · 2025Article
- Explainable radiomics based on association of histopathological cell density and multiparametric MR radiomic features for high-risk stratification of prostate cancer patients.Magma (New York, N.Y.) · 2025Article
- Construction of a transfer learning-based depression detection model for female breast cancer patients: text sentiment analysis.BMC cancer · 2025Article
- Sleep disturbances predict nine-year panic disorder chronicity: The sleep-panic nexus theory with machine learning insights.Journal of anxiety disorders · 2025Article
- A computed tomography-based deep learning model for non-invasively predicting World Health Organization (WHO)/International Society of Urological Pathology (ISUP) pathological grades of clear cell renal cell carcinoma (ccRCC): a multicenter cohort study.Translational andrology and urology · 2025Article
- How to use learning curves to evaluate the sample size for malaria prediction models developed using machine learning algorithms.Malaria journal · 2025Article
- Anthropometric Measurements for Predicting Low Appendicular Lean Mass Index for the Diagnosis of Sarcopenia: A Machine Learning Model.Journal of functional morphology and kinesiology · 2025Article
- Predicting Cognitive Outcome Through Nutrition and Health Markers Using Supervised Machine Learning.The Journal of nutrition · 2025Article
- Machine Learning-Based Mobile Application for Predicting Posterior Canal Benign Paroxysmal Positional Vertigo.Laryngoscope investigative otolaryngology · 2025Article
- Prediction of Snacking Behavior Involving Snacks Having High Levels of Saturated Fats, Salt, or Sugar Using Only Information on Previous Instances of Snacking: Survey- and App-Based Study.JMIR medical informatics · 2025Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
backgroundBefore integrating new machine learning (ML) into clinical practice, algorithms must undergo validation. Validation studies require sample size estimates. Unlike hypothesis testing studies seeking a
methodsOur open-source method, Sample Size Analysis for Machine Learning (SSAML) was described and was tested in three previously published models: brain age to predict mortality (Cox Proportional Hazard), COVID hospitalization risk prediction (ordinal regression), and seizure risk forecasting (deep learning).
resultsMinimum sample sizes were obtained in each dataset using standardized criteria. DISCUSSION: SSAML provides a formal expectation of precision and accuracy at a desired confidence level. SSAML is open-source and agnostic to data type and ML model. It can be used for clinical validation studies of ML models.
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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.