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Paper Citation Record · LEDGER

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance

As of 17 August 2026, this Paper Citation Record lists 100 of 159 outbound references and 1 inbound Pith citation observation for arXiv:2412.10288.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2412.10288 v1

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measured 100 of 159 reference resolution

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Pith citing papers itemized under the disclosed page cap.

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Reference resolution

100 of 159 outbound references displayed

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Outbound references

Observation 8c7803c6-60e2-4282-8bb0-e77c2ddf5fe0 · outbound

This paper cites Clinical prediction models: diagnosis versus prognosis.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance Clinical prediction models: diagnosis versus prognosis

Reference 1

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This paper cites Risk factors for a permanent stoma after resection of left-sided obstructive colon cancer - A prediction model.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance Risk factors for a permanent stoma after resection of left-sided obstructive colon cancer - A prediction model

Reference 2

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This paper cites Deep learning of electrocardiograms in sinus rhythm from US veterans to predict atrial fibrillation.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance Deep learning of electrocardiograms in sinus rhythm from US veterans to predict atrial fibrillation

Reference 3

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This paper cites The measurement of performance in probabilistic diagnosis.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance The measurement of performance in probabilistic diagnosis

Reference 4

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This paper cites The measurement of performance in probabilistic diagnosis.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance The measurement of performance in probabilistic diagnosis

Reference 5

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This paper cites The measurement of performance in probabilistic diagnosis.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance The measurement of performance in probabilistic diagnosis

Reference 6

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Performance evaluation of predictive AI models to support medical decisions: Overview and guidance An experimental comparison of performance measures for classification

Reference 7

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This paper cites Assessing the performance of prediction models: a framework for traditional and novel measures.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance Assessing the performance of prediction models: a framework for traditional and novel measures

Reference 8

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This paper cites Metrics reloaded: Recommendations for image analysis validation.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance Metrics reloaded: Recommendations for image analysis validation

Reference 9

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Performance evaluation of predictive AI models to support medical decisions: Overview and guidance Assessing the performance of classification methods

Reference 10

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This paper cites A unified view of performance metrics: translating threshold choice of into expected classification loss.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance A unified view of performance metrics: translating threshold choice of into expected classification loss

Reference 11

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This paper cites Evaluation of Sepsis Prediction Models before Onset of Treatment.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance Evaluation of Sepsis Prediction Models before Onset of Treatment

Reference 12

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This paper cites Evaluation of clinical prediction models (part 1): from development to external validation.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance Evaluation of clinical prediction models (part 1): from development to external validation

Reference 13

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Performance evaluation of predictive AI models to support medical decisions: Overview and guidance Perspectives on validation of clinical predictive algorithms

Reference 14

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This paper cites Evaluation of clinical prediction models (part 2): how to undertake an external validation study.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance Evaluation of clinical prediction models (part 2): how to undertake an external validation study

Reference 15

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Performance evaluation of predictive AI models to support medical decisions: Overview and guidance Targeted validation: validating clinical prediction models in their intended population and setting

Reference 16

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Performance evaluation of predictive AI models to support medical decisions: Overview and guidance Unresolved cited work

Reference 17

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This paper cites Comparison of the ADNEX and ROMA risk prediction models for the diagnosis of ovarian cancer: a multicentre external validation in patients who underwent surgery.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance Comparison of the ADNEX and ROMA risk prediction models for the diagnosis of ovarian cancer: a multicentre external validation in patients who underwent surgery

Reference 18

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Performance evaluation of predictive AI models to support medical decisions: Overview and guidance External correspondence: Decompositions of the mean probability score

Reference 19

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Performance evaluation of predictive AI models to support medical decisions: Overview and guidance Discrimination slope and integrated discrimination improvement - properties, relationships and impact of calibration

Reference 20

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Performance evaluation of predictive AI models to support medical decisions: Overview and guidance Therapeutic decision making: a cost-benefit analysis

Reference 21

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Performance evaluation of predictive AI models to support medical decisions: Overview and guidance The foundations of cost-sensitive learning

Reference 22

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Performance evaluation of predictive AI models to support medical decisions: Overview and guidance Three myths about risk thresholds for prediction models

Reference 23

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Performance evaluation of predictive AI models to support medical decisions: Overview and guidance Decision Curve Analysis: A Novel Method for Evaluating Prediction Models

Reference 24

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Performance evaluation of predictive AI models to support medical decisions: Overview and guidance An improved measure for comparing diagnostic tests

Reference 25

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Performance evaluation of predictive AI models to support medical decisions: Overview and guidance ESGO/ISUOG/IOTA/ESGE consensus statement on preoperative diagnosis of ovarian tumors

Reference 26

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Performance evaluation of predictive AI models to support medical decisions: Overview and guidance A simple, step-by-step guide to interpreting decision curve analysis

Reference 27

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Performance evaluation of predictive AI models to support medical decisions: Overview and guidance Piloting a new method to estimate action thresholds in medicine through intuitive weighing

Reference 28

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Performance evaluation of predictive AI models to support medical decisions: Overview and guidance Using relative utility curves to evaluate risk prediction

Reference 29

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Performance evaluation of predictive AI models to support medical decisions: Overview and guidance Assessing the net benefit of machine learning models in the presence of resource constraints

Reference 30

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Performance evaluation of predictive AI models to support medical decisions: Overview and guidance good-looking

Reference 31

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Performance evaluation of predictive AI models to support medical decisions: Overview and guidance A simulation study of preditive ability measures in a survival model I: explained variation measures

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Performance evaluation of predictive AI models to support medical decisions: Overview and guidance Loss Functions for Binary Class Probability Estimation and Classification: Structure and Applications

Reference 33

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Performance evaluation of predictive AI models to support medical decisions: Overview and guidance Strictly proper scoring rules, prediction, and estimation

Reference 34

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Performance evaluation of predictive AI models to support medical decisions: Overview and guidance A note on the evaluation of novel biomarkers: do not rely on integrated discrimination improvement and net reclassification index

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Performance evaluation of predictive AI models to support medical decisions: Overview and guidance Novel Decompositions of Proper Scoring Rules for Classification: Score Adjustment as Precursor to Calibration

Reference 36

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Performance evaluation of predictive AI models to support medical decisions: Overview and guidance Assessing diagnostic tests by a strictly proper scoring rule

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Performance evaluation of predictive AI models to support medical decisions: Overview and guidance Caveats and pitfalls of ROC analysis in clinical microarray research (and how to avoid them)

Reference 38

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This paper cites Confidence intervals for an effect size measure based on the Mann-Whitney statistic.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance Confidence intervals for an effect size measure based on the Mann-Whitney statistic

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Observation 5fc73c2f-5c2c-405f-96dd-df1cd1b0a320 · outbound

This paper cites The use of the area under the ROC curve in the evaluation of machine learning algorithms.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance The use of the area under the ROC curve in the evaluation of machine learning algorithms

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Observation 3fe5e42f-935f-4602-978f-c9f586d52c97 · outbound

This paper cites ROC curves for clinical prediction models part 1.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance ROC curves for clinical prediction models part 1

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Observation 4718fc48-e5b1-453c-9aa5-18c8ce4c3bf4 · outbound

This paper cites The use of receiver operating characteristic curves in biomedical informatics.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance The use of receiver operating characteristic curves in biomedical informatics

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Observation 8f22eebd-4041-45d3-9247-934792e1895a · outbound

This paper cites Learning from Imbalanced Data Sets.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance Learning from Imbalanced Data Sets

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Observation cec364db-c064-4cd7-bd5d-72a463dace4b · outbound

This paper cites Improving the practice of classifier performance assessment.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance Improving the practice of classifier performance assessment

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Observation adf7e668-00a6-49e6-a8cb-478667000c4f · outbound

This paper cites The precision-recall plot is more informative than the ROC plot when evaluating binary classifiers on imbalanced datasets.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance The precision-recall plot is more informative than the ROC plot when evaluating binary classifiers on imbalanced datasets

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Observation 5522fdf2-74fa-4069-adcc-29e4d9e3d99c · outbound

This paper cites A new concordant partial AUC and partial c statistic for imbalanced data in the evaluation of machine learning algorithms.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance A new concordant partial AUC and partial c statistic for imbalanced data in the evaluation of machine learning algorithms

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Observation 7c16b8aa-c6d9-4c94-805b-9008e3bfc562 · outbound

This paper cites AUC: a misleading measure of the performance of predictive distribution models.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance AUC: a misleading measure of the performance of predictive distribution models

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Observation 794dde0a-84e3-4228-813c-979dbcecda60 · outbound

This paper cites The relationship between precision-recall and ROC curves.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance The relationship between precision-recall and ROC curves

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Observation ca6a2c09-c328-4612-b90f-8938e91fd14e · outbound

This paper cites A Closer Look at AUROC and AUPRC under Class Imbalance.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance A Closer Look at AUROC and AUPRC under Class Imbalance

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Observation ec0f2409-85ac-4e8c-a3ea-13426cc375a1 · outbound

This paper cites Interpreting area under the receiver operating characteristic curve.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance Interpreting area under the receiver operating characteristic curve

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Observation 017bcdda-bc95-4430-b20d-cd8c0505e12f · outbound

This paper cites The precision-recall curve overcame the optimism of the receiver operating characteristic curve in rare diseases.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance The precision-recall curve overcame the optimism of the receiver operating characteristic curve in rare diseases

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Observation ee12a17c-2bab-4934-9fd3-f6779deca611 · outbound

This paper cites Area under the precision-recall curve: point estimates and confidence intervals.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance Area under the precision-recall curve: point estimates and confidence intervals

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Observation 381f9688-8adc-4792-aac8-2c2859830cf7 · outbound

This paper cites Partial AUC estimation and regression.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance Partial AUC estimation and regression

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Observation 7693bbcc-d320-43cf-8fb7-533e23fa66aa · outbound

This paper cites an unresolved cited work.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance Unresolved cited work

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Observation b8344df8-19a5-4f51-bcd9-4391cc00f3c5 · outbound

This paper cites A calibration hierarchy for risk models was defined: from utopia to empirical data.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance A calibration hierarchy for risk models was defined: from utopia to empirical data

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Observation 015b765b-0966-4e94-8e88-0da790578f2e · outbound

This paper cites calibration slope.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance calibration slope

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Observation e0506b91-42e8-4776-bdb9-307411c6a3e7 · outbound

This paper cites Two further applications of a model for binary regression.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance Two further applications of a model for binary regression

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Observation 1ee9b328-24cd-4ae2-8f19-d051346e0449 · outbound

This paper cites Predicting good probabilities with supervised learning.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance Predicting good probabilities with supervised learning

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Observation 1a520f31-8908-4cbc-9a93-3c8ed7fd35cb · outbound

This paper cites Graphical assessment of internal and external calibration of logistic regression models by using loess smoothers.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance Graphical assessment of internal and external calibration of logistic regression models by using loess smoothers

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Observation 0287047f-e61e-43c4-a3af-12b06d73e846 · outbound

This paper cites Calibration: the Achilles heel of predictive analytics.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance Calibration: the Achilles heel of predictive analytics

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Observation b93cfefa-7b6c-4818-b424-64bacac13b5a · outbound

This paper cites A new calibration test and a reappraisal of the calibration belt for the assessment of prediction models based on dichotomous outcomes.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance A new calibration test and a reappraisal of the calibration belt for the assessment of prediction models based on dichotomous outcomes

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Observation 25c96935-050c-4d30-ac95-2bae6f9a8fb8 · outbound

This paper cites Smooth ECE: Principled Reliability Diagrams via Kernel Smoothing.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance Smooth ECE: Principled Reliability Diagrams via Kernel Smoothing

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Observation 0e9311ad-4103-4320-99eb-4c3950ab2535 · outbound

This paper cites Obtaining Well Calibrated Probabilities Using Bayesian Binning.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance Obtaining Well Calibrated Probabilities Using Bayesian Binning

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Observation 79feba05-7a01-4d2a-9161-d609afd9a7b1 · outbound

This paper cites Risk prediction models for discrete ordinal outcomes: calibration and the impact of the proportional odds assumption.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance Risk prediction models for discrete ordinal outcomes: calibration and the impact of the proportional odds assumption

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Observation 7c207a6c-8756-433e-8ee9-bebc1652075a · outbound

This paper cites A spline-based tool to assess and visualize calibration of multiclass risk predictions.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance A spline-based tool to assess and visualize calibration of multiclass risk predictions

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Observation c59a4982-ddea-4f0e-95ce-8295f987b083 · outbound

This paper cites The integrated calibration index (ICI) and related metrics for quantifying the calibration of logistic regression models.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance The integrated calibration index (ICI) and related metrics for quantifying the calibration of logistic regression models

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Observation 28b09346-97f0-4190-bdba-6edbe1759470 · outbound

This paper cites Metrics of calibration for probabilistic predictions.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance Metrics of calibration for probabilistic predictions

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Observation a4a09ee2-c743-4208-82ee-9b94e6b5b238 · outbound

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Performance evaluation of predictive AI models to support medical decisions: Overview and guidance Non-parametric inference on calibration of predicted risks

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Observation bef8da73-1116-4d79-b573-41659b3e0144 · outbound

This paper cites A comparison of goodness-of-fit tests for the logistic regression model.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance A comparison of goodness-of-fit tests for the logistic regression model

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Observation 7a066693-351b-4967-9ccd-07fb1ab17e3d · outbound

This paper cites Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD).

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD)

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Observation 941a09ff-c416-4858-b073-3e490d70654e · outbound

This paper cites Assessing the goodness of fit of logistic regression models in large samples: A modification of the Hosmer-Lemeshow test.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance Assessing the goodness of fit of logistic regression models in large samples: A modification of the Hosmer-Lemeshow test

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Observation cf7bed6e-7b4b-4868-beca-63a9c6a7095d · outbound

This paper cites Calibration tests in multi-class classification: A unifying framework.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance Calibration tests in multi-class classification: A unifying framework

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Observation 83946c74-1e00-4516-aec4-12c504ad0990 · outbound

This paper cites A translational perspective towards clinical AI fairness.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance A translational perspective towards clinical AI fairness

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Observation b84b9956-7d19-4d2f-8a10-f2de26c92571 · outbound

This paper cites Beyond calibration: estimating the grouping loss of modern neural networks.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance Beyond calibration: estimating the grouping loss of modern neural networks

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Observation 0eb75c3b-c99f-477f-ac18-0b040efbecc4 · outbound

This paper cites Aleatoric and epistemic uncertainty in machine learning: an introduction to concepts and methods.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance Aleatoric and epistemic uncertainty in machine learning: an introduction to concepts and methods

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Observation 1eab0357-1232-4af3-b28e-ca2a9a2d28b9 · outbound

This paper cites Pattern Recognition and Machine Learning.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance Pattern Recognition and Machine Learning

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Observation 4755c653-6221-4a4c-b25f-6c32bb551e91 · outbound

This paper cites Probability for machine learning: discover how to harness uncertainty with Python.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance Probability for machine learning: discover how to harness uncertainty with Python

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Observation 2829f8a1-ab25-40cf-8e0b-18dba3f38e6c · outbound

This paper cites Verification of forecasts expressed in terms of probability.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance Verification of forecasts expressed in terms of probability

Reference 78

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Observation 2060f452-9c62-4aa6-9899-4c6c2dea8ea9 · outbound

This paper cites Statistical Methods in the Atmospheric Sciences.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance Statistical Methods in the Atmospheric Sciences

Reference 79

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Observation a1c58ba0-ac3e-4372-9a1f-5a600b460fdc · outbound

This paper cites The index of prediction accuracy: an intuitive measure useful for evaluating risk prediction models.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance The index of prediction accuracy: an intuitive measure useful for evaluating risk prediction models

Reference 80

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Observation b9ff46d5-72d0-407a-a81d-e3f5309ea289 · outbound

This paper cites Explained variation for logistic regression.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance Explained variation for logistic regression

Reference 81

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Observation d7ebc1a8-cc62-400d-9acd-9399361b885c · outbound

This paper cites Coefficients of determination for multiple logistic regression analysis.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance Coefficients of determination for multiple logistic regression analysis

Reference 82

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Observation 766ab44f-9bef-4213-b503-bf196107c364 · outbound

This paper cites Properties of R2 statistics for logistic regression.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance Properties of R2 statistics for logistic regression

Reference 83

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Observation 3b0de786-1154-47a2-963c-eb3bd27f24d0 · outbound

This paper cites A note on a general definition of the coefficient of determination.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance A note on a general definition of the coefficient of determination

Reference 84

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Observation d7876d6c-d2f1-4caa-8c11-320ee8edc832 · outbound

This paper cites Coefficients of determination in logistic regression models – a new proposal: the coefficient of discrimination.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance Coefficients of determination in logistic regression models – a new proposal: the coefficient of discrimination

Reference 85

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Observation b3c9dc2a-04a6-4c28-a109-1d6c83ddd213 · outbound

This paper cites Modifying ROC curves to incorporate predicted probabilities.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance Modifying ROC curves to incorporate predicted probabilities

Reference 86

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Observation c1cc3334-0bdd-441c-93a7-4b92d33229f0 · outbound

This paper cites Dynamic prediction in clinical survival analysis.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance Dynamic prediction in clinical survival analysis

Reference 87

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Observation 82b8c70d-ffa0-447f-b148-0db41aa99bc3 · outbound

This paper cites Evaluating machine learning models and their diagnostic value.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance Evaluating machine learning models and their diagnostic value

Reference 88

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Observation aca07956-3395-456b-a5d6-bf62ac81b5af · outbound

This paper cites Index for rating diagnostic tests.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance Index for rating diagnostic tests

Reference 89

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Observation 097c92da-7ffb-4e73-826d-f99e328c9bc2 · outbound

This paper cites The balanced accuracy and its posterior distribution.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance The balanced accuracy and its posterior distribution

Reference 90

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Observation 28b1f41b-a5fc-45c6-9159-319b47f26f4a · outbound

This paper cites A coefficient of agreement for nominal scales.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance A coefficient of agreement for nominal scales

Reference 91

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Observation 5f74c1d8-b27f-4b6b-bbe0-48b16bb40d71 · outbound

This paper cites Information Retrieval.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance Information Retrieval

Reference 92

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Observation 847b34ce-e9f2-469d-b06d-b2c05c457179 · outbound

This paper cites The advantages of the Matthews correlation coefficient (MCC) over F1 score and accuracy in binary classification evaluation.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance The advantages of the Matthews correlation coefficient (MCC) over F1 score and accuracy in binary classification evaluation

Reference 93

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Observation 2716ace8-e08c-443a-a35d-fb5db2e97e25 · outbound

This paper cites A Review of the F-Measure: Its History, Properties, Criticism, and Alternatives.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance A Review of the F-Measure: Its History, Properties, Criticism, and Alternatives

Reference 94

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Observation 3616dc6f-2254-4024-91cf-82cad7211a80 · outbound

This paper cites Assessing the accuracy of prediction algorithms for classification: an overview.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance Assessing the accuracy of prediction algorithms for classification: an overview

Reference 95

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Observation 3bda14c0-1458-4d03-8eb4-e03b7e04f94f · outbound

This paper cites The Matthews correlation coefficient (MCC) is more reliable than balanced accuracy, bookmaker informedness, and markedness in two-class confusion matrix evaluation.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance The Matthews correlation coefficient (MCC) is more reliable than balanced accuracy, bookmaker informedness, and markedness in two-class confusion matrix evaluation

Reference 96

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 97577c92-2024-4f2b-913f-6e9762faceb9 · outbound

This paper cites Decision-making in health and medicine: integrating evidence and Values.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance Decision-making in health and medicine: integrating evidence and Values

Reference 97

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation bddb6033-fc46-4049-ab17-99a719ac8eeb · outbound

This paper cites Net benefit approaches to the evaluation of prediction models, molecular markers, and diagnostic tests.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance Net benefit approaches to the evaluation of prediction models, molecular markers, and diagnostic tests

Reference 98

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Observation 9453c78e-1fd3-47f1-b67c-6f836c90fb39 · outbound

This paper cites Assessing the clinical impact of risk models for opting out of treatment.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance Assessing the clinical impact of risk models for opting out of treatment

Reference 99

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Observation 534879fe-9ed7-4dc9-b384-8c21f37c4a04 · outbound

This paper cites Calibration of risk prediction models: impact on decision-analytic performance.

Performance evaluation of predictive AI models to support medical decisions: Overview and guidance Calibration of risk prediction models: impact on decision-analytic performance

Reference 100

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Pith citing papers

Observation a0d2bc53-3e74-4042-8a61-fc43d860414a · inbound

Critical Appraisal of Fairness Metrics in Clinical Predictive AI cites this paper.

Critical Appraisal of Fairness Metrics in Clinical Predictive AI Performance evaluation of predictive AI models to support medical decisions: Overview and guidance

Reference 13

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local_arxiv, observed 2026-08-06T23:35:07.545487Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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