Software Quality Prediction Models Compared
, 2010 Numerous empirical studies confirm that many software metrics aggregated in software quality prediction models are valid predictors for qualities of general interest like maintainability and correctness.
Gutzmann, Tobias, +2 more
core +4 more sources
Editorial: Clinical prediction models in cancer through bioinformatics [PDF]
Frontiers in BioinformaticsWenlin Yang +3 more
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Reporting of prognostic clinical prediction models based on machine learning methods in oncology needs to be improved. [PDF]
, 2021 OBJECTIVE: Evaluate the completeness of reporting of prognostic prediction models developed using machine learning methods in the field of oncology. STUDY DESIGN AND SETTING: We conducted a systematic review, searching the MEDLINE and Embase databases ...
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Guide to presenting clinical prediction models for use in clinical settings. [PDF]
, 2019 Clinical prediction models estimate the risk of existing disease or future outcome for an individual, which is conditional on the values of multiple predictors such as age, sex, and biomarkers.
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Methodological conduct of prognostic prediction models developed using machine learning in oncology: a systematic review. [PDF]
, 2022 BACKGROUND: Describe and evaluate the methodological conduct of prognostic prediction models developed using machine learning methods in oncology. METHODS: We conducted a systematic review in MEDLINE and Embase between 01/01/2019 and 05/09/2019, for ...
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Demographics and clinical features used in the prediction models.
, 2023 Demographics and clinical features used in the prediction models.
Tim Q. Duong (9179067) +2 more
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Clinical prediction models [PDF]
, 2016 Clinical prediction models (also known as prognostic models, risk scores) are mathematical equations that relate multiple predictors (risk factors, co-variates) to the probability of having a disease or condition (diagnostic) or the probability that an ...
Collins, G +7 more
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Prediction Constrained Topic Models [PDF]
, 2020 <p>Open source software for training and evaluating prediction-constrained topic models, and comparing these to baseline classification methods (such as logistic regression or ensembles of decision trees).</p> <p>Available on Github ...
Hughes, Michael C.
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Added predictive value of high-throughput molecular data to clinical data, and its validation [PDF]
, 2010 Hundreds of ''molecular signatures'' have been proposed in the literature to predict patient outcome in clinical settings from high-dimensional data, many of which eventually failed to get validated. Validation of such molecular research findings is thus
Sauerbrei, Willi, Boulesteix, Anne-Laure
core +1 more source
Incorporation bias in clinical prediction models for epilepsy [PDF]
Epilepsia OpenSem L. Kampman +4 more
doaj +2 more sources