[HTML][HTML] Missing data is poorly handled and reported in prediction model studies using machine learning: a literature review
SWJ Nijman, AM Leeuwenberg, I Beekers… - Journal of clinical …, 2022 - Elsevier
Objectives Missing data is a common problem during the development, evaluation, and
implementation of prediction models. Although machine learning (ML) methods are often …
implementation of prediction models. Although machine learning (ML) methods are often …
Modelling for policy: the five principles of the Neglected Tropical Diseases Modelling Consortium
The neglected tropical diseases (NTDs) thrive mainly among the poorest populations of the
world. The World Health Organization (WHO) has set ambitious targets for eliminating much …
world. The World Health Organization (WHO) has set ambitious targets for eliminating much …
Biomarkers of AKI progression after pediatric cardiac surgery
Background As children progress to higher stages of AKI, the risk for adverse outcomes
dramatically increases. No reliable methods exist to predict AKI progression in hospitalized …
dramatically increases. No reliable methods exist to predict AKI progression in hospitalized …
Methodological issues in randomized clinical trials for prodromal Alzheimer's and Parkinson's disease
CH Aquino - Frontiers in Neurology, 2021 - frontiersin.org
Alzheimer's disease (AD) and Parkinson's disease (PD) are the first and second most
common neurodegenerative disorders, respectively. Both are proteinopathies with …
common neurodegenerative disorders, respectively. Both are proteinopathies with …
Applications of prediction models
EW Steyerberg, EW Steyerberg - Clinical prediction models: a practical …, 2019 - Springer
Applications of Prediction Models | SpringerLink Skip to main content Advertisement
SpringerLink Account Menu Find a journal Publish with us Track your research Search Cart …
SpringerLink Account Menu Find a journal Publish with us Track your research Search Cart …
Evaluating modeling and validation strategies for tooth loss
J Krois, C Graetz, B Holtfreter… - Journal of dental …, 2019 - journals.sagepub.com
Prediction models learn patterns from available data (training) and are then validated on
new data (testing). Prediction modeling is increasingly common in dental research. We …
new data (testing). Prediction modeling is increasingly common in dental research. We …
Antimicrobial prophylaxis for vesicoureteral reflux: which subgroups of children benefit the most?
Abstract Background While the Randomized Intervention for Children with Vesicoureteral
Reflux (RIVUR) trial found that long-term antimicrobial prophylaxis reduced the risk of …
Reflux (RIVUR) trial found that long-term antimicrobial prophylaxis reduced the risk of …
Evaluating biomarkers for prognostic enrichment of clinical trials
KF Kerr, J Roth, K Zhu, H Thiessen-Philbrook… - Clinical …, 2017 - journals.sagepub.com
Background/Aims: A potential use of biomarkers is to assist in prognostic enrichment of
clinical trials, where only patients at relatively higher risk for an outcome of interest are …
clinical trials, where only patients at relatively higher risk for an outcome of interest are …
An ontology-based documentation of data discovery and integration process in cancer outcomes research
Background To reduce cancer mortality and improve cancer outcomes, it is critical to
understand the various cancer risk factors (RFs) across different domains (eg, genetic …
understand the various cancer risk factors (RFs) across different domains (eg, genetic …
[HTML][HTML] Methodological issues in current practice may lead to bias in the development of biomarker combinations for predicting acute kidney injury
Individual biomarkers of renal injury are only modestly predictive of acute kidney injury (AKI).
Using multiple biomarkers has the potential to improve predictive capacity. In this systematic …
Using multiple biomarkers has the potential to improve predictive capacity. In this systematic …