Evidence map›Paper›PMID 22211175›Full record

ArticleAMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science2011

Smooth isotonic regression: a new method to calibrate predictive models.

Xiaoqian Jiang, Melanie Osl, Jihoon Kim, Lucila Ohno-Machado

Abstract read
In one paragraph

Article in AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

18 citing papers in PubMed.

  1. Improved risk prediction via cross-domain calibration in a retrospective case-control study.The Canadian journal of statistics = Revue canadienne de statistique · 2026
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  14. A tutorial on calibration measurements and calibration models for clinical prediction models.Journal of the American Medical Informatics Association : JAMIA · 2020
    Review
  15. I-spline Smoothing for Calibrating Predictive Models.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2012
    Article
  16. Article
  17. Isotonic Regression Based-Method in Quantitative High-Throughput Screenings for Genotoxicity.Dose-response : a publication of International Hormesis Society
    Article
  18. iDASH: integrating data for analysis, anonymization, and sharing.Journal of the American Medical Informatics Association : JAMIA
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Xiaoqian JiangDivision of Biomedical Informatics, Department of Medicine University of California, San Diego.
Melanie Osl
Jihoon Kim
Lucila Ohno-Machado

Funding

iDASH: Integrating Data for Analysis, Anonymization, and SharingU54HL108460 · NHLBI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI OHNO-MACHADO, LUCILA · 2010 to 2015
$19.1M
SCANNER: Scalable National Network for Effectiveness ResearchR01HS019913 · AHRQ · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI OHNO-MACHADO, LUCILA · 2010 to 2010
$8.3M
Assessing quality of individual predictions in medical decision support systemsR01LM009520 · NLM · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI OHNO-MACHADO, LUCILA · 2007 to 2010
$1.4M
AHRQ HHS R01 HS019913NHLBI NIH HHS U54 HL108460NLM NIH HHS R01 LM009520
6 · The paper itself

Abstract

Predictive models are critical for risk adjustment in clinical research. Evaluation of supervised learning models often focuses on predictive model discrimination, sometimes neglecting the assessment of their calibration. Recent research in machine learning has shown the benefits of calibrating predictive models, which becomes especially important when probability estimates are used for clinical decision making. By extending the isotonic regression method for recalibration to obtain a smoother fit in reliability diagrams, we introduce a novel method that combines parametric and non-parametric approaches. The method calibrates probabilistic outputs smoothly and shows better generalization ability than its ancestors in simulated as well as real world biomedical data sets.

Identifiers

PMID22211175
PMCPMC3248752

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.