Evidence map›Paper›PMID 33795205›Full record

ArticleJournal of geriatric oncology2021

An introduction to machine learning for clinicians: How can machine learning augment knowledge in geriatric oncology?

Erika Ramsdale, Eric Snyder, Eva Culakova, Huiwen Xu, Adam Dziorny, Shuhan Yang, Martin Zand, Ajay Anand

Abstract read
In one paragraph

Article in Journal of geriatric oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Trial
  2. Trial
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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

8 authors.

Erika RamsdaleJames P. Wilmot Cancer Center, University of Rochester Medical Center, NY, USA. Electronic address: erika_ramsdale@urmc.rochester.edu.
Eric SnyderJames P. Wilmot Cancer Center, University of Rochester Medical Center, NY, USA.
Eva CulakovaJames P. Wilmot Cancer Center, University of Rochester Medical Center, NY, USA.
Huiwen XuJames P. Wilmot Cancer Center, University of Rochester Medical Center, NY, USA; Department of Surgery, Cancer Control, University of Rochester Medical Center, NY, USA.
Adam DziornyDepartment of Pediatrics, University of Rochester, NY, USA.
Shuhan YangJames P. Wilmot Cancer Center, University of Rochester Medical Center, NY, USA.
Martin ZandClinical and Translational Science Institute, University of Rochester Medical Center, NY, USA.
Ajay AnandGoergen Institute for Data Science, University of Rochester, NY, USA.

Funding

URCC NCORP Research BaseUG1CA189961 · NCI · UNIVERSITY OF ROCHESTER · PI Michelle C Janelsins, KAREN M. MUSTIAN · 2014 to 2026
$67.7M
Geriatric Oncology Research Infrastructure to Improve Clinical CareR33AG059206 · NIA · BECKMAN RESEARCH INSTITUTE/CITY OF HOPE · PI WILLIAM DALE, Heidi Diana Klepin · 2020 to 2026
$5.1M
Understanding Treatment Tolerability in Older Patients with CancerU01CA233167 · NCI · UNIVERSITY OF ROCHESTER · PI MOHILE, SUPRIYA G. · 2018 to 2023
$3.5M
Reducing Chemotherapy Toxicity in Older AdultsR01CA177592 · NCI · UNIVERSITY OF ROCHESTER · PI MOHILE, SUPRIYA G. · 2013 to 2018
$3.0M
A Patient-Oriented Research Program in Geriatric OncologyK24AG056589 · NIA · UNIVERSITY OF ROCHESTER · PI Supriya G. Mohile · 2018 to 2026
$1.5M
Decreasing Polypharmacy in Older Adults with Curable CancersK08CA248721 · NCI · UNIVERSITY OF ROCHESTER · PI RAMSDALE, ERIKA E · 2020 to 2024
$1.2M
Polypharmacy, Potentially Inappropriate Medications, and Adverse Outcomes in Older Adults with Advanced Cancer Receiving ChemotherapyR03AG067977 · NIA · UNIVERSITY OF ROCHESTER · PI RAMSDALE, ERIKA E · 2020 to 2021
$308k
NCI NIH HHS K08 CA248721NCI NIH HHS R01 CA177592NCI NIH HHS U01 CA233167NCI NIH HHS UG1 CA189961NIA NIH HHS K24 AG056589NIA NIH HHS R03 AG067977NIA NIH HHS R33 AG059206
6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

Machine LearningNeoplasmsAgedHumansDecision toolsGeriatric oncologyMachine learningPredictive modelsStatistics

Identifiers

PMID33795205
PMCPMC8478967

What OpenQuestion holds

Textmetadata
LicenceTDM
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.