Evidence map›Paper›PMID 36578375›Full record

ArticleMachine learning with applications2022

A fully automatic framework for evaluating cosmetic results of breast conserving therapy.

Chenqi Guo, Tamara L Smith, Qianli Feng, Fabian Benitez-Quiroz, Frank Vicini, Douglas Arthur, Julia White, Aleix Martinez

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Machine learning with applications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

8 authors.

Chenqi GuoComputational Biology and Cognitive Science Laboratory, the Ohio State University, Columbus, OH, USA.
Tamara L SmithRadiation Oncology, Memorial Healthcare System, Hollywood, FL, USA.
Qianli FengComputational Biology and Cognitive Science Laboratory, the Ohio State University, Columbus, OH, USA.
Fabian Benitez-QuirozComputational Biology and Cognitive Science Laboratory, the Ohio State University, Columbus, OH, USA.
Frank ViciniRadiation Oncology, Genesis Care Pty Ltd, Alexandria, NSW, Australia.
Douglas ArthurRadiation Oncology, Virginia Commonwealth University, Richmond, VA, USA.
Julia WhiteRadiation Oncology, the Ohio State University, Columbus, OH, USA.
Aleix MartinezComputational Biology and Cognitive Science Laboratory, the Ohio State University, Columbus, OH, USA.

Funding

NRG Oncology Network Group Operations Center - GY9 BIQSFP Reports/BudgetsU10CA180868 · NCI · NRG ONCOLOGY FOUNDATION, INC. · PI NORMAN WOLMARK · 2014 to 2026
$206.8M
Statistics CoreU10CA180822 · NCI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI James J. Dignam, GREG YOTHERS · 2014 to 2026
$146.4M
NCI NIH HHS U10 CA180822NCI NIH HHS U10 CA180868
6 · The paper itself

Abstract

The breast cosmetic outcome after breast conserving therapy is essential for evaluating breast treatment and determining patient's remedy selection. This prompts the need of objective and efficient methods for breast cosmesis evaluations. However, current evaluation methods rely on ratings from a small group of physicians or semi-automated pipelines, making the processes time-consuming and their results inconsistent. To solve the problem, in this study, we proposed: 1. a

Indexed as

Breast cancerBreast conserving therapyBreast Cosmesis scoresBreast detectionMachine learningPredictive model

Identifiers

PMID36578375
PMCPMC9794198

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.