Literature DB >> 33795205

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

Erika Ramsdale1, Eric Snyder2, Eva Culakova2, Huiwen Xu3, Adam Dziorny4, Shuhan Yang2, Martin Zand5, Ajay Anand6.   

Abstract

Entities:  

Keywords:  Decision tools; Geriatric oncology; Machine learning; Predictive models; Statistics

Mesh：

Year:  2021        PMID： 33795205      PMCID： PMC8478967          DOI： 10.1016/j.jgo.2021.03.012

Source DB:  PubMed          Journal:  J Geriatr Oncol        ISSN： 1879-4068            Impact factor:   3.599


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  30 in total

1.  A five-gene signature and clinical outcome in non-small-cell lung cancer.

Authors:  Hsuan-Yu Chen; Sung-Liang Yu; Chun-Houh Chen; Gee-Chen Chang; Chih-Yi Chen; Ang Yuan; Chiou-Ling Cheng; Chien-Hsun Wang; Harn-Jing Terng; Shu-Fang Kao; Wing-Kai Chan; Han-Ni Li; Chun-Chi Liu; Sher Singh; Wei J Chen; Jeremy J W Chen; Pan-Chyr Yang
Journal:  N Engl J Med       Date:  2007-01-04       Impact factor: 91.245

2.  Competing risk of death: an important consideration in studies of older adults.

Authors:  Sarah D Berry; Long Ngo; Elizabeth J Samelson; Douglas P Kiel
Journal:  J Am Geriatr Soc       Date:  2010-03-22       Impact factor: 5.562

3.  Multivariate machine learning models for prediction of pathologic response to neoadjuvant therapy in breast cancer using MRI features: a study using an independent validation set.

Authors:  Elizabeth Hope Cain; Ashirbani Saha; Michael R Harowicz; Jeffrey R Marks; P Kelly Marcom; Maciej A Mazurowski
Journal:  Breast Cancer Res Treat       Date:  2018-10-16       Impact factor: 4.872

Review 4.  Addressing the quality of life needs of older patients with cancer: a SIOG consensus paper and practical guide.

Authors:  F Scotté; P Bossi; E Carola; T Cudennec; P Dielenseger; F Gomes; S Knox; F Strasser
Journal:  Ann Oncol       Date:  2018-08-01       Impact factor: 32.976

5.  Immunomarker Support Vector Machine Classifier for Prediction of Gastric Cancer Survival and Adjuvant Chemotherapeutic Benefit.

Authors:  Jingjing Xie; Zhen Han; Wei Liu; Jiang Yu; Yuming Jiang; Sujuan Xi; Lei Huang; Weicai Huang; Tian Lin; Liying Zhao; Yanfeng Hu; Qi Zhang; Tuanjie Li; Shirong Cai; Guoxin Li
Journal:  Clin Cancer Res       Date:  2018-07-24       Impact factor: 12.531

6.  Modern modelling techniques are data hungry: a simulation study for predicting dichotomous endpoints.

Authors:  Tjeerd van der Ploeg; Peter C Austin; Ewout W Steyerberg
Journal:  BMC Med Res Methodol       Date:  2014-12-22       Impact factor: 4.615

7.  SALMON: Survival Analysis Learning With Multi-Omics Neural Networks on Breast Cancer.

Authors:  Zhi Huang; Xiaohui Zhan; Shunian Xiang; Travis S Johnson; Bryan Helm; Christina Y Yu; Jie Zhang; Paul Salama; Maher Rizkalla; Zhi Han; Kun Huang
Journal:  Front Genet       Date:  2019-03-08       Impact factor: 4.599

8.  Machine learning-based lifetime breast cancer risk reclassification compared with the BOADICEA model: impact on screening recommendations.

Authors:  Pierre O Chappuis; Maria C Katapodi; Chang Ming; Valeria Viassolo; Nicole Probst-Hensch; Ivo D Dinov
Journal:  Br J Cancer       Date:  2020-06-22       Impact factor: 7.640

9.  Open source machine-learning algorithms for the prediction of optimal cancer drug therapies.

Authors:  Cai Huang; Roman Mezencev; John F McDonald; Fredrik Vannberg
Journal:  PLoS One       Date:  2017-10-26       Impact factor: 3.240

10.  Visualizing nationwide variation in medicare Part D prescribing patterns.

Authors:  Alexander Rosenberg; Christopher Fucile; Robert J White; Melissa Trayhan; Samir Farooq; Caroline M Quill; Lisa A Nelson; Samuel J Weisenthal; Kristen Bush; Martin S Zand
Journal:  BMC Med Inform Decis Mak       Date:  2018-11-19       Impact factor: 2.796
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