Literature DB >> 33058693

Machine Learning in Oncology: Methods, Applications, and Challenges.

Dimitris Bertsimas1,2, Holly Wiberg2.   

Abstract

Year:  2020        PMID： 33058693      PMCID： PMC7608565          DOI： 10.1200/CCI.20.00072

Source DB:  PubMed          Journal:  JCO Clin Cancer Inform        ISSN： 2473-4276


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  46 in total

Review 1.  Deep learning for healthcare: review, opportunities and challenges.

Authors:  Riccardo Miotto; Fei Wang; Shuang Wang; Xiaoqian Jiang; Joel T Dudley
Journal:  Brief Bioinform       Date:  2018-11-27       Impact factor: 11.622

2.  A DEEP LEARNING APPROACH FOR CANCER DETECTION AND RELEVANT GENE IDENTIFICATION.

Authors:  Padideh Danaee; Reza Ghaeini; David A Hendrix
Journal:  Pac Symp Biocomput       Date:  2017

3.  Radiomic phenotype features predict pathological response in non-small cell lung cancer.

Authors:  Thibaud P Coroller; Vishesh Agrawal; Vivek Narayan; Ying Hou; Patrick Grossmann; Stephanie W Lee; Raymond H Mak; Hugo J W L Aerts
Journal:  Radiother Oncol       Date:  2016-04-13       Impact factor: 6.280

4.  A Machine-Based Approach to Preoperatively Identify Patients with the Most and Least Benefit Associated with Resection for Intrahepatic Cholangiocarcinoma: An International Multi-institutional Analysis of 1146 Patients.

Authors:  Diamantis I Tsilimigras; Rittal Mehta; Dimitrios Moris; Kota Sahara; Fabio Bagante; Anghela Z Paredes; Amika Moro; Alfredo Guglielmi; Luca Aldrighetti; Matthew Weiss; Todd W Bauer; Sorin Alexandrescu; George A Poultsides; Shishir K Maithel; Hugo P Marques; Guillaume Martel; Carlo Pulitano; Feng Shen; Olivier Soubrane; Bas Groot Koerkamp; Itaru Endo; Timothy M Pawlik
Journal:  Ann Surg Oncol       Date:  2019-11-14       Impact factor: 5.344

5.  Digital pathology image analysis: opportunities and challenges.

Authors:  Anant Madabhushi
Journal:  Imaging Med       Date:  2009

6.  Application of unsupervised analysis techniques to lung cancer patient data.

Authors:  Chip M Lynch; Victor H van Berkel; Hermann B Frieboes
Journal:  PLoS One       Date:  2017-09-14       Impact factor: 3.240

7.  Machine learning predicts individual cancer patient responses to therapeutic drugs with high accuracy.

Authors:  Cai Huang; Evan A Clayton; Lilya V Matyunina; L DeEtte McDonald; Benedict B Benigno; Fredrik Vannberg; John F McDonald
Journal:  Sci Rep       Date:  2018-11-06       Impact factor: 4.379

8.  Developing prognostic systems of cancer patients by ensemble clustering.

Authors:  Dechang Chen; Kai Xing; Donald Henson; Li Sheng; Arnold M Schwartz; Xiuzhen Cheng
Journal:  J Biomed Biotechnol       Date:  2009-06-23

9.  Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach.

Authors:  Hugo J W L Aerts; Emmanuel Rios Velazquez; Ralph T H Leijenaar; Chintan Parmar; Patrick Grossmann; Sara Carvalho; Sara Cavalho; Johan Bussink; René Monshouwer; Benjamin Haibe-Kains; Derek Rietveld; Frank Hoebers; Michelle M Rietbergen; C René Leemans; Andre Dekker; John Quackenbush; Robert J Gillies; Philippe Lambin
Journal:  Nat Commun       Date:  2014-06-03       Impact factor: 14.919

10.  Deep learning as a tool for increased accuracy and efficiency of histopathological diagnosis.

Authors:  Geert Litjens; Clara I Sánchez; Nadya Timofeeva; Meyke Hermsen; Iris Nagtegaal; Iringo Kovacs; Christina Hulsbergen-van de Kaa; Peter Bult; Bram van Ginneken; Jeroen van der Laak
Journal:  Sci Rep       Date:  2016-05-23       Impact factor: 4.379
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  5 in total

1.  Applications of Artificial Intelligence in Pediatric Oncology: A Systematic Review.

Authors:  Siddhi Ramesh; Sukarn Chokkara; Timothy Shen; Ajay Major; Samuel L Volchenboum; Anoop Mayampurath; Mark A Applebaum
Journal:  JCO Clin Cancer Inform       Date:  2021-12

2.  Plasma secretome analyses identify IL-8 and nitrites as predictors of poor prognosis in nasopharyngeal carcinoma patients.

Authors:  Ahmed Amine Zergoun; Kyle S Draleau; Faycal Chettibi; Chafia Touil-Boukoffa; Djamel Djennaoui; Taha Merghoub; Mehdi Bourouba
Journal:  Cytokine       Date:  2022-03-09       Impact factor: 3.926

Review 3.  Artificial intelligence in mammographic phenotyping of breast cancer risk: a narrative review.

Authors:  Aimilia Gastounioti; Shyam Desai; Vinayak S Ahluwalia; Emily F Conant; Despina Kontos
Journal:  Breast Cancer Res       Date:  2022-02-20       Impact factor: 8.408

4.  Using machine learning to predict individual patient toxicities from cancer treatments.

Authors:  Katherine Marie Cole; Mark Clemons; Sharon McGee; Mashari Alzahrani; Gail Larocque; Fiona MacDonald; Michelle Liu; Gregory R Pond; Lucy Mosquera; Lisa Vandermeer; Brian Hutton; Ardelle Piper; Ricardo Fernandes; Khaled El Emam
Journal:  Support Care Cancer       Date:  2022-05-25       Impact factor: 3.359

5.  AI-Driven Image Analysis in Central Nervous System Tumors-Traditional Machine Learning, Deep Learning and Hybrid Models.

Authors:  A V Krauze; Y Zhuge; R Zhao; E Tasci; K Camphausen
Journal:  J Biotechnol Biomed       Date:  2022-01-10
  5 in total

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