Literature DB >> 30472716

Machine Learning and Imaging Informatics in Oncology.

Huan-Hsin Tseng1, Lise Wei1, Sunan Cui1, Yi Luo1, Randall K Ten Haken1, Issam El Naqa2.   

Abstract

In the era of personalized and precision medicine, informatics technologies utilizing machine learning (ML) and quantitative imaging are witnessing a rapidly increasing role in medicine in general and in oncology in particular. This expanding role ranges from computer-aided diagnosis to decision support of treatments with the potential to transform the current landscape of cancer management. In this review, we aim to provide an overview of ML methodologies and imaging informatics techniques and their recent application in modern oncology. We will review example applications of ML in oncology from the literature, identify current challenges and highlight future potentials.
© 2018 S. Karger AG, Basel.

Entities:  

Keywords:  Imaging informatics; Machine learning; Oncology

Mesh:

Year:  2018        PMID: 30472716      PMCID: PMC6533165          DOI: 10.1159/000493575

Source DB:  PubMed          Journal:  Oncology        ISSN: 0030-2414            Impact factor:   2.935


  19 in total

Review 1.  Decision support systems for personalized and participative radiation oncology.

Authors:  Philippe Lambin; Jaap Zindler; Ben G L Vanneste; Lien Van De Voorde; Daniëlle Eekers; Inge Compter; Kranthi Marella Panth; Jurgen Peerlings; Ruben T H M Larue; Timo M Deist; Arthur Jochems; Tim Lustberg; Johan van Soest; Evelyn E C de Jong; Aniek J G Even; Bart Reymen; Nicolle Rekers; Marike van Gisbergen; Erik Roelofs; Sara Carvalho; Ralph T H Leijenaar; Catharina M L Zegers; Maria Jacobs; Janita van Timmeren; Patricia Brouwers; Jonathan A Lal; Ludwig Dubois; Ala Yaromina; Evert Jan Van Limbergen; Maaike Berbee; Wouter van Elmpt; Cary Oberije; Bram Ramaekers; Andre Dekker; Liesbeth J Boersma; Frank Hoebers; Kim M Smits; Adriana J Berlanga; Sean Walsh
Journal:  Adv Drug Deliv Rev       Date:  2016-01-14       Impact factor: 15.470

2.  Long short-term memory.

Authors:  S Hochreiter; J Schmidhuber
Journal:  Neural Comput       Date:  1997-11-15       Impact factor: 2.026

3.  Receptive fields and functional architecture of monkey striate cortex.

Authors:  D H Hubel; T N Wiesel
Journal:  J Physiol       Date:  1968-03       Impact factor: 5.182

4.  Diagnostic Assessment of Deep Learning Algorithms for Detection of Lymph Node Metastases in Women With Breast Cancer.

Authors:  Babak Ehteshami Bejnordi; Mitko Veta; Paul Johannes van Diest; Bram van Ginneken; Nico Karssemeijer; Geert Litjens; Jeroen A W M van der Laak; Meyke Hermsen; Quirine F Manson; Maschenka Balkenhol; Oscar Geessink; Nikolaos Stathonikos; Marcory Crf van Dijk; Peter Bult; Francisco Beca; Andrew H Beck; Dayong Wang; Aditya Khosla; Rishab Gargeya; Humayun Irshad; Aoxiao Zhong; Qi Dou; Quanzheng Li; Hao Chen; Huang-Jing Lin; Pheng-Ann Heng; Christian Haß; Elia Bruni; Quincy Wong; Ugur Halici; Mustafa Ümit Öner; Rengul Cetin-Atalay; Matt Berseth; Vitali Khvatkov; Alexei Vylegzhanin; Oren Kraus; Muhammad Shaban; Nasir Rajpoot; Ruqayya Awan; Korsuk Sirinukunwattana; Talha Qaiser; Yee-Wah Tsang; David Tellez; Jonas Annuscheit; Peter Hufnagl; Mira Valkonen; Kimmo Kartasalo; Leena Latonen; Pekka Ruusuvuori; Kaisa Liimatainen; Shadi Albarqouni; Bharti Mungal; Ami George; Stefanie Demirci; Nassir Navab; Seiryo Watanabe; Shigeto Seno; Yoichi Takenaka; Hideo Matsuda; Hady Ahmady Phoulady; Vassili Kovalev; Alexander Kalinovsky; Vitali Liauchuk; Gloria Bueno; M Milagro Fernandez-Carrobles; Ismael Serrano; Oscar Deniz; Daniel Racoceanu; Rui Venâncio
Journal:  JAMA       Date:  2017-12-12       Impact factor: 56.272

5.  A deep feature fusion methodology for breast cancer diagnosis demonstrated on three imaging modality datasets.

Authors:  Natalia Antropova; Benjamin Q Huynh; Maryellen L Giger
Journal:  Med Phys       Date:  2017-08-12       Impact factor: 4.071

6.  Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD): the TRIPOD statement.

Authors:  Gary S Collins; Johannes B Reitsma; Douglas G Altman; Karel G M Moons
Journal:  Ann Intern Med       Date:  2015-01-06       Impact factor: 25.391

7.  Detection and localization of surgically resectable cancers with a multi-analyte blood test.

Authors:  Joshua D Cohen; Lu Li; Yuxuan Wang; Christopher Thoburn; Bahman Afsari; Ludmila Danilova; Christopher Douville; Ammar A Javed; Fay Wong; Austin Mattox; Ralph H Hruban; Christopher L Wolfgang; Michael G Goggins; Marco Dal Molin; Tian-Li Wang; Richard Roden; Alison P Klein; Janine Ptak; Lisa Dobbyn; Joy Schaefer; Natalie Silliman; Maria Popoli; Joshua T Vogelstein; James D Browne; Robert E Schoen; Randall E Brand; Jeanne Tie; Peter Gibbs; Hui-Li Wong; Aaron S Mansfield; Jin Jen; Samir M Hanash; Massimo Falconi; Peter J Allen; Shibin Zhou; Chetan Bettegowda; Luis A Diaz; Cristian Tomasetti; Kenneth W Kinzler; Bert Vogelstein; Anne Marie Lennon; Nickolas Papadopoulos
Journal:  Science       Date:  2018-01-18       Impact factor: 47.728

8.  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

9.  Radiomics: Images Are More than Pictures, They Are Data.

Authors:  Robert J Gillies; Paul E Kinahan; Hedvig Hricak
Journal:  Radiology       Date:  2015-11-18       Impact factor: 11.105

10.  Radiomics strategies for risk assessment of tumour failure in head-and-neck cancer.

Authors:  Martin Vallières; Emily Kay-Rivest; Léo Jean Perrin; Xavier Liem; Christophe Furstoss; Hugo J W L Aerts; Nader Khaouam; Phuc Felix Nguyen-Tan; Chang-Shu Wang; Khalil Sultanem; Jan Seuntjens; Issam El Naqa
Journal:  Sci Rep       Date:  2017-08-31       Impact factor: 4.379

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  10 in total

Review 1.  High-dimensional role of AI and machine learning in cancer research.

Authors:  Enrico Capobianco
Journal:  Br J Cancer       Date:  2022-01-10       Impact factor: 9.075

2.  Identification of metastatic primary cutaneous squamous cell carcinoma utilizing artificial intelligence analysis of whole slide images.

Authors:  Jaakko S Knuutila; Pilvi Riihilä; Antti Karlsson; Mikko Tukiainen; Lauri Talve; Liisa Nissinen; Veli-Matti Kähäri
Journal:  Sci Rep       Date:  2022-06-14       Impact factor: 4.996

3.  Introduction to machine and deep learning for medical physicists.

Authors:  Sunan Cui; Huan-Hsin Tseng; Julia Pakela; Randall K Ten Haken; Issam El Naqa
Journal:  Med Phys       Date:  2020-06       Impact factor: 4.071

Review 4.  Oncology Informatics: Status Quo and Outlook.

Authors:  Paul Martin Putora; Michael Baudis; Beth M Beadle; Issam El Naqa; Frank A Giordano; Nils H Nicolay
Journal:  Oncology       Date:  2020-05-14       Impact factor: 2.935

Review 5.  Artificial intelligence for molecular neuroimaging.

Authors:  Amanda J Boyle; Vincent C Gaudet; Sandra E Black; Neil Vasdev; Pedro Rosa-Neto; Katherine A Zukotynski
Journal:  Ann Transl Med       Date:  2021-05

Review 6.  Improving PET Imaging Acquisition and Analysis With Machine Learning: A Narrative Review With Focus on Alzheimer's Disease and Oncology.

Authors:  Ian R Duffy; Amanda J Boyle; Neil Vasdev
Journal:  Mol Imaging       Date:  2019 Jan-Dec       Impact factor: 4.488

Review 7.  Balancing accuracy and interpretability of machine learning approaches for radiation treatment outcomes modeling.

Authors:  Yi Luo; Huan-Hsin Tseng; Sunan Cui; Lise Wei; Randall K Ten Haken; Issam El Naqa
Journal:  BJR Open       Date:  2019-07-04

Review 8.  Machine learning applications in radiation oncology.

Authors:  Matthew Field; Nicholas Hardcastle; Michael Jameson; Noel Aherne; Lois Holloway
Journal:  Phys Imaging Radiat Oncol       Date:  2021-06-24

9.  Deep Neural Networks and Transfer Learning on a Multivariate Physiological Signal Dataset.

Authors:  Andrea Bizzego; Giulio Gabrieli; Gianluca Esposito
Journal:  Bioengineering (Basel)       Date:  2021-03-06

10.  Improving the Efficacy of Deep-Learning Models for Heart Beat Detection on Heterogeneous Datasets.

Authors:  Andrea Bizzego; Giulio Gabrieli; Michelle Jin Yee Neoh; Gianluca Esposito
Journal:  Bioengineering (Basel)       Date:  2021-11-28
  10 in total

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