Literature DB >> 23942497

Envisioning Watson as a rapid-learning system for oncology.

Jennifer L Malin1.   

Abstract

Mesh:

Year:  2013        PMID: 23942497      PMCID: PMC3651566          DOI: 10.1200/JOP.2013.001021

Source DB:  PubMed          Journal:  J Oncol Pract        ISSN: 1554-7477            Impact factor:   3.840


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  5 in total

1.  Clinical cancer advances 2011: Annual Report on Progress Against Cancer from the American Society of Clinical Oncology.

Authors:  Nicholas J Vogelzang; Steven I Benowitz; Sylvia Adams; Carol Aghajanian; Susan Marina Chang; Zoann Eckert Dreyer; Pasi A Janne; Andrew H Ko; Greg A Masters; Olatoyosi Odenike; Jyoti D Patel; Bruce J Roth; Wolfram E Samlowski; Andrew D Seidman; William D Tap; Jennifer S Temel; Jamie H Von Roenn; Mark G Kris
Journal:  J Clin Oncol       Date:  2011-12-05       Impact factor: 44.544

Review 2.  ASCO's approach to a learning health care system in oncology.

Authors:  George W Sledge; Clifford A Hudis; Sandra M Swain; Peter M Yu; Joshua T Mann; Robert S Hauser; Allen S Lichter
Journal:  J Oncol Pract       Date:  2013-05       Impact factor: 3.840

3.  Medicine and the computer. The promise and problems of change.

Authors:  W B Schwartz
Journal:  N Engl J Med       Date:  1970-12-03       Impact factor: 91.245

4.  Rapid-learning system for cancer care.

Authors:  Amy P Abernethy; Lynn M Etheredge; Patricia A Ganz; Paul Wallace; Robert R German; Chalapathy Neti; Peter B Bach; Sharon B Murphy
Journal:  J Clin Oncol       Date:  2010-06-28       Impact factor: 44.544

5.  Comprehensive molecular portraits of human breast tumours.

Authors: 
Journal:  Nature       Date:  2012-09-23       Impact factor: 49.962

  5 in total
  15 in total

1.  Big data and biomedical informatics: a challenging opportunity.

Authors:  R Bellazzi
Journal:  Yearb Med Inform       Date:  2014-05-22

Review 2.  Rapid learning for precision oncology.

Authors:  Jeff Shrager; Jay M Tenenbaum
Journal:  Nat Rev Clin Oncol       Date:  2014-01-21       Impact factor: 66.675

Review 3.  Artificial Intelligence and Machine Learning: A New Disruptive Force in Orthopaedics.

Authors:  Murali Poduval; Avik Ghose; Sanjeev Manchanda; Vaibhav Bagaria; Aniruddha Sinha
Journal:  Indian J Orthop       Date:  2020-01-13       Impact factor: 1.251

4.  Prospects and challenges for clinical decision support in the era of big data.

Authors:  Issam El Naqa; Michael R Kosorok; Judy Jin; Michelle Mierzwa; Randall K Ten Haken
Journal:  JCO Clin Cancer Inform       Date:  2018-11-09

5.  Artificial intelligence and lung cancer treatment decision: agreement with recommendation of multidisciplinary tumor board.

Authors:  Min-Seok Kim; Ha-Young Park; Bo-Gun Kho; Cheol-Kyu Park; In-Jae Oh; Young-Chul Kim; Seok Kim; Ju-Sik Yun; Sang-Yun Song; Kook-Joo Na; Jae-Uk Jeong; Mee Sun Yoon; Sung-Ja Ahn; Su Woong Yoo; Sae-Ryung Kang; Seong Young Kwon; Hee-Seung Bom; Woo-Youl Jang; In-Young Kim; Jong-Eun Lee; Won-Gi Jeong; Yun-Hyeon Kim; Taebum Lee; Yoo-Duk Choi
Journal:  Transl Lung Cancer Res       Date:  2020-06

Review 6.  Cognitive computing and eScience in health and life science research: artificial intelligence and obesity intervention programs.

Authors:  Thomas Marshall; Tiffiany Champagne-Langabeer; Darla Castelli; Deanna Hoelscher
Journal:  Health Inf Sci Syst       Date:  2017-11-01

Review 7.  Tuberculosis control, and the where and why of artificial intelligence.

Authors:  Riddhi Doshi; Dennis Falzon; Bruce V Thomas; Zelalem Temesgen; Lal Sadasivan; Giovanni Battista Migliori; Mario Raviglione
Journal:  ERJ Open Res       Date:  2017-06-21

8.  Physician Confidence in Artificial Intelligence: An Online Mobile Survey.

Authors:  Songhee Oh; Jae Heon Kim; Sung-Woo Choi; Hee Jeong Lee; Jungrak Hong; Soon Hyo Kwon
Journal:  J Med Internet Res       Date:  2019-03-25       Impact factor: 5.428

9.  Cancer Prevention Using Machine Learning, Nudge Theory and Social Impact Bond.

Authors:  Daitaro Misawa; Jun Fukuyoshi; Shintaro Sengoku
Journal:  Int J Environ Res Public Health       Date:  2020-01-28       Impact factor: 3.390

10.  Finding relevant free-text radiology reports at scale with IBM Watson Content Analytics: a feasibility study in the UK NHS.

Authors:  Alicja Piotrkowicz; Owen Johnson; Geoff Hall
Journal:  J Biomed Semantics       Date:  2019-11-12
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