Concordance as evidence in the Watson for Oncology decision-support system
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[1] Steve T. Mckinlay. Evidence, Explanation and Predictive Data Modelling , 2017 .
[2] Alex Pentland,et al. Fair, Transparent, and Accountable Algorithmic Decision-making Processes , 2017, Philosophy & Technology.
[3] Tanveer Syeda-Mahmood,et al. Role of Big Data and Machine Learning in Diagnostic Decision Support in Radiology. , 2018, Journal of the American College of Radiology : JACR.
[4] B. Mittelstadt. Auditing for Transparency in Content Personalization Systems , 2016 .
[5] R. McDougall. No we shouldn’t be afraid of medical AI; it involves risks and opportunities , 2019, Journal of Medical Ethics.
[6] Tamar Sharon,et al. The Googlization of health research: from disruptive innovation to disruptive ethics. , 2016, Personalized medicine.
[7] J. Sterne,et al. Design characteristics, risk of bias, and reporting of randomised controlled trials supporting approvals of cancer drugs by European Medicines Agency, 2014-16: cross sectional analysis , 2019, BMJ.
[8] Tal Z. Zarsky,et al. The Trouble with Algorithmic Decisions , 2016 .
[9] Bo Hyun Kim,et al. Concordance in postsurgical radioactive iodine therapy recommendations between Watson for Oncology and clinical practice in patients with differentiated thyroid carcinoma , 2019, Cancer.
[10] R. McDougall. Computer knows best? The need for value-flexibility in medical AI , 2018, Journal of Medical Ethics.
[11] A. Tupasela,et al. The Nordic data imaginary , 2020, Big Data Soc..
[12] James H Thrall,et al. Artificial Intelligence and Machine Learning in Radiology: Opportunities, Challenges, Pitfalls, and Criteria for Success. , 2018, Journal of the American College of Radiology : JACR.
[13] David Schneider. Trading at the speed of light , 2011 .
[14] E H Shortliffe,et al. Watson for Oncology and breast cancer treatment recommendations: agreement with an expert multidisciplinary tumor board , 2018, Annals of oncology : official journal of the European Society for Medical Oncology.
[15] Paul K Hodgkin,et al. The computer may be assessing you now, but who decided its values? , 2016, British Medical Journal.
[16] Mark Buchanan,et al. Physics in finance: Trading at the speed of light , 2015, Nature.
[17] A. Norden,et al. Early experience with IBM Watson for Oncology (WFO) cognitive computing system for lung and colorectal cancer treatment. , 2017 .
[18] Young Saing Kim,et al. Concordance Rate between Clinicians and Watson for Oncology among Patients with Advanced Gastric Cancer: Early, Real-World Experience in Korea , 2019, Canadian journal of gastroenterology & hepatology.
[19] D. Prabhakaran,et al. Conduct of clinical trials in developing countries: a perspective , 2009, Current opinion in cardiology.
[20] A. Kumar,et al. 551PD Validation study to assess performance of IBM cognitive computing system Watson for oncology with Manipal multidisciplinary tumour board for 1000 consecutive cases: An Indian experience , 2016 .
[21] Matt Carlson,et al. Automating judgment? Algorithmic judgment, news knowledge, and journalistic professionalism , 2018, New Media Soc..
[22] Marcello D’Agostino,et al. Introduction: the Governance of Algorithms , 2018, Philosophy & Technology.
[23] N. Shah,et al. Implementing Machine Learning in Health Care - Addressing Ethical Challenges. , 2018, The New England journal of medicine.
[24] E. Di Nucci. Should we be afraid of medical AI? , 2019, Journal of Medical Ethics.
[25] Pär Sparén,et al. Occupation and cancer – follow-up of 15 million people in five Nordic countries , 2009, Acta oncologica.
[26] M. Piccart,et al. Keeping faith with trial volunteers , 2007, Nature.
[27] Jie Xu,et al. The practical implementation of artificial intelligence technologies in medicine , 2019, Nature Medicine.
[28] H. Storm,et al. Nordic Cancer Registries – an overview of their procedures and data comparability , 2017, Acta oncologica.
[29] Florian Jaton,et al. We get the algorithms of our ground truths: Designing referential databases in digital image processing , 2017, Social studies of science.
[30] S. Tamang,et al. Potential Biases in Machine Learning Algorithms Using Electronic Health Record Data , 2018, JAMA internal medicine.
[31] Chunhong Hu,et al. Using Artificial Intelligence (Watson for Oncology) for Treatment Recommendations Amongst Chinese Patients with Lung Cancer: Feasibility Study , 2018, Journal of medical Internet research.
[32] A. Rosoff. THE GOLD STANDARD: THE CHALLENGE OF EVIDENCE-BASED MEDICINE AND STANDARDIZATION IN HEALTH CARE , 2004 .
[33] Won-Suk Lee,et al. Assessing Concordance With Watson for Oncology, a Cognitive Computing Decision Support System for Colon Cancer Treatment in Korea. , 2018, JCO clinical cancer informatics.
[34] Do-Hoon Kim,et al. A comparative study of Watson for Oncology and tumor boards in breast cancer treatment , 2019, Korean Journal of Clinical Oncology.
[35] Ted Striphas. Algorithmic culture , 2015 .
[36] Geoffrey E. Hinton. Deep Learning-A Technology With the Potential to Transform Health Care. , 2018, JAMA.
[37] Judy Wajcman,et al. Automation: is it really different this time? , 2017, The British journal of sociology.
[38] E. Shortliffe,et al. Artificial Intelligence Treatment Decision Support For Complex Breast Cancer Among Oncologists With Varying Expertise. , 2019, JCO clinical cancer informatics.