ArticleJournal of oncology practice2019
"A Tool, Not a Crutch": Patient Perspectives About IBM Watson for Oncology Trained by Memorial Sloan Kettering.
Article in Journal of oncology practice, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 2 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
17 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Impact of Digital Health on Patient-Provider Relationships in Respiratory Secondary Care Based on Qualitative and Quantitative Evidence: Systematic Review.Journal of medical Internet research · 2025Pooled it
- A meta-analysis of Watson for Oncology in clinical application.Scientific reports · 2021Pooled it
- Assessing TDApp: An AI-based clinical decision support system for ADHD treatment recommendations.Frontiers in psychiatry · 2025Article
- A Comprehensive Investigation: Developing the Pharmaceutical Industry through Artificial Intelligence.Current drug discovery technologies · 2025Review
- Artificial intelligence in respiratory care: perspectives on critical opportunities and challenges.Breathe (Sheffield, England) · 2024Review
- Machine learning-based clinical decision support system for treatment recommendation and overall survival prediction of hepatocellular carcinoma: a multi-center study.NPJ digital medicine · 2024Article
- A survey of pregnant patients' perspectives on the implementation of artificial intelligence in clinical care.Journal of the American Medical Informatics Association : JAMIA · 2022Article
- Article
- A New Dawn for the Use of Artificial Intelligence in Gastroenterology, Hepatology and Pancreatology.Diagnostics (Basel, Switzerland) · 2021Review
- Can artificial intelligence overtake human intelligence on the bumpy road towards glioma therapy?Medical oncology (Northwood, London, England) · 2021Review
- [Artificial intelligence in oncological radiology : A (p)review].Der Radiologe · 2021Review
- Progress of Artificial Intelligence in Gynecological Malignant Tumors.Cancer management and research · 2020Review
- Engaging Patients in Precision Oncology: Development and Usability of a Web-Based Patient-Facing Genomic Sequencing Report.JCO precision oncology · 2020Article
- Artificial Intelligence in Decision-Making for Colorectal Cancer Treatment Strategy: An Observational Study of Implementing Watson for Oncology in a 250-Case Cohort.Frontiers in oncology · 2020Article
- Differential impact of cognitive computing augmented by real world evidence on novice and expert oncologists.Cancer medicine · 2019Article
- Artificial Intelligence in the Management of Glioma: Era of Personalized Medicine.Frontiers in oncology · 2019Review
- Adaptive Cancer Therapy in the Age of Generative Artificial Intelligence.Cancer control : journal of the Moffitt Cancer CenterReview
Corrections and comments
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Authors and funding
15 authors.
Funding
Abstract
purposeIBM Watson for Oncology trained by Memorial Sloan Kettering (WFO) is a clinical decision support tool designed to assist physicians in choosing therapies for patients with cancer. Although substantial technical and clinical expertise has guided the development of WFO, patients' perspectives of this technology have not been examined. To facilitate the optimal delivery and implementation of this tool, we solicited patients' perceptions and preferences about WFO.
methodsWe conducted nine focus groups with 46 patients with breast, lung, or colorectal cancer with various treatment experiences: neoadjuvant/adjuvant chemotherapy, chemotherapy for metastatic disease, or systemic therapy through a clinical trial. In-depth qualitative and quantitative data were collected and analyzed to describe patients' attitudes and perspectives concerning WFO and how it may be used in clinical care.
resultsAnalysis of the qualitative data identified three main themes: patient acceptance of WFO, physician competence and the physician-patient relationship, and practical and logistic aspects of WFO. Overall, participant feedback suggested high levels of patient interest, perceived value, and acceptance of WFO, as long as it was used as a supplementary tool to inform their physicians' decision making. Participants also described important concerns, including the need for strict processes to guarantee the integrity and completeness of the data presented and the possibility of physician overreliance on WFO.
conclusionParticipants generally reacted favorably to the prospect of WFO being integrated into the cancer treatment decision-making process, but with caveats regarding the comprehensiveness and accuracy of the data powering the system and the potential for giving WFO excessive emphasis in the decision-making process. Addressing patients' perspectives will be critical to ensuring the smooth integration of WFO into cancer care.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.