ArticleSensors (Basel, Switzerland)2020
Artificial Intelligence-Driven Oncology Clinical Decision Support System for Multidisciplinary Teams.
Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Pooled it
- Artificial intelligence construction: a review of the bridge between CT imaging features of lung ground-glass nodules adenocarcinoma and carcinogenic driver genes.Journal of cancer research and clinical oncology · 2026Review
- Article
- Current AI technologies in cancer diagnostics and treatment.Molecular cancer · 2025Review
- Alignment Between Treatment Decision and Treatment Administration for Squamous Cell Carcinoma of the Upper Aerodigestive Tract Before, During, and After the COVID-19 Pandemic: A Retrospective Analysis.Journal of clinical medicine · 2025Article
- Artificial Intelligence in Breast Cancer Diagnosis and Surgical Decision-Making: An Updated and Comprehensive Overview of Precision and Personalization in Current Evidence.Cancer management and research · 2025Review
- Multimodal integration strategies for clinical application in oncology.Frontiers in pharmacology · 2025Review
- The Role of Artificial Intelligence on Tumor Boards: Perspectives from Surgeons, Medical Oncologists and Radiation Oncologists.Current oncology (Toronto, Ont.) · 2024Review
- Clinical decision making in prostate cancer care-evaluation of EAU-guidelines use and novel decision support software.Scientific reports · 2024Article
- Consistency of CSCO AI with Multidisciplinary Clinical Decision-Making Teams in Breast Cancer: A Retrospective Study.Breast cancer (Dove Medical Press) · 2024Article
- A Qualitative Study of Decision-making (DM) in Surgery and Cancer Care: an Indian Perspective.Indian journal of surgical oncology · 2023Article
- The Convergence of FTIR and EVs: Emergence Strategy for Non-Invasive Cancer Markers Discovery.Diagnostics (Basel, Switzerland) · 2022Review
- Artificial Intelligence for Smart Manufacturing: Methods and Applications.Sensors (Basel, Switzerland) · 2021Article
- Human, All Too Human? An All-Around Appraisal of the "Artificial Intelligence Revolution" in Medical Imaging.Frontiers in psychology · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Watson for Oncology (WfO) is a clinical decision support system driven by artificial intelligence. In Korea, WfO is used by multidisciplinary teams (MDTs) caring for cancer patients. This study aimed to investigate the effect of WfO use on hospital satisfaction and perception among patients cared for by MDTs. This was a descriptive study that used a written survey to gather information from cancer patients at a hospital in Korea. The rate of positive change in patient perception after treatment was 86.8% in the MDT-WfO group and 71.2% in the MDT group. In terms of easily understandable explanations, the MDT-WfO (9.53 points) group reported higher satisfaction than the MDT group (9.24 points). Younger patients in the MDT-WfO group showed high levels of satisfaction and reliability of treatment. When WfO was used, the probability of positive change in patient perception of the hospital was 2.53 times higher than when WfO was not used. With a one-point increase in overall satisfaction, the probability of positive change in patient perception of the hospital increased 1.97 times. Therefore, if WfO is used appropriately in the medical field, it may enhance patient satisfaction and change patient perception positively.
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Registered trials
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.