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Using the method of meta-analysis to systematically evaluate the consistency of treatment schemes between Watson for Oncology (WFO) and Multidisciplinary Team (MDT), and to provide references for the practical application of artificial intelligence clinical decision-support system in cancer treatment. We systematically searched articles about the clinical applications of Watson for Oncology in the databases and conducted meta-analysis using RevMan 5.3 software. A total of 9 studies were identified, including 2463 patients. When the MDT is consistent with WFO at the 'Recommended' or the 'For consideration' level, the overall concordance rate is 81.52%. Among them, breast cancer was the highest and gastric cancer was the lowest. The concordance rate in stage I-III cancer is higher than that in stage IV, but the result of lung cancer is opposite (P < 0.05).Similar results were obtained when MDT was only consistent with WFO at the "recommended" level. Moreover, the consistency of estrogen and progesterone receptor negative breast cancer patients, colorectal cancer patients under 70 years old or ECOG 0, and small cell lung cancer patients is higher than that of estrogen and progesterone positive breast cancer patients, colorectal cancer patients over 70 years old or ECOG 1-2, and non-small cell lung cancer patients, with statistical significance (P < 0.05). Treatment recommendations made by WFO and MDT were highly concordant for cancer cases examined, but this system still needs further improvement. Owing to relatively small sample size of the included studies, more well-designed, and large sample size studies are still needed.
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http://dx.doi.org/10.1038/s41598-021-84973-5 | DOI Listing |
Cancer
September 2025
Department of Medical Oncology, Centre Léon Bérard, Lyon, France.
Background: Immune checkpoint inhibitors (ICIs) in unselected sarcomas yield limited response rates and tumor control. Long-term responders have however been reported, suggesting a critical challenge in refining patient selection, by identifying reliable predictive factors for response.
Methods: The authors conducted a multicenter, retrospective study of patients with advanced sarcomas treated with ICIs in six French reference sarcoma centers.
Appl Clin Inform
August 2025
Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, New York, United States.
Hospitals are looking to AI and other innovative applications to help alleviate provider burden and dissatisfaction associated with clinical documentation in oncology. Ambient artificial intelligence (AI) scribes are a promising technology to address these issues. However, they generally have not been optimized for oncology.
View Article and Find Full Text PDFJ Palliat Med
September 2025
Section of Palliative Care, Division of General Internal Medicine and Public Health, Vanderbilt University Medical Center, Nashville, TN, USA.
Incarcerated persons (IPs) retain the constitutional right to health care, yet they face unique challenges in accessing palliative care (PC) and designating surrogates, especially when incapacitated. We present two cases of hospitalized IPs with life-limiting illnesses who experienced significant barriers in identifying and engaging surrogates. Both cases underscore the effect of delays in communication with surrogates and restricted end-of-life (EOL) visitation due to correctional policies.
View Article and Find Full Text PDFPhys Imaging Radiat Oncol
July 2025
Division of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Background And Purpose: Accurate delineation of orodental structures on radiotherapy computed tomography (CT) images is essential for dosimetric assessment and dental decisions. We propose a deep-learning (DL) auto-segmentation framework for individual teeth and mandible/maxilla sub-volumes aligned with the ClinRad osteoradionecrosis staging system.
Materials And Methods: Mandible and maxilla sub-volumes were manually defined on simulation CT images from 60 clinical cases, differentiating alveolar from basal regions; teeth were labelled individually.
Int J Environ Res Public Health
August 2025
School of Nursing, Columbia University, New York, NY 10032, USA.
This study reviews how technology-based interventions have been designed and implemented to promote lung cancer screening (LCS), support shared decision-making, and enhance patient engagement. A systematic search of six databases in February 2025 identified 28 eligible studies published between 2014 and 2025. Most interventions were home-based and self-guided, including videos, websites, mobile apps, telehealth, and patient portal messages.
View Article and Find Full Text PDF