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Background: Artificial intelligence (AI) is changing our life, including the medical field. Repeated machine learning using big data made various fields more predictable and accurate. In medicine, IBM Watson for Oncology (WFO), trained by Memorial Slone Kettering Cancer Center (MSKCC), was first introduced and applied in 14 countries worldwide.Our study was designed to assess the feasibility of WFO in actual clinical practice. We aimed to investigate the concordance rate between WFO and multidisciplinary tumor board (MTB) in Urologic cancer patients.
Materials And Methods: We reviewed retrospectively collected data for consecutive patients who underwent WFO and MTB simultaneously in the diagnosis of urologic malignancy before determining further treatment between August 2017 and September 2020. We compared the recommendation of the AI system, WFO (IBM Watson Health, Cambridge, MA), with the opinion of MTB for further managing all patients diagnosed with urologic malignancies such as prostate, bladder, and kidney cancer.
Results: A total of 55 patients were enrolled in our study. The number of patients with prostate cancer was 48. The number of bladder and kidney cancer patients was 5 and 2, respectively. The overall concordance rate between WFO and MTB was 92.7%. Three patients could not suggest proper treatment options using WFO, and the recommended choice of WFO was not feasible in the Korean Health Insurance Review and Assessment Service.
Conclusions: The decision of WFO showed a high concordance rate with a multidisciplinary tumor board for urologic oncology. However, some recommendations of WFO were not feasible in actual practice, and WFO still has some points to improve and modify. Interestingly, applying WFO is likely to facilitate a multidisciplinary team approach.
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http://dx.doi.org/10.1016/j.prnil.2023.09.001 | DOI Listing |
PNAS Nexus
September 2025
Department of Chemical and Biomedical Engineering, University of Missouri, Columbia, MO 65211, USA.
DNA data storage is a promising alternative to conventional storage due to high density, low energy consumption, durability, and ease of replication. While information can be encoded into DNA via synthesis, high costs and the lack of rewriting capability limit its applications beyond archival storage. Emerging "hard drive" strategies seek to encode data onto universal DNA templates without de novo synthesis, using methods such as DNA nanostructures and base modifications.
View Article and Find Full Text PDFAppl Clin Inform
August 2025
Division of Epidemiology, University of Utah School of Medicine, Salt Lake City, Utah, United States.
This study aimed to develop a human factors assessment for medication-related clinical decision support (CDS) based on a previously validated tool that assessed the integration of human factors principles in CDS, the instrument for evaluating human factors principles in medication-related decision support alerts (I-MeDeSA), and pilot it with 10 outpatient clinics across the United States.The human factors assessment was developed based on past validations of I-MeDeSA. Examples included changing the wording of questions and reformatting answer choices to check-box options, allowing for multiple answer choices.
View Article and Find Full Text PDFHepatology
September 2025
Department of Internal Medicine, University of Michigan, Ann Arbor, MI.
HCC surveillance is recommended by liver professional societies but lacks broad acceptance by several primary care and cancer societies due to limitations in the existing data. We convened a diverse multidisciplinary group of cancer screening experts to evaluate current and future paradigms of HCC prevention and early detection using a rigorous Delphi panel approach. The experts had high agreement on 21 statements about primary prevention, HCC surveillance benefits, HCC surveillance harms, and the evaluation of emerging surveillance modalities.
View Article and Find Full Text PDFLangmuir
August 2025
Centre for Sustainable Bioproducts School of Life and Environmental Sciences, Deakin University, Geelong, Victoria 3216, Australia.
Capturing carbon dioxide (CO) remains a critical challenge in mitigating climate change due to its stability and low reactivity. Carbonic anhydrase (CA), a highly efficient enzyme capable of converting CO to bicarbonate at a turnover rate of up to 1 × 10 s, presents a promising solution for carbon capture and storage (CCS). However, its industrial application is limited by poor thermal and chemical stability, especially under harsh conditions such as those found in flue gas streams.
View Article and Find Full Text PDFRadiology
August 2025
Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio.