Showing 2,961 - 2,980 results of 22,070 for search 'decision three (method OR methods)', query time: 0.44s Refine Results
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    Development of a Comprehensive Decision Support Tool for Chemotherapy-Cycle Prescribing: Initial Usability Study by Sanna Iivanainen, Reetta Arokoski, Santeri Mentu, Laura Lang, Jussi Ekström, Henri Virtanen, Vesa Kataja, Jussi Pekka Koivunen

    Published 2025-03-01
    “… Abstract BackgroundChemotherapy cycle prescription is generally carried out through a multistep manual process that is prone to human error. Clinical decision support tools can provide patient-specific assessments that support clinical decisions, improve prescribing practices, and reduce medication errors. …”
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  5. 2965

    Anatomic-size determinants drive therapeutic decisions in inflammatory fibroid polyps: a retrospective study by Xintong Chi, Jiexin Zhao, Jiaxin Shen, Xiongfeng Lin, Chengchao Zheng, Yanwei Lai, Shuping Jiang, Yuping Wang, Guijun Lu, Wenming Liu

    Published 2025-07-01
    “…Our investigation sought to determine crucial clinical indicators for therapeutic decision-making in IFP management. Methods We conducted a retrospective analysis of 114 hospitalized patients from The First Affiliated Hospital of Fujian Medical University and Fuzhou University Affiliated Provincial Hospital between January 2015 and April 2025. …”
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    Use of MedSafer electronic decision support for deprescribing in patients on hemodialysis: a qualitative study by Émilie Bortolussi-Courval, Jimmy J. Lee, Emilie Trinh, Lisa M. McCarthy, M. Battistella, Ryan Hanula, Todd C. Lee, Kathleen Rice, Emily G. McDonald

    Published 2024-12-01
    “…Deprescribing is a promising intervention to reduce PIMs.Methods We previously conducted a prospective controlled trial whereby we provided deprescribing decision support to nephrologists in one of two tertiary care outpatient hemodialysis units in Montreal, Canada. …”
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    The impact of a patient decision aid for patients with advanced laryngeal carcinoma – a multicenter study by Anne N. Heirman, Japke F. Petersen, Abrahim Al-Mamgani, Simone E. J. Eerenstein, Bertram J. de Kleijn, Frank Hoebers, Bernard M. Tijink, Lisette van der Molen, Gyorgy B. Halmos, Richard Dirven, Martijn M. Stuiver, Michiel W. M. van den Brekel

    Published 2025-07-01
    “…Abstract Purpose Patients with advanced larynx cancer face challenging treatment decisions. To address this, we developed and tested a patient decision aid (PDA), aiming to reduce decisional conflict (DC), and enhance knowledge and perceived shared decision-making (SDM). …”
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    Clinical decision support for pharmacologic management of treatment-resistant depression with augmented large language models by Roy H. Perlis, Pilar F. Verhaak, Joseph Goldberg, Cristina Cusin, Michael Ostacher, Gin S. Malhi, Carlos A. Zarate, Richard C. Shelton, Dan V. Iosifescu, Mauricio Tohen, Manish Kumar Jha, Martha Sajatovic, Michael Berk

    Published 2025-12-01
    “…Background: We evaluated whether a large language model could assist in selecting psychopharmacological treatments for adults with treatment-resistant depression. Methods: We generated 20 clinical vignettes reflecting treatment-resistant depression among adults based on distributions drawn from electronic health records. …”
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    Behavioral Biases in Investor Decision-Making: A Comparative Meta-Analysis of Behavioral Finance Research by Seyed Amir Sabet, Saeed Aibaghi esfahani, Abdolmajid Abdolbaghi Ataabadi

    Published 2025-12-01
    “…By understanding these biases, markets can develop tools to mitigate their effects and foster more rational decision-making, as recognizing behavioral biases in investment decisions proves crucial for both investors and policymakers to help mitigate irrational choices and avoid unexpected financial risks, while this research aligns with global behavioral finance studies in emphasizing the need for bias-aware strategies to enhance decision-making stability.MethodsThis meta-analysis synthesizes empirical research on investor behavioral biases through a rigorous four-step methodology: (1) systematic literature review to identify relevant studies, (2) effect size calculation using standardized metrics, (3) heterogeneity testing via Q-statistics and I² to assess consistency, and (4) model selection (fixed- or random-effects) based on heterogeneity levels, with inclusion criteria requiring studies to examine at least one of 12 key biases (e.g., overconfidence, loss aversion), report statistical outcomes (effect sizes, p-values), and cover diverse markets including traditional assets and cryptocurrencies. …”
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