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Development of a Comprehensive Decision Support Tool for Chemotherapy-Cycle Prescribing: Initial Usability Study
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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Anatomic-size determinants drive therapeutic decisions in inflammatory fibroid polyps: a retrospective study
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
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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Revisiting angiomyolipomas: The significance of a rich blood supply on imaging for risk-adapted decision making
Published 2025-07-01“…At 5 years of follow-up, we found a 4.5% risk of HC and 3.6% of patients had a clinically significant growth rate of ≥3 mm/year. …”
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Development of a parent decision support tool for surgical necrotising enterocolitis: a study protocol
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Cost-Effectiveness of Clinical Decision Support to Improve CKD Outcomes Among First Nations Australians
Published 2025-02-01“…We model the cost-effectiveness of the CDS versus usual care. Methods: Taking a health care funder perspective, we modeled a cohort of people from remote NT at risk of or with CKD, as of January 1, 2017. …”
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The impact of a patient decision aid for patients with advanced laryngeal carcinoma – a multicenter study
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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Head and Neck Sarcoma Assessor (HaNSA) for treatment decisions using real-world data
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Clinical decision support for pharmacologic management of treatment-resistant depression with augmented large language models
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
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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