Exploring the need for a clinical decision support system for deprescribing - A qualitative interview study by Aryoutha Asmar Talani, Tora Hammar, Ylva Böttiger

Subjects: “…Clinical decision support system…”
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Problems and Barriers Related to the Use of AI-Based Clinical Decision Support Systems: Interview Study by Godwin Denk Giebel, Pascal Raszke, Hartmuth Nowak, Lars Palmowski, Michael Adamzik, Philipp Heinz, Marianne Tokic, Nina Timmesfeld, Frank Brunkhorst, Jürgen Wasem, Nikola Blase

“…The integration of AI is particularly promising in clinical decision support systems (CDSSs). While the opportunities of this technology are numerous, the problems should not be overlooked. …”
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Using a clinical decision support system to reduce excess driving pressure: the ALARM trial by Ursula Burger-Klepp, Mathias Maleczek, Robin Ristl, Bettina Kroyer, Marcus Raudner, Claus G. Krenn, Roman Ullrich

“…Conclusions In a population at risk of ARDS, a combined intervention of a clinical decision support system and a nudge intervention was shown to reduce the excessive driving pressure above 15 mbar in augmented but not in controlled modes of ventilation.…”
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Enhancing prehospital decision-making: exploring user needs and design considerations for clinical decision support systems by Enze Bai, Zhan Zhang, Yincao Xu, Xiao Luo, Kathleen Adelgais

Subjects: “…Clinical decision support system…”
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Does Gastroenterology Need Artificial Intelligence? by S. M. Kurbatsky

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Effectiveness of an electronic clinical decision support system in improving the management of childhood illness in primary care in rural Nigeria: an observational study by Marek Kwiatkowski, Rodolfo Rossi, Torsten Schmitz, Fenella Beynon, Capucine Musard, Marco Landi, Daniel Ishaya, Jeremiah Zira, Muazu Muazu, Camille Renner, Edwin Emmanuel, Solomon Gideon Bulus

“…Objectives To evaluate the impact of ALgorithm for the MANAgement of CHildhood illness (‘ALMANACH’), a digital clinical decision support system (CDSS) based on the Integrated Management of Childhood Illness, on health and quality of care outcomes for sick children attending primary healthcare (PHC) facilities.Design Observational study, comparing outcomes of children attending facilities implementing ALMANACH with control facilities not yet implementing ALMANACH.Setting PHC facilities in Adamawa State, North-Eastern Nigeria.Participants Children 2–59 months presenting with an acute illness. …”
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User-Oriented Requirements for Artificial Intelligence–Based Clinical Decision Support Systems in Sepsis: Protocol for a Multimethod Research Project by Pascal Raszke, Godwin Denk Giebel, Carina Abels, Jürgen Wasem, Michael Adamzik, Hartmuth Nowak, Lars Palmowski, Philipp Heinz, Silke Mreyen, Nina Timmesfeld, Marianne Tokic, Frank Martin Brunkhorst, Nikola Blase

“… BackgroundArtificial intelligence (AI)–based clinical decision support systems (CDSS) have been developed for several diseases. …”
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Design and validation of a new Healthcare Systems Usability Scale (HSUS) for clinical decision support systems: a mixed-methods approach by Peter J Watkinson, Abir Ghorayeb, Julie L Darbyshire, Marta W Wronikowska

“…Objective To develop and validate a questionnaire to assess the usability of clinical decision support systems (CDSS) and to assist in the early identification of usability issues that may impact patient safety and quality of care.Design Mixed research methods were used to develop and validate the questionnaire. …”
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Using a Clinical Decision Support System to Improve Anticoagulation in Patients with Nonvalve Atrial Fibrillation in China’s Primary Care Settings: A Feasibility Study by Xueying Ru, Tianhao Wang, Lan Zhu, Yunhui Ma, Liqun Qian, Huan Sun, Zhigang Pan

“…To primarily investigate the effect of using a clinical decision support system (CDSS) in community health centers in Shanghai, China, on the proportion of patients prescribed guideline-directed antithrombotic therapy. …”
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Acceptance of artificial intelligence clinical assistant decision support system to prevent and control venous thromboembolism among healthcare workers: an extend Unified Theory of... by Jingxian Wang, Yun Zhou, Yun Zhou, Kai Tan, Zhigang Yu, You Li

Subjects: “…clinical decision support system…”
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Efficacy and safety of an algorithm using C-reactive protein to guide antibiotic therapy applied through a digital clinical decision support system: a study protocol for a randomised controlled clinical trial by Vandack Nobre, Pedro R Povoa, Vitoria Moura Leite Rabelo Rezende, Isabela Nascimento Borges, Cecilia Gomez Ravetti, Renan Pedra De Souza, Paula Frizera Vassalo, Ana Clara de Paula Caldas, Felipe Rodrigues Gatto, Getulio Hideyoshi Okamura, Raquel Lopes de Brito Lacerda

“…It will be applied through a mobile application as a digital clinical decision support system. The primary goal will be to assess the algorithm’s effectiveness in reducing treatment duration compared with standard care based on current guidelines, while ensuring patient safety by monitoring the occurrence of adverse events.Ethics and dissemination Only patients who agree to participate in the study after reading the informed consent form will be included. …”
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Empowering personalized oncology: evolution of digital support and visualization tools for molecular tumor boards by Cosima Strantz, Dominik Böhm, Thomas Ganslandt, Melanie Börries, Patrick Metzger, Thomas Pauli, Andreas Blaumeiser, Alexander Scheiter, Ian-Christopher Jung, Jan Christoph, Iryna Manuilova, Konstantin Strauch, Arsenij Ustjanzew, Niklas Reimer, Hauke Busch, Philipp Unberath

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Benchmarking LLM chatbots’ oncological knowledge with the Turkish Society of Medical Oncology’s annual board examination questions by Efe Cem Erdat, Engin Eren Kavak

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Analysis of preprocessing for Generative Adversarial Networks: A case study on color fundoscopy to fluorescein angiography image-to-image translation by Veena K.M., Veena Mayya, Rashmi Naveen Raj, Sulatha V. Bhandary, Uma Kulkarni

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Leveraging Clinical Decision Support in Dental Settings to Bridge HIV Testing Gaps and Contribute to Ending the Epidemic by Sharon C. Perelman, Tunaidi Ansari, Michael T. Yin, Peter G. Gordon, Nadia Nguyen, Vicky Evangelidis-Sakellson, Carol Kunzel, Kathrine Meyers, Delivette Castor, Ariel Blanchard, David A. Albert

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Advancements in Predictive Analytics: Machine Learning Approaches to Estimating Length of Stay and Mortality in Sepsis by Houssem Ben Khalfallah, Mariem Jelassi, Jacques Demongeot, Narjès Bellamine Ben Saoud

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Supporting clinical decision making in the emergency department for paediatric patients using machine learning: A scoping review protocol. by Fiona Leonard, Dympna O'Sullivan, John Gilligan, Nicola O'Shea, Michael J Barrett

“…<h4>Introduction</h4>Machine learning as a clinical decision support system tool has the potential to assist clinicians who must make complex and accurate medical decisions in fast paced environments such as the emergency department. …”
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An Automated Clinical Laboratory Decision Support System for Test Utilization, Medical Necessity Verification, and Payment Processing by Safedin Beqaj, Rojeet Shrestha, Tim Hamill

“…This viewpoint lays out the potential use of an automated laboratory clinical decision support system that helps providers order the right test for the right disease and documents the right reason or medical necessity to pay for the testing.…”
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Antidepressant Treatment Response Prediction With Early Assessment of Functional Near-Infrared Spectroscopy and Micro-RNA by Lok Hua Lee, Cyrus Su Hui Ho, Yee Ling Chan, Gabrielle Wann Nii Tay, Cheng-Kai Lu, Tong Boon Tang

“…The performance of the proposed custom algorithm suggests the prediction of ATR can be improved with multiple features sources, provided that the inter-subject variability is properly addressed, and can be an effective tool for clinical decision support system in MDD ATR prediction. Clinical and Translational Impact Statement&#x2014;The fusion of neuroimaging fNIRS features and miRNA profiles significantly enhances the prediction accuracy of MDD ATR. …”
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Digital Health Technology Interventions for Improving Medication Safety: Systematic Review of Economic Evaluations by Widya Norma Insani, Neily Zakiyah, Irma Melyani Puspitasari, Muhammad Yorga Permana, Kankan Parmikanti, Endang Rusyaman, Auliya Abdurrohim Suwantika

“…Of the included studies, more than half (n=7, 53.9%) evaluated a clinical decision support system (CDSS)/computerized provider order entry (CPOE), 4 (30.8%) examined automated medication-dispensing systems, and 2 (15.4%) focused on pharmacist-led outreach programs targeting health care professionals. …”
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