Cancer Multidisciplinary Team Meetings: Evidence, Challenges, and the Role of Clinical Decision Support Technology by Vivek Patkar, Dionisio Acosta, Tim Davidson, Alison Jones, John Fox, Mohammad Keshtgar

“…The growing acceptance by clinical community of the health information technology in recent years has created new opportunities and possibilities of using advanced clinical decision support (CDS) systems to realise full potential of cancer MDT meetings. …”
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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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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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Artificial intelligence-assisted clinical decision support for childhood asthma management: A randomized clinical trial. by Hee Yun Seol, Pragya Shrestha, Joy Fladager Muth, Chung-Il Wi, Sunghwan Sohn, Euijung Ryu, Miguel Park, Kathy Ihrke, Sungrim Moon, Katherine King, Philip Wheeler, Bijan Borah, James Moriarty, Jordan Rosedahl, Hongfang Liu, Deborah B McWilliams, Young J Juhn

“…<h4>Rationale</h4>Clinical decision support (CDS) tools leveraging electronic health records (EHRs) have been an approach for addressing challenges in asthma care but remain under-studied through clinical trials.…”
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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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Barriers to dental providers’ use of a clinical decision support tool for pain management following tooth extractions by Shannon Gwin Mitchell, Jan Gryczynski, Donald C. Worley, Stephen E. Asche, Anjali R. Truitt, D. Brad Rindal

“…One approach to practice transformation is to deploy clinical decision support (CDS) tools. This qualitative study examined barriers to CDS use as part of a cluster randomized trial that aimed to decrease opioid prescribing for pain management following tooth extractions across a large dental practice. …”
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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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Development of clinical decision support for patients older than 65 years with fall-related TBI using artificial intelligence modeling. by Biche Osong, Eric Sribnick, Jonathan Groner, Rachel Stanley, Lauren Schulz, Bo Lu, Lawrence Cook, Henry Xiang

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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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Addressing the “Black Hole” of Low Back Pain Care With Clinical Decision Support: User-Centered Design and Initial Usability Study by Robert S Rudin, Patricia M Herman, Robert Vining

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Development of a clinical decision support tool for Primary care Management of lower Urinary tract Symptoms in men: the PriMUS study by Adrian Edwards, Ridhi Agarwal, Janine Bates, Alison Bray, Sarah Milosevic, Emma Thomas-Jones, Michael Drinnan, Marcus Drake, Peter Michell, Bethan Pell, Haroon Ahmed, Natalie Joseph-Williams, Kerenza Hood, Yemisi Takwoingi, Chris Harding

“…To develop and validate three diagnostic prediction models, and a prototype primary care clinical decision support tool. Design Prospective diagnostic accuracy study. …”
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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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The Tools for Integrated Management of Childhood Illness (TIMCI) study protocol: a multi-country mixed-method evaluation of pulse oximetry and clinical decision support algorithms by Fenella Beynon, Hélène Langet, Leah F. Bohle, Shally Awasthi, Ousmane Ndiaye, James Machoki M’Imunya, Honorati Masanja, Susan Horton, Maymouna Ba, Silvia Cicconi, Mira Emmanuel-Fabula, Papa Moctar Faye, Tracy R. Glass, Kristina Keitel, Divas Kumar, Gaurav Kumar, Gillian A. Levine, Lena Matata, Grace Mhalu, Andolo Miheso, Deusdedit Mjungu, Francis Njiri, Elisabeth Reus, Michael Ruffo, Fabian Schär, Kovid Sharma, Helen L. Storey, Irene Masanja, Kaspar Wyss, Valérie D’Acremont, TIMCI Collaborator Group

“…The Tools for Integrated Management of Childhood Illness (TIMCI) project aims to support healthcare providers to identify and manage severe illness, whilst promoting resource stewardship, by introducing pulse oximetry and clinical decision support algorithms (CDSAs) to primary care facilities in India, Kenya, Senegal and Tanzania. …”
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Comparing prediction accuracy for 30-day readmission following primary total knee arthroplasty: the ACS-NSQIP risk calculator versus a novel artificial neural network model by Anirudh Buddhiraju, Michelle Riyo Shimizu, Tony Lin-Wei Chen, Henry Hojoon Seo, Blake M. Bacevich, Pengwei Xiao, Young-Min Kwon

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The role of artificial intelligence in aortic valve stenosis: a bibliometric analysis by Shanshan Chen, Shanshan Chen, Changde Wu, Zhaojie Zhang, Lingjuan Liu, Yike Zhu, Dingji Hu, Chenhui Jin, Haoya Fu, Jing Wu, Songqiao Liu, Songqiao Liu, Songqiao Liu

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Machine learning for predicting severe dengue in Puerto Rico by Zachary J. Madewell, Dania M. Rodriguez, Maile B. Thayer, Vanessa Rivera-Amill, Gabriela Paz-Bailey, Laura E. Adams, Joshua M. Wong

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