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Learning analytics and the future of postgraduate medical training
Confronted by the many barriers and deficiencies which currently face those responsible for the training of doctors, the concept of a logic model...
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GEN-RWD Sandbox: bridging the gap between hospital data privacy and external research insights with distributed analytics
BackgroundArtificial intelligence (AI) has become a pivotal tool in advancing contemporary personalised medicine, with the goal of tailoring...
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Internet analytics of an innovative digital educational resource of type 1 diabetes HelloType1 in local languages for people living with diabetes families and healthcare professionals in Southeast Asia
BackgroundThere is minimal data of health outcomes for Type 1 Diabetes (T1D) in Southeast Asia (SEA) where government funding of insulin and blood...
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Comparing quality of breast cancer care in the Netherlands and Norway by federated propensity score analytics
PurposeThe aim of the study was to benchmark and compare breast cancer care quality indicators (QIs) between Norway and the Netherlands using...
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How can we discover the most valuable types of big data and artificial intelligence-based solutions? A methodology for the efficient development of the underlying analytics that improve care
BackgroundMuch has been invested in big data and artificial intelligence-based solutions for healthcare. However, few applications have been...
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Imaging biomarkers and radiomics in pediatric oncology: a view from the PRIMAGE (PRedictive In silico Multiscale Analytics to support cancer personalized diaGnosis and prognosis, Empowered by imaging biomarkers) project
This review paper presents the practical development of imaging biomarkers in the scope of the PRIMAGE (PRedictive In silico Multiscale Analytics to...
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Online reach and engagement of a child nutrition peer-education program (PICNIC): insights from social media and web analytics
BackgroundParents frequently seek parental advice online and on social media; thus, these channels should be better utilized in child health...
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Management decisions of an Academic Radiology Department during COVID-19 pandemic: the important support of a business analytics software
ObjectivesTo analyze the response in the management of both radiological emergencies and continuity of care in oncologic/fragile patients of a...
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The principles of whole-hospital predictive analytics monitoring for clinical medicine originated in the neonatal ICU
In 2011, a multicenter group spearheaded at the University of Virginia demonstrated reduced mortality from real-time continuous cardiorespiratory...
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Translation of AI into oncology clinical practice
Artificial intelligence (AI) is a transformative technology that is capturing popular imagination and can revolutionize biomedicine. AI and machine...
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Patient similarity analytics for explainable clinical risk prediction
BackgroundClinical risk prediction models (CRPMs) use patient characteristics to estimate the probability of having or develo** a particular...
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Health Care Equity in the Use of Advanced Analytics and Artificial Intelligence Technologies in Primary Care
The integration of advanced analytics and artificial intelligence (AI) technologies into the practice of medicine holds much promise. Yet, the...
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Advanced Nursing Practice im europäischen Raum
BackgroundIn the international arena, the role of the advanced practice nurse (APN) has emerged due to changes in the healthcare system and patient...
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The path from big data analytics capabilities to value in hospitals: a sco** review
BackgroundAs the uptake of health information technologies increased, most healthcare organizations have become producers of big data. A growing...
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Knowledge Translation Task Force for core measures clinical practice guideline: a short report on the process and utilization
BackgroundAs part of the 2018 Clinical Practice Guideline (CPG): A Core Set of Outcome Measures for Adults with Neurologic Conditions Undergoing...
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A Two-Step, Trajectory-Focused, Analytics Approach to Attempt Prediction of Analgesic Response in Patients with Moderate-to-Severe Osteoarthritis
IntroductionWe sought to predict analgesic response to daily oral nonsteroidal anti-inflammatory drugs (NSAIDs) or subcutaneous tanezumab 2.5 mg...
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IMplementing Predictive Analytics towards efficient COPD Treatments (IMPACT): protocol for a stepped-wedge cluster randomized impact study
IntroductionPersonalized disease management informed by quantitative risk prediction has the potential to improve patient care and outcomes. The...
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Machine learning-based preoperative analytics for the prediction of anastomotic leakage in colorectal surgery: a swiss pilot study
BackgroundAnastomotic leakage (AL), a severe complication following colorectal surgery, arises from defects at the anastomosis site. This study...
