Machine Learning in Medicine
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Summary
This research presents a meta-modelling architecture that automates the very labor-intensive and therefore time-heavy and expensive and therefore expensive and expensive process of manually cataloging and cataloging patient-provider interactions.
- Type
- review
- Published
- 2019-04-03
- Cited by
- 1,831
- References
- 97
- OpenAlex
- https://openalex.org/W2934399013
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:92996321
Keywords
Download, Computer science, Data science, Medicine, Medical education
References
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- A Surgical Safety Checklist to Reduce Morbidity and Mortality in a Global Population
- Caveats for the Use of Operational Electronic Health Record Data in Comparative Effectiveness Research
- Time spent on clinical documentation: a survey of internal medicine residents and program directors.
- Clinical decision support systems could be modified to reduce 'alert fatigue' while still minimizing the risk of litigation.
- Longitudinal histories as predictors of future diagnoses of domestic abuse: modelling study
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- New digital healthcare technologies.
- What Is the Best Mix of Population‐Wide and High‐Risk Targeted Strategies of Primary Stroke and Cardiovascular Disease Prevention?
- A Research Agenda for Diagnostic Excellence in Critical Care Medicine.
- Artificial Intelligence-Based Treatment Decisions: A New Era for NSCLC
- Assessment of Deep Learning Models for Cutaneous Leishmania Parasite Diagnosis Using Microscopic Images
- Large-Scale Annotation of Histopathology Images from Social Media
- Machine Learning to Identify Predictors of Glycemic Control in Type 2 Diabetes: An Analysis of Target HbA1c Reduction Using Empagliflozin/Linagliptin Data
- Head to Head Comparison between Neurology Residents and a Mobile Medical Application (App) for diagnostic accuracy in Cognitive Neurology.
- Machine learning's feet of clay.
- New Phenotypes for Sepsis: The Promise and Problem of Applying Machine Learning and Artificial Intelligence in Clinical Research.
- Applications of deep learning for the analysis of medical data
- Molekulare und zellbasierte Krebstherapie – Quo vadis?
- Big data in nephrology: Are we ready for the change?
- Strap In for the Artificial Intelligence Revolution in Interventional Cardiology.
- Prediction and Prevention Using Deep Learning.
- Artificial Intelligence for Drug Toxicity and Safety
- Aplicaciones de la inteligencia artificial en cardiología: el futuro ya está aquí
- Pre-transplantation Risks and Transplant-Techniques in Haematopoietic Stem Cell Transplantation for Acute Leukaemia
- Primer on machine learning: utilization of large data set analyses to individualize pain management
- The “inconvenient truth” about AI in healthcare
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