Data Science in Critical Care, An Issue of Critical Care Clinics

ISBN-13: 9780443181931 / Twarda / 2023 / 240 str.

Spis treści

Leveraging Data Science and Novel Technologies to Develop and Implement Precision Medicine Strategies in Critical Care
Predictive Modeling Using Artificial Intelligence and Machine Learning Algorithms on Electronic Health Record Data: Advantages and Challenges
Machine Learning of Physiologic Waveforms and Electronic Health Record Data: A Large Perioperative Data Set of High-Fidelity Physiologic Waveforms
The Learning Electronic Health Record
The Role of Data Science in Closing the Implementation Gap
Designing and Implementing "Living and Breathing” Clinical Trials: An Overview and Lessons Learned from the COVID-19 Pandemic
How Electronic Medical Record Integration Can Support More Efficient Critical Care Clinical Trials
Making the Improbable Possible: Generalizing Models Designed for a Syndrome[1]Based, Heterogeneous Patient Landscape
Clinician Trust in Artificial Intelligence: What is Known and How Trust Can Be Facilitated
Implementing Artificial Intelligence: Assessing the Cost and Benefits of Algorithmic Decision-Making in Critical Care
Critical Bias in Critical Care Devices