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• • ·Data Science in Critical Care

    Page :i

    Andre L. Holder, Rishikesan Kamaleswaran

    
• • ·Copyright

    Page :ii

    
• • ·Contributors

    Page :iii

    Plan Plan
• • ·Contents

    Page :vii

    Plan Plan
• • ·Forthcoming Issues

    Page :xi

    Plan Plan
• • ·Facilitating the Next Paradigm Shift in Critical Care Through Artificial Intelligence

    Page :xiii

    Andre L. Holder, Rishikesan Kamaleswaran

     

• Promise 1: Targeted, personalized bedside care

  • ·Leveraging Data Science and Novel Technologies to Develop and Implement Precision Medicine Strategies in Critical Care

    Page :627-646

    Lazaro N. Sanchez-Pinto, Sivasubramanium V. Bhavani, Mihir R. Atreya, Pratik Sinha

    Résumé Résumé Plan Plan  
  • ·Predictive Modeling Using Artificial Intelligence and Machine Learning Algorithms on Electronic Health Record Data : Advantages and Challenges

    Page :647-673

    Michael J. Patton, Vincent X. Liu

    Résumé Résumé Plan Plan   
  • ·Machine Learning of Physiologic Waveforms and Electronic Health Record Data : A Large Perioperative Data Set of High-Fidelity Physiologic Waveforms

    Page :675-687

    Sungsoo Kim, Sohee Kwon, Akos Rudas, Ravi Pal, Mia K. Markey, Alan C. Bovik, Maxime Cannesson

    Résumé Résumé Plan Plan   
  • ·The Learning Electronic Health Record

    Page :689-700

    Gilles Clermont

    Résumé Résumé Plan Plan

• Promise 2: Better understanding of critical care deployment and epidemiology

  • ·The Role of Data Science in Closing the Implementation Gap

    Page :701-716

    Andrew J. King, Jeremy M. Kahn

    Résumé Résumé Plan Plan  

• Promise 3: More efficient research practices and strategies

  • ·Designing and Implementing “Living and Breathing” Clinical Trials : An Overview and Lessons Learned from the COVID-19 Pandemic

    Page :717-732

    Christopher M. Horvat, Andrew J. King, David T. Huang

    Résumé Résumé Plan Plan  
  • ·How Electronic Medical Record Integration Can Support More Efficient Critical Care Clinical Trials

    Page :733-749

    Ankita Agarwal, Joseph Marion, Paul Nagy, Matthew Robinson, Allan Walkey, Jonathan Sevransky

    Résumé Résumé Plan Plan  

• The challenges of integrating data science into critical care medicine

  • ·Making the Improbable Possible: Generalizing Models Designed for a Syndrome-Based, Heterogeneous Patient Landscape

    Page :751-768

    Joshua Pei Le, Supreeth Prajwal Shashikumar, Atul Malhotra, Shamim Nemati, Gabriel Wardi

    Résumé Résumé Plan Plan  
  • ·Clinician Trust in Artificial Intelligence : What is Known and How Trust Can Be Facilitated

    Page :769-782

    Juan C. Rojas, Mario Teran, Craig A. Umscheid

    Résumé Résumé Plan Plan  

• Bioethical dilemmas with data science in critical care

  • ·Implementing Artificial Intelligence : Assessing the Cost and Benefits of Algorithmic Decision-Making in Critical Care

    Page :783-793

    Pier Francesco Caruso, Massimiliano Greco, Claudia Ebm, Giovanni Angelotti, Maurizio Cecconi

    Résumé Résumé Plan Plan  
  • ·Critical Bias in Critical Care Devices

    Page :795-813

    Marie-Laure Charpignon, Joseph Byers, Stephanie Cabral, Leo Anthony Celi, Chrystinne Fernandes, Jack Gallifant, Mary E. Lough, Donald Mlombwa, Lama Moukheiber, Bradley Ashley Ong, Anupol Panitchote, Wasswa William, An-Kwok Ian Wong, Lama Nazer

    Résumé Résumé Plan Plan