Data Preprocessing Techniques for AI and Machine Learning Readiness: Scoping Review of Wearable Sensor Data in Cancer Care.

Journal: JMIR mHealth and uHealth
Published Date: Sep 27, 2024

Abstract

BACKGROUND: Wearable sensors are increasingly being explored in health care, including in cancer care, for their potential in continuously monitoring patients. Despite their growing adoption, significant challenges remain in the quality and consistency of data collected from wearable sensors. Moreover, preprocessing pipelines to clean, transform, normalize, and standardize raw data have not yet been fully optimized.

Authors

  • Bengie L Ortiz
    Department of Pediatrics, Hematology and Oncology Division, Michigan Medicine, University of Michigan Health System, Ann Arbor, MI, United States.
  • Vibhuti Gupta
    Department of Computer Science and Data Science, School of Applied Computational Sciences, Meharry Medical College, Nashville, TN, USA.
  • Rajnish Kumar
    Department of Medical Laboratory Technology, School of Allied Health Sciences, Delhi Pharmaceutical Sciences and Research University, Delhi 110017, India.
  • Aditya Jalin
    Department of Pediatrics, Hematology and Oncology Division, Michigan Medicine, University of Michigan Health System, Ann Arbor, MI, United States.
  • Xiao Cao
    School of Software, Shandong University, Jinan, China.
  • Charles Ziegenbein
    Department of Pediatrics, Hematology and Oncology Division, Michigan Medicine, University of Michigan Health System, Ann Arbor, MI, United States.
  • Ashutosh Singhal
    School of Applied Computational Sciences, Meharry Medical College, Nashville, TN, United States.
  • Muneesh Tewari
    Division of Hematology/Oncology, Department of Internal Medicine, University of Michigan, Ann Arbor, MI.
  • Sung Won Choi
    Division of Hematology/Oncology, Department of Pediatrics, University of Michigan, Ann Arbor, MI.

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