Physical Features and Vital Signs Predict Serum Albumin and Globulin Concentrations Using Machine Learning.

Journal: Asian Pacific journal of cancer prevention : APJCP
PMID: 33639645

Abstract

OBJECTIVE: Serum protein concentrations are diagnostically and prognostically valuable in cancer and other diseases, but their measurement via blood test is uncomfortable, inconvenient, and costly. This study investigates the possibility of predicting albumin, globulin, and albumin-globulin ratio from easily accessible physical characteristics (height, weight, Body Mass Index, age, gender) and vital signs (systolic blood pressure, diastolic blood pressure, mean arterial pressure, pulse pressure, pulse) using advanced machine learning techniques.

Authors

  • Jing Wei
    School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University, Shenzhen, Guangdong, China.
  • Jie Xiang
    College of Computer Science and Technology, Taiyuan University of Technology, Taiyuan, China.
  • Yousef Yasin
    Department of Applied Psychology and Human Development, Ontario Institute for Studies in Education, University of Toronto, Toronto, Ontario, Canada.
  • Andrew Barszczyk
    Department of Physiology, University of Toronto, Toronto, ON, Canada.
  • Deanne Tak On Wah
    Department of Applied Psychology and Human Development, Ontario Institute for Studies in Education, University of Toronto, Toronto, Ontario, Canada.
  • Meifen Yu
    The Affiliated Hospital of Hangzhou Normal University, Hangzhou Normal University. Hangzhou, Zhejiang, People's Republic of China.
  • Wendy Wenyu Huang
    Applied Psychology and Human Development, University of Toronto, 252 Bloor St. West, Toronto, Ontario, Canada M5S 1V6.
  • Zhong-Ping Feng
    Department of Physiology, University of Toronto, Toronto, ON, Canada.
  • Kang Lee
    Dr. Eric Jackman Institute of Child Study, University of Toronto, Toronto, M5R 2X2, Canada. kang.lee@utoronto.ca.
  • Hong Luo
    SAMR Key Laboratory of Human Factors and Ergonomics, China National Institute of Standardization, Beijing, 100191, China.

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