Prediction of anemia using facial images and deep learning technology in the emergency department.

Journal: Frontiers in public health
PMID: 36438300

Abstract

BACKGROUND: According to the WHO, anemia is a highly prevalent disease, especially for patients in the emergency department. The pathophysiological mechanism by which anemia can affect facial characteristics, such as membrane pallor, has been proven to detect anemia with the help of deep learning technology. The quick prediction method for the patient in the emergency department is important to screen the anemic state and judge the necessity of blood transfusion treatment.

Authors

  • Aixian Zhang
    Medical School of the Chinese PLA, Beijing, China.
  • Jingjiao Lou
    Shandong Key Laboratory of Medical Physics and Image Processing, Shandong Institute of Industrial Technology for Health Sciences and Precision Medicine, School of Physics and Electronics, Shandong Normal University, Jinan, Shandong, 250358, China.
  • Zijie Pan
    Luoyang Outpatient Department of 63650 Army Hospital of the Chinese PLA, Luoyang, China.
  • Jiaqi Luo
    Department of Computer Science, City University of Hong Kong, Hong Kong 99907, China.
  • Xiaomeng Zhang
    Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, 100700, People's Republic of China.
  • Han Zhang
    Johns Hopkins University, Baltimore, MD, USA.
  • Jianpeng Li
    Department of Cardiology, Taizhou Second People's Hospital, The Affiliated Taizhou Second People's Hospital of Yangzhou University, Taizhou, China.
  • Lili Wang
    School of Logistics, Chengdu University of Information Technology, Chengdu, China.
  • Xiang Cui
    School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China.
  • Bing Ji
    School of Control Science and Engineering, Shandong University, Jinan, Shandong, China.
  • Li Chen
    Department of Endocrinology and Metabolism, Qilu Hospital, Shandong University, Jinan, China.

Keywords

External Resources

Popular Topics
Recent Journals