TY - CHAP
T1 - Case studies and recommendations for designing federated learning models for digital healthcare systems
AU - Wu, Chun Ying
AU - Gupta, Pushpanjali
AU - Mohapatra, Sulagna
N1 - Publisher Copyright:
© 2024 Elsevier Inc. All rights reserved.
PY - 2024/1/1
Y1 - 2024/1/1
N2 - In the realm of digital healthcare, there is a growing trend toward the utilization of exciting technologies such as federated learning (FL) and artificial intelligence. Healthcare systems previously focused on centralized working must now collaborate with the use of remarkable FL. Multiple collaborations can be achieved in a distributed manner where collaborators can communicate when desired in a centralized fashion without sharing the raw data. FL deals with challenges and concerns related to data confidentiality and privacy, helping in minimizing the risk of confidential data leakage. In this chapter, we survey and discuss various literature related to the use of FL in digital healthcare systems. We state the various challenges that arise in the digital healthcare system and provide case studies and solutions to the problem with the use of FL. Finally, we conclude with open challenges that have yet to be addressed.
AB - In the realm of digital healthcare, there is a growing trend toward the utilization of exciting technologies such as federated learning (FL) and artificial intelligence. Healthcare systems previously focused on centralized working must now collaborate with the use of remarkable FL. Multiple collaborations can be achieved in a distributed manner where collaborators can communicate when desired in a centralized fashion without sharing the raw data. FL deals with challenges and concerns related to data confidentiality and privacy, helping in minimizing the risk of confidential data leakage. In this chapter, we survey and discuss various literature related to the use of FL in digital healthcare systems. We state the various challenges that arise in the digital healthcare system and provide case studies and solutions to the problem with the use of FL. Finally, we conclude with open challenges that have yet to be addressed.
KW - Artificial intelligence
KW - data privacy and security
KW - digital healthcare system
KW - federated learning
KW - secured model sharing
UR - http://www.scopus.com/inward/record.url?scp=85199021552&partnerID=8YFLogxK
U2 - 10.1016/B978-0-443-13897-3.00007-2
DO - 10.1016/B978-0-443-13897-3.00007-2
M3 - Chapter
AN - SCOPUS:85199021552
SN - 9780443138966
SP - 301
EP - 323
BT - Federated Learning for Digital Healthcare Systems
PB - Elsevier
ER -