Human-Centered Explainable AI at the Edge for eHealth

被引:0
|
作者
Dutta, Joy [1 ]
Puthal, Deepak
机构
[1] Khalifa Univ, C2PS, Abu Dhabi, U Arab Emirates
关键词
XAI; IoMT; Edge; Machine Learning; Interpretability; eHealth;
D O I
10.1109/EDGE60047.2023.00044
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Explainable Artificial Intelligence (XAI) is a new paradigm of Artificial Intelligence (AI) that is giving different AI/Machine Learning (ML) models a boost to penetrate sectors where people are thinking about adopting AI. This work focuses on the adoption of XAI in the health sector. It portrays that careful integration of XAI in both cloud and edge could change the whole healthcare industry and make humans more aware of their present health conditions, which is the need of the hour. To demonstrate the same, we have done an experiment based on the prediction of a particular medical condition called "cardiac arrest" in a specific subject group (patients who are 70 years old). Here, based on the explanation provided by the XAI model (e.g., SHAP, LIME) at Cloud and Edge, our system can predict the chances of a "cardiac arrest" for the subject with a valid explanation. This type of model will be the next big upgrade in the healthcare industry in terms of automation and a self-explanatory system that works as a personal health assistant for individuals.
引用
收藏
页码:227 / 232
页数:6
相关论文
共 50 条
  • [21] Human-Centered AI: A New Synthesis
    Shneiderman, Ben
    [J]. HUMAN-COMPUTER INTERACTION, INTERACT 2021, PT I, 2021, 12932 : 3 - 8
  • [22] Human-Centered AI: A Framework for Green and Sustainable AI
    Shin, Donghee
    Shin, Emily Y.
    [J]. COMPUTER, 2023, 56 (06) : 16 - 25
  • [23] Explainable AI for Designers: A Human-Centered Perspective on Mixed-Initiative Co-Creation
    Zhu, Jichen
    Liapis, Antonios
    Risi, Sebastian
    Bidarra, Rafael
    Youngblood, G. Michael
    [J]. PROCEEDINGS OF THE 2018 IEEE CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND GAMES (CIG'18), 2018, : 458 - 465
  • [24] Human-Centered Explainable AI (HCXAI): Reloading Explainability in the Era of Large Language Models (LLMs)
    Ehsan, Upol
    Watkins, Elizabeth Anne
    Wintersberger, Philipp
    Manger, Carina
    Kim, Sunnie S. Y.
    Van Berkel, Niels
    Riener, Andreas
    Riedl, Mark O.
    [J]. EXTENDED ABSTRACTS OF THE 2024 CHI CONFERENCE ON HUMAN FACTORS IN COMPUTING SYSTEMS, CHI 2024, 2024,
  • [25] Explainable medical imaging AI needs human-centered design: guidelines and evidence from a systematic review
    Haomin Chen
    Catalina Gomez
    Chien-Ming Huang
    Mathias Unberath
    [J]. npj Digital Medicine, 5
  • [26] Cognitive Orthoses: Toward Human-Centered AI
    Ford, Kenneth M.
    Hayes, Patrick J.
    Glymour, Clark
    Allen, James
    [J]. AI MAGAZINE, 2015, 36 (04) : 5 - 8
  • [27] Human-centered redistricting automation in the age of AI
    Cho, Wendy K. Tam
    Cain, Bruce E.
    [J]. SCIENCE, 2020, 369 (6508) : 1179 - 1181
  • [28] Explainable medical imaging AI needs human-centered design: guidelines and evidence from a systematic review
    Chen, Haomin
    Gomez, Catalina
    Huang, Chien-Ming
    Unberath, Mathias
    [J]. NPJ DIGITAL MEDICINE, 2022, 5 (01)
  • [29] Human-centered AI through employee participation
    Haipeter, Thomas
    Wannoeffel, Manfred
    Daus, Jan-Torge
    Schaffarczik, Sandra
    [J]. FRONTIERS IN ARTIFICIAL INTELLIGENCE, 2024, 7
  • [30] AI and student assessment in human-centered education
    Balducci, Bruno
    [J]. FRONTIERS IN EDUCATION, 2024, 9