ArtInHCI’24-TAM

ArtInHCI2024 Session: Trustworthy Algorithms in Medicine: Advancing Explainability, Robustness, Privacy, and Fairness (ArtInHCI’24-TAM) is conducted under the 2nd International Conference on Artificial Intelligence and Human-Computer Interaction, held during October 25-27, 2024 in Kunming.

In recent years, the incorporation of sophisticated algorithms within the medical domain has exhibited significant potential for enhancing diagnostics, treatment modalities, and healthcare delivery. However, the imperative of ensuring the reliability and trustworthiness of these algorithms stands as a pivotal prerequisite for their extensive acceptance and implementation. The primary objective of this specialized session is to delve into and deliberate upon state-of-the-art research and advancements concerning trustworthy algorithms as applied to the realm of medicine. Researchers, practitioners, and subject matter experts are cordially invited to contribute their scholarly perspectives on pertinent themes, encompassing but not limited to, explainable artificial intelligence (XAI), algorithmic resilience, privacy-preserving methodologies, and the equitable application of algorithms in medical contexts. This session offers a comprehensive platform to address the multifaceted challenges and opportunities inherent in the development of dependable and lucid algorithms that engender trust among healthcare professionals and patients alike.


Topics

include but are not limited to:
  • Explainable AI in Medicine: Bridging the Gap between Algorithms and Human Understanding
  • Ensuring Robustness in Medical Algorithms: Challenges and Solutions
  • Privacy-Preserving Techniques for Secure Healthcare Data in Algorithmic Applications
  • Fostering Fairness in Medical Algorithms: Ethical Considerations and Best Practices
  • Algorithmic Accountability in Healthcare: Navigating Legal and Ethical Dimensions
  • Building Trust in Medical AI: Lessons from Interpretable and Transparent Models
  • Securing Patient Privacy: Strategies and Innovations in Medical Algorithm Design

ArtInHCI’24-TAM Committee Member


Dr. Mini Han Wang
Zhuhai Institute of Advanced Technology, Chinese Academy of Sciences

Areas of Expertise: explainable AI with applications in biomedicine, data mining, and image processing

Brief Introduction: Dr. Mini Han Wang received a Ph.D. degree from the faculty of Data Science at the City University of Macao in 2023. She also has a Ph.D. programme at the Department of Ophthalmology and Visual Sciences, the Chinese University of Hong Kong since 2021. She is a senior researcher and a post-doctor at Zhuhai People’s Hospital (Zhuhai Hospital Affiliated with Jinan University/The First Affiliated Hospital of Faculty of Medicine Macau University of Science and Technology). She is also the dean and chief scientist of Perspective Technology Group and the current vice dean of the Department of Big Data and Artificial Intelligence of Zhuhai Institute of Advanced Technology, Chinese Academy of Sciences. Her research interests include explainable AI with applications in biomedicine, data mining, and image processing. She has released more than 124 publications, including patents, papers, and software copyrights. She performs an excellent job in the data science and computer science areas, especially in digital medicine application research.