Tracks

IEEE ICHI 2024 is a premier community forum concerned with the application of computer science, information science, data science, and informatics principles, as well as information technology, and communication science and technology to address problems and support research in healthcare, medicine, life science, public health, and everyday wellness. The conference highlights the most novel technical contributions to stakeholder-centered technology innovation for benefiting human health and the related social and ethical implications.

We strongly encourage authors to submit their original contributions describing their algorithmic, methodological or empirical contributions, and theories relevant to the broader context of health informatics. Submissions can focus on one or more specific aspects of theory, design, development, evaluation, or deployment. IEEE ICHI 2024 has three main tracks for paper submissions: analytics, human factors, and systems:

Analytics Track

In the Analytics track, we invite submissions on novel methods for exploring and analyzing healthcare data such as biomedical pattern recognition, biomarker discovery, disease profiling and personalized treatment, natural language processing and text mining, recommender systems, clinical phenotyping, visual analytics, explainability, and epidemiological modeling.

Human Factors Track

Contributions in the realm of Human Factors may include empirical studies on the use and needs of health information technology in everyday life, socio-technical studies on the implementation and utilization of health information technology in clinical settings, investigations into the community-level impact and implications of health informatics, design and evaluative efforts centered on innovative user-centered health information technology, as well as empirical research on public policies that leverage health informatics infrastructures.

Systems Track

The Systems track welcomes submissions related to the design, development, deployment, and evaluation of high-performing, privacy-preserving and secure software or hardware systems. In particular, the Systems track invites submissions on the development of large language model (LLM) applications, such as ChatGPT, their utilization in clinical settings, and the strengths and limitations of LLMs in enhancing the efficiency and effectiveness of clinical research, education, and practice.