Precision Medicine in Practice: What Role for HCI?

Precision Medicine (PM) promises to tailor prevention, diagnosis, and treatment to individuals using molecular, clinical, and lifestyle data. For example, advances in genomic sequencing, large-scale biomedical datasets, and machine learning are accelerating this vision, particularly in the fields of oncology and pharmacogenomics. Yet, beyond technical developments, PM introduces a range of socio-technical challenges when implemented in real-world healthcare settings. These include interpreting probabilistic predictions in clinical practice, communicating uncertainty to patients and clinicians, integrating data-intensive tools into complex healthcare workflows, and addressing concerns around privacy, cost, and equitable access. Such challenges suggest that PM cannot be understood purely as a biomedical or computational problem, but also requires attention to interaction, interpretation, and governance. This Birds of a Feather (BoF) session brings together researchers and practitioners across HCI, Interactive Health (IH), clinical medicine, and design to discuss how HCI perspectives can help make PM interpretable, workable, and equitable in practice.

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Publication Details

Journal
Lancaster EPrints (Lancaster University)
Published
2026-03-31
Primary Topic
Machine Learning in Healthcare
Type
article
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article

Precision Medicine in Practice: What Role for HCI?

Shuhao Ma, Minzhu Zhao, Bo Young Kim, Yuhao Sun et al.
Lancaster EPrints (Lancaster University)
Machine Learning in Healthcare
article

Precision Medicine in Practice: What Role for HCI?

Shuhao Ma, Minzhu Zhao, Bo Young Kim, Yuhao Sun, Wesley Kai-Xian McLoughlin
article en

Abstract

Precision Medicine (PM) promises to tailor prevention, diagnosis, and treatment to individuals using molecular, clinical, and lifestyle data. For example, advances in genomic sequencing, large-scale biomedical datasets, and machine learning are accelerating this vision, particularly in the fields of oncology and pharmacogenomics. Yet, beyond technical developments, PM introduces a range of socio-technical challenges when implemented in real-world healthcare settings. These include interpreting probabilistic predictions in clinical practice, communicating uncertainty to patients and clinicians, integrating data-intensive tools into complex healthcare workflows, and addressing concerns around privacy, cost, and equitable access. Such challenges suggest that PM cannot be understood purely as a biomedical or computational problem, but also requires attention to interaction, interpretation, and governance. This Birds of a Feather (BoF) session brings together researchers and practitioners across HCI, Interactive Health (IH), clinical medicine, and design to discuss how HCI perspectives can help make PM interpretable, workable, and equitable in practice.

Lancaster EPrints (Lancaster University)
Partnerships for the goals
Openalex Percentile: Top 3%
Machine Learning in Healthcare
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Precision Medicine in Practice: What Role for HCI? — Shuhao Ma, Minzhu Zhao, et al. · Lancaster EPrints (Lancaster University) (2026) | TGRS Research Map | TGRS