Call for Papers: Towards Ethical Biomedical Informatics

Submission Information

Thanks for your interest in submitting to the Pacific Symposium on Biocomputing (PSB) conference. Paper submission information can be found here. The submitted papers are reviewed and accepted on a competitive basis. At least three reviewers will be assigned to each submitted manuscript.
August 1, 2022: Call for papers deadline. THIS IS AN ABSOLUTE DEADLINE. Submit your paper here.
September 9, 2022: Final paper decisions announced by PSB organizers.
October 3, 2022: Camera-ready papers due.
December 5, 2022: Abstract deadline for non-reviewed posters.
January 3-7, 2023: Conference dates.

Motivation

Fairness, privacy, trust, and ethics of data capture and sharing are central issues in all of computing. Issues such as biased datasets and insecure privacy practices plague a plethora of biomedical informatics applications. It is crucial for the field to address these issues now, as much of research in biomedical data science is increasingly translated into clinical practice, public policy, and scientific knowledge. We will accept papers within the domains of algorithmic fairness in biomedical ML, privacy and security of biomedical data, trustworthy data sharing, and bioethical evaluations and critiques of existing approaches.

Session Topics

The importance of ethical biomedical and healthcare solutions cannot be overstated. While all of the traditional issues related to fairness and data privacy and sharing apply to biomedical data, there are additional challenges and opportunities when applying these methods to biomedical data. Research themes in “Ethical Biocomputing” can include but are not limited to: sharing of datasets in a privacy-preserved manner, algorithmic approaches to achieving fairness and reducing bias (e.g., novel data augmentation strategies to artificially increase representation), algorithmic techniques for transforming data in a secure manner (e.g., homomorphic encryption), human-computer interaction (HCI) studies of biomedical systems which collect data in a trustworthy manner, demonstrations of security or fairness flaws in existing systems, ethical issues, and development of biomedical systems which intrinsically prioritize fairness, trust, transparency, and/or privacy in their design.

Example Topics

This is not an exhaustive list of topics. Email Peter for questions about whether your paper is within scope for this session.

Privacy and security

Quantification of private information leakage in data taken from genomics, proteomics, metagenomics, bioimaging, biosensors, and personal health trackers.
Privacy-preserving analysis and computation on biological data
Re-identification against biological databases and counter-measures to protect individuals’ sensitive information.
Privacy enhancing techniques and file-formats for data sharing.
Ethical, legal issues and policy efforts in medical and/or biological data sharing.
Storage and safety of biological data.
Application of privacy and cryptography measures to the protection of biological data.
Methods balancing openness of biological data and protection of individuals’ sensitive information.
Human-centered studies of cutting-edge privacy methods.

Fairness

New metrics quantifying the fairness of a dataset or model.
Augmentation and sampling strategies to generate balanced datasets.
Identification of fairness gaps in existing or new data sources.
Preprocessing (e.g., adversarial debiasing) and postprocessing (e.g., model output interpretation) algorithms to achieve fair biomedical classification.