ACM-CHIL 2021 Call for Papers – Conference on Health, Inference and Learning (Virtual, April 2021)

The ACM Conference on Health, Inference, and Learning (ACM-CHIL 2021) solicits work across a variety of disciplines, including machine learning, statistics, epidemiology, health policy, operations, and economics. ACM-CHIL 2021 invites submissions touching on topics focused on relevant problems affecting health. Authors are invited to submit 8-10 page papers (with unlimited pages for references) to each of the tracks described below.

Link to CFP: https://www.chilconference.org/call-for-papers.html 

Important Dates

• Abstracts due – January 7, 2021 (11:59 pm AoE)
• Submissions due – January 11, 2021 (11:59 pm AoE)
• Notification of Acceptance – Feb 15, 2021 (11:59 pm AoE)
• Camera Ready Due – March 5, 2021 (11:59 pm AoE)
• Conference Dates – April 8-10, 2021

=== Tracks and topics ===

• Track 1: Models and Methods
• Track 2: Applications and Practice
• Track 3: Impact and Society

Topics for each track include but are not restricted to:

Track 1 (Models and Methods):

• (Un)supervised learning, representation learning
• Natural language processing, knowledge graphs
• Computer vision
• Survival analysis
• Deep learning architectures
• Transfer learning, domain adaptation
• Bayesian learning, inference
• Structured learning
• Robust learning
• Causal inference

Track 2 (Applications and Practice):

• Examination of robustness of ML systems to real-world dataset shift, adversarial shift, or on minority subpopulations
• Investigations into model performance on minority subpopulations, and the implications thereof
• Scalable, safe machine learning/inference in clinical environments
• New tools or comprehensive benchmarks for machine learning for healthcare
• Development of scalable systems for processing data in practice (demonstrating, e.g., concern for multi-modality, runtime, robustness, etc., as guided by a clinical use case)
• Bridging the deployment gap
• Remote, wearable, and telehealth
• Data or software packages

Track 3 (Impact and Society):

• Fairness, equity, ethics and justice  
• Model implementation, deployment, and adoption
• Policy, public health, and societal impact of algorithms
• Interpretability
• System design for implementation of ML at scale
• Regulatory frameworks
• Tools for adoption of ML
• Evaluation of bias in legal and/or health contexts 
• Human-algorithm interaction

For more detail on the scope of each track, consult the online CFP:  https://www.chilconference.org/call-for-papers.html 

In case you are not sure which track your submission fits under, feel free to contact the track or program committee chairs for clarification.

=== Submission Details and Guidelines ===

For full details, refer to the online CFP: https://www.chilconference.org/call-for-papers.html.

Length and Formatting

Submitted papers must be 8-10 pages (including all figures and tables), plus unlimited pages for references. Additional supplementary materials (e.g., appendices) can be submitted with their main manuscript. Reviewers will not be required to read the supplementary materials. Papers that are neither in ACM format or exceeding the specified page length, may be rejected without review.

Archival Submissions

Submissions to the main conference are considered archival and will appear in the published proceedings of the conference if accepted.

Dual Submission Policy

You may not submit papers that are identical, or substantially similar to versions that are currently under review at another conference or journal, have been previously published, or have been accepted for publication. Submissions to the main conference are considered archival and will appear in the published proceedings of the conference if accepted.

An exception to this rule is extensions of workshop papers that have previously appeared in non-archival venues, such as workshops, arXiv, or similar without formal proceedings. These works may be submitted as-is or in an extended form. ACM-CHIL also welcomes full paper submissions that extend previously published short papers or abstracts, so long as the previously published version does not exceed 4 pages in length. Note that the submission should not cite the workshop/report and preserve anonymity in the submitted manuscript.

Peer Review

The review process is double-blind. Please submit completely anonymized drafts. Please do not include any identifying information, and refrain from citing the authors’ own prior work in anything other than third-person. Violations to this policy may result in rejection without review.

Conference organizers and reviewers are required to maintain confidentiality of submitted material. Upon acceptance, the titles, authorship, and abstracts of papers will be released prior to the conference.

Open Access

ACM-CHIL is committed to open science and ensuring our proceedings are freely available. The conference will make use of the ‘ACM Authorizer “Open Access” Service’ and ‘ACM OpenTOC Service’, allowing unrestricted access to individual papers as well as the overall proceedings.

=== ACM-CHIL 2021 Organisers ===

Dr. Marzyeh Ghassemi, Dr. Tristan Naumann, Dr. Emma Pierson, Emily Alsentzer, Matthew McDermott, Dr. George Chen, Dr. Stephanie Hyland, Dr. Sanja Šćepanović, Dr. Sanmi Koyejo, Dr. Joyce Ho, Dr. Brett Beaulieu-Jones, Irene Chen, Dr. Jessica Gronsbell, Dr. Tom Pollard

Track 1 Chairs: Dr. Michael Hughes, Dr. Shalmali Joshi, Dr. Rajesh Ranganath, Dr. Rahul G. Krishnan

Track 2 Chairs: Dr. Tom Pollard, Dr. Bobak Mortazavi, Dr. Andrew Beam, Dr. Uri Shalit 

Track 3 Chairs: Dr. Alistair Johnston, Dr. Rumi Chunara, Dr. George Chen