CHIL 2022 : AHLI Conference on Health, Inference and Learning (CHIL) 2022
Call For Papers
[CFP] CHIL 2022 Call for Papers - Conference on Health, Inference and Learning (Virtual, April 7-8 2022)
We invite you to submit your work to the Conference on Health, Inference, and Learning (CHIL 2022), which solicits work across a variety of disciplines, including machine learning, statistics, epidemiology, health policy, operations, and economics. CHIL 2022 invites submissions on all topics at the intersection of machine learning and health. Authors are invited to submit 8-10 page papers (with unlimited pages for references) to each of the tracks described below.
Pre-register at https://www.chilconference.org/register.html.
Link to call for papers: https://www.chilconference.org/call-for-papers.html
Submissions due – January 14, 2022 (11:59 pm AoE)
Author Notification – February 25, 2022
Conference Dates – April 7-8, 2022
=== Tracks and topics ===
Track 1: Models and Methods: Algorithms, Inference, and Estimation
Track 2: Applications and Practice: Investigation, Evaluation, Interpretation, and Deployment
Track 3: Impact and Society: Policy, Public Health, Social Outcomes, and Economics
Topics for each track include but are not restricted to the following.
Track 1 (Models and Methods):
(Un)supervised learning, representation learning
Natural language processing, knowledge graphs
Deep learning architectures
Transfer learning, domain adaptation
Bayesian learning, inference
Track 2 (Applications and Practice):
Examination of robustness of ML systems to real-world dataset shift or adversarial shift
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
Tools for adoption of ML
Evaluation of bias in legal and/or health contexts
For more detail on the scope of each track, please see our online call for papers: https://www.chilconference.org/call-for-papers.html
If you are not sure which track your submission fits under, please reach out to firstname.lastname@example.org for advice.
=== Submission Details and Guidelines ===
For full details, refer to the online call for papers: https://www.chilconference.org/call-for-papers.html
Submissions should be made via OpenReview: https://openreview.net/group?id=chilconference.org/CHIL/2022/Conference.
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) are welcomed alongside the main manuscript. Reviewers will not be required to read the supplementary materials. For additional details and LaTeX template, refer to the Author Instructions (https://www.chilconference.org/call-for-papers.html#tab-author-info).
As with prior years, submissions to the conference will be considered for both:
Archival proceedings and presentation. Submissions of this type are considered archival and will appear in the conference’s published proceedings, which will be made openly available in the Proceedings of Machine Learning Research (PMLR).
Invited non-archival presentation. Submissions of this type are considered non-archival and will not appear in the conference’s published proceedings, but they will be invited to present during the conference (e.g. in a poster session).
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. 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.
The review process is mutually anonymous. 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.
=== AHLI CHIL 2022 Organisers ===
General Chairs - Dr. Tristan Naumann and Dr. Joyce Ho
Program Chairs - Dr. Sherri Rose and Matthew McDermott
Proceedings Chairs - Dr. George Chen, Dr. Tom Pollard, and Gerardo Flores
Track Chairs - Dr. Rahul Krishnan, Dr. Shalmali Joshi, Dr. Mike Hughes, Dr. Yuyin Zhou, Dr. Uri Shalit, Dr. Alistair Johnson, Dr. Judy Gichoya, Emma Rocheteau, Dr. Lifang He, Dr. Bobak Mortazavi, Dr. Stephen Pfohl, and Dr. Farzan Sasangohar
Communications Chairs - Dr. Sanja Šćepanović, Emily Alsentzer, and Dr. Ayah Zirikly
Finance Chairs - Dr. Brett Beaulieu-Jones, Dr. Ahmed Alaa, and Tasmie Sarker
Tutorial Chairs - Dr. Jessica Gronsbell and Harvineet Singh
Virtual Chairs - Dr. Stephanie Hyland, Dr. Ioakeim Perros, and Brian Gow
Logistics Chair - Tasmie Sarker
For questions/comments, email us at email@example.com.