Call For Papers

The ACM Conference on Health, Inference, and Learning (CHIL) solicits work across a variety of disciplines, including machine learning, statistics, epidemiology, health policy, operations, and economics. CHIL 2020 invites submissions touching on topics focused on relevant problems affecting health. Specifically, authors are invited to submit 8-10 page papers (with unlimited pages for references) to each of the tracks described below.

To ensure that all submissions to CHIL are reviewed by a knowledgeable and appropriate set of reviewers, the conference is divided into tracks and areas of interest. Authors will select exactly one primary track and area of interest when they register their submissions, in addition to one or more sub-disciplines.

Track chairs will oversee the reviewing process. In case you are not sure which track your submission fits under, feel free to contact the track or PC chairs for clarification. The PC Chairs reserve the right to move submissions between tracks and/or areas of interest if the PC believes that a submission has been misclassified.


Important Dates

  • Submissions due – January 13, 2020
  • Notification of Acceptance – Feb 17, 2020
  • Camera Ready – March 6, 2020
  • Conference Date – April 2-4, 2020

Tracks

Track 1, Machine Learning: Models, Algorithms, Inference, and Estimation

Track 2, Applications: Investigation, Evaluation, and Interpretation

Track 3, Policy: Impact, Economics, and Society

Track 4, Practice: Deployments, Systems, and Datasets


Sub-Disciplines

These are called topics in the submission form. Authors should select one or more discipline(s) in machine learning for health (ML4H) from the following list when submitting their paper: benchmark datasets, distribution shift, transfer learning, population health, social networks, scaleable ML4H systems, natural language processing (NLP), computer vision, time series, bias/fairness, causality, *-omics, wearable-data, etc.

Peer reviewers are assigned according to expertise in the sub-discipline(s) selected, so please choose your relevant topics carefully.

Evaluation

Work submitted to ACM CHIL will be reviewed by 3 reviewers within the broader field of machine learning for healthcare. Reviewers will be asked to primarily judge the work according to four criteria:

Relevance: All submissions are expected to be relevant to health. Concretely, this means that the problem is well-placed into the relevant themes for the conference;

Quality: The overall submission quality will be measured by the clarity, validity, comprehensiveness, and depth of scientific exploration, including the summarization of relevant field(s) and placement of the work within them;

Novelty/Sophistication: Excellent submissions will display novel contributions in their problem domain, and demonstrate some form of sophistication. 

Suitability to Track: We will instruct reviewers to gauge whether works submitted are best suited to the track, or should be moved elsewhere.

Final decisions will be made in accordance to reviewer’s overall judgement, along with their subjective ratings of confidence/expertise, and according to our own editorial judgement.

Submission Format and Guidelines

Submission Site

ACM CHIL 2020 is using the site: https://chil2020.hotcrp.com/
This system will go online on December 6, 2019.

At least one author of each accepted paper is required to register for, attend, and present the work at the conference in order for the paper to appear in the conference proceedings in the ACM Digital Library.

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 should be formatted using the 2017 ACM Master Article Template and the reference format indicated therein. For LaTeX users, choose format=sigconf. ACM also makes a Word template available. Authors do not need to include terms, keywords, or other front matter in their submissions.

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. Author notification of acceptance will be provided towards the end of February 2020.

Peer Review

The review process is double blind. Please submit completely anonymized drafts. Please do not include any identifying information, and refrain from citing 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.

Camera Ready

For accepted papers, authors will need to provide the following camera-ready materials by March 6:

  1. Metadata for the eRights system
  2. Submit forms for approval
  3. Final versions of papers via FTP

Dual Submission Policy

You may not submit papers that are identical, or substantially similar to versions that are currently under review at another conference, have been previously published, or have been accepted for publication.

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

Representations

Authors submitting work to ACM CHIL make representations in accordance with that of ACM Publications.

Violations to this policy will result in rejection without review.

ETHICS GUIDELINES

ACM CHIL abides by ethics guidelines provided here: ACM Ethics guidelines