AAAI Symposium on Survival Prediction - Algorithms, Challenges and Applications [CFP]
Russ (SPACA) Greiner
Call for Participation
Symposium URL: https://spaca.weebly.com/
Submission URL: https://easychair.org/conferences/?conf=sss21
Author Kit: https://www.aaai.org/Publications/Templates/AuthorKit21.zip
A survival analysis model estimates the time until a specified event will happen in the future (or related survival measure), for an individual. The event of interest could be the time to death or relapse of a patient, or time until an employee leaves a company or until the failure of a mechanical system. The key challenge in learning effective survival models is that this time-to-event is censored for some observations, which limits the direct use of standard regression techniques. This has led to a wide range of survival models, that each use the features of an instance (such as a patient), available at the start time, to produce some survival measure, which might be a risk score, the probability of survival to a specific future time (such as 1 year), or the survival probability over all future times.
This symposium focuses on approaches for learning models that estimate survival measures from survival datasets, which include censored instances. Its objective is to push the state-of-the-art in survival prediction algorithms and address fundamental issues that hinder their applicability for solving complex real-world problems. We anticipate this will foster interdisciplinary collaborations and create new research directions
Topics
We seek submissions that discuss the following topics.
Novel Algorithms — new static or dynamic machine-learning frameworks for survival prediction, algorithms to compute survival measures from multimodal and/or longitudinal datasets.
Evaluation Metrics — limitations of the data (for example, high censoring) and evaluation metrics (for example, c-index), provide new directions for comparing survival models, address model calibration and discrimination issues, and discuss model comparison strategies.
Foundational Issues — issues such as competing risks, causality, counterfactual reasoning, comorbidities, multimorbidities, and uncertainty quantification.
Applications — in medicine, healthcare, manufacturing, engineering, finance, economics, law enforcement.
Submission Instructions
Interested participants should submit either extended abstracts for the poster sessions (2-4 pages) or full papers (4-6 pages, excluding references) for position, review, and work-in-progress pieces. Note we will also consider papers that include results that have already been published (with appropriate acknowledgment).
The Program Committee will review all submissions and communicate the acceptance decisions to the authors via email. Submissions should be formatted according to the AAAI template and submitted through the AAAI Spring Symposium EasyChair site. Accepted and camera-ready papers will be published on the open-access proceedings site, CEUR-WS.
Organizing Committee:
Russ Greiner (Symposium Chair), University of Alberta (rgre...@ualberta.ca) Neeraj Kumar, University of Alberta (neeraj...@ualberta.ca)
For questions please send an email to survivalpre...@gmail.com .
Russ Greiner
Professor • Department of Computing Science
PI • Alberta Machine Intelligence Institute
University of Alberta • Edmonton • Canada • T6G 2E8
Tel: (587) 415-9622 • Fax: (780) 492-1071
rgreiner-@-ualberta-.-ca • https://webdocs.cs.ualberta.ca/~rgreiner/