Due to numerous requests, we have agreed to extend the deadlines until *Jan
10, 2021 *(Sunday) for
AAAI Spring Symposium on Survival Prediction - Algorithms, Challenges, and
Applications (https://spaca.weebly.com/),
which is scheduled to be held on March 22-24, 2021 at Stanford University
in Palo Alto, California, USA (now virtually).
We are also seeking related submissions in the form of *extended
abstracts* (2-4
pages) for poster sessions or *full papers* (4-6 pages, excluding
references) for position, review, and work-in-progress pieces. Papers with
previously published results will be considered. Authors are advised to
format the submissions according to the AAAI template (
https://www.aaai.org/Publications/Templates/AuthorKit21.zip) and submit
through the EasyChair site
(https://easychair.org/conferences/?conf=sss21). *The
submission deadline is January 10*. For details, please see the following
Call for Participation and the attached flyer.
Call for Participation
Symposium URL: *https://spaca.weebly.com/* <https://spaca.weebly.com/>
Submission URL: https://easychair.org/conferences/?conf=sss21
<https://sites.google.com/utexas.edu/ml4nav/>
*Author Kit: https://www.aaai.org/Publications/Templates/AuthorKit21.zip
<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
<https://www.aaai.org/Publications/Templates/AuthorKit21.zip> and submitted
through the AAAI Spring Symposium EasyChair site
<https://easychair.org/conferences/?conf=sss21>. Accepted and camera-ready
papers will be published on the open-access proceedings site, CEUR-WS
<http://ceur-ws.org/>.
Organizing Committee:
Russ Greiner
<https://sites.google.com/view/drrussellgreiner/home?authuser=0> (Symposium
Chair), University of Alberta (rgreiner@ualberta.ca) Neeraj Kumar
<https://neerajkumarvaid.weebly.com/>, University of Alberta (
neeraj.kumar@ualberta.ca)
Thomas A. Gerds <https://biostat.ku.dk/staff_/?pure=en/persons/323237>,
University of Copenhagen (tag@biostat.ku.dk) Mihaela van der Schaar
<https://www.vanderschaar-lab.com/>, Turing Institute, Cambridge and UCLA (
mv472@cam.ac.uk)
For questions please send an email to survivalprediction2021@gmail.com .
Best,
Neeraj, Russ, Thomas, Mihaela
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