[Comp-neuro] Call for papers MLCN at MICCAI 2020

MLCN Workshop mlcnworkshop at gmail.com
Fri May 8 13:54:16 CEST 2020

*Please find below the call for papers for the International Workshop of
Machine Learning in Clinical Neuroimaging (MLCN) on 4 October 2020 at
MICCAI 2020 in Lima, Peru. We welcome contributions on novel machine
learning methods and their applications to clinical neuroimaging data.*

The submission deadline is *30 June 2020*, and all MLCN accepted papers
will be eligible for the best paper award of 500 USD.

For more information, please visit https://mlcnws.com/.

Best wishes,
The MLCN 2020 committee

Christos Davatzikos
Andre Marquand
Jonas Richiardi
Emma Robinson
Ahmed Abdulkadir
Cher Bass
Mohamad Habes
Seyed Mostafa Kia
Jane Maryam Rondina
Chantal Tax
Hongzhi Wang
Thomas Wolfers

International Workshop on Machine Learning in Clinical Neuroimaging

4 October 2020 in Lima, Peru

The International Workshop of Machine Learning in Clinical Neuroimaging (
https://mlcnws.com/), a satellite event of MICCAI
(https://miccai2020.org), calls
for original papers in the field of clinical neuroimaging data analysis
with machine learning. The two tracks of the workshop include
methodological innovations as well as clinical applications. This highly
interdisciplinary topic provides an excellent platform to connect
researchers of varying disciplines and to collectively advance the field in
multiple directions.

For the machine learning track, we seek contributions with substantial
methodological novelty in analyzing high-dimensional, longitudinal, and
heterogeneous neuroimaging data using stable, scalable, and interpretable
machine learning models. Topics of interest include but are not limited to:


   Spatio-temporal brain data analysis

   Structural data analysis

   Graph theory and complex network analysis

   Longitudinal data analysis

   Model stability and interpretability

   Model scalability in large neuroimaging datasets

   Multi-source data integration and multi-view learning

   Multi-site data analysis, from preprocessing to modeling

   Domain adaptation, data harmonization, and transfer learning in

   Unsupervised methods for stratifying brain disorders

   Deep learning in clinical neuroimaging

   Model uncertainty in clinical predictions


In the clinical neuroimaging track, we seek contributions that explore how
the application of advanced machine learning methods help us to move
towards precision medicine for complex brain disorders. Topics of interest
include but are not limited to:


   Biomarker discovery

   Refinement of nosology and diagnostics

   Biological validation of clinical syndromes

   Treatment outcome prediction

   Course prediction

   Analysis of wearable sensors

   Neurogenetics and brain imaging genetics

   Mechanistic modeling

   Brain aging


Submission Process:

The workshop seeks high quality, original, and unpublished work that
addresses one or more challenges described above. Papers should be
submitted electronically in Springer Lecture Notes in Computer Science
(LCNS) style (see
for detailed author guidelines) using the CMT system at
https://cmt3.research.microsoft.com/MLCN2020. The page limit is 8-pages (text,
figures, and tables) plus up to 2-pages of references. We review the
submissions in a double-blind process. Please make sure that your
submission is anonymous. Accepted papers will be published in a joint
proceeding with the MICCAI 2020 conference.

Best Paper Award:

This year, all MLCN accepted papers will be eligible for the best paper
award. The recipient of the award will be chosen by the MLCN scientific
committee based on the scientific quality and novelty of contributions. The
winner will be announced at the end of the workshop and will receive 500
USD honorarium.

Important Dates:


   Paper submission deadline: June 30th, 2020

   Notification of Acceptance: July 24th, 2020

   Camera-ready Submission: July 31st, 2020

   Workshop Date: 4 October 2020
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