[scikit-learn] [CFP] The 3rd International workshop on Machine Learning in Clinical Neuroimaging (MLCN 2020)

[MLCN Workshop]

*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
   neuroimaging
   - 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
https://www.miccai2020.org/en/PAPER-SUBMISSION-GUIDELINE.html#manuscript-format
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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