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MLAI4N 2019 : Machine Learning and Artificial Intelligence for Biomedical Health Data


When Oct 5, 2019 - Oct 8, 2019
Where Washington D.C.
Submission Deadline May 20, 2019
Notification Due Jul 25, 2019
Final Version Due Aug 8, 2019
Categories    machine learning   biomedical data   neuroimaging   healthcare

Call For Papers

MLAI4N 2019
Special session on Machine Learning and Artificial Intelligence for Biomedical Health Data will be held in conjunction with DSAA 2019
October 5-8th, 2019, Washington DC — USA
MLAI4N is a full day special session, organized in conjunction with DSAA 2019.


Recent breakthroughs in Data science (deep neural networks including convolutional and tensor networks, geometrical and topological data analysis, statistical methods in functional imaging consisting of EEG/MEG data or time series of 3D images, etc.) allowed not only to create effective diagnostic and prognostic tools but also created prerequisites for alleviating early detection of mental disorders and brain tumors, accelerate the search for life-saving pharmaceuticals, and provide insights about the molecular pathways of the neurodegenerative diseases.

The special session is oriented to all potential applications of data science technologies in feature extraction, classification, recognition, segmentation, enhancing, clustering, anomaly detection, and prediction of neurodegenerative disease states – as applied to the various biomedical time series and images of different nature, especially to multi-modal brain data (X-ray, MRI/fMRI/CT, EEG/MEG, and biomarker assays). Special attention will be paid to Biomedical signals processing for diagnostics and treatment outcome prediction and Natural language processing for case records and medical history.

Topics of interests for the special session include, but are not limited to:

Deep Learning for healthcare
Data Fusion for HealthCare, especially Biomedical images of different nature (X-ray, CT, etc.);
Early diagnosis of specific diseases like Alzheimer, ADHD, ASD etc
Computational Neuroscience; Neuroimaging and Time Series data (including MRI/fMRI/CT, EEG/MEG, etc.) studies;
Novel methods of data analysis and pattern recognition applied to the biomedical images of different nature;
Deep learning in Neuroimaging data analysis;
Matrix and tensor methods in Neuroimaging data analysis;
Dimensionality reduction in Neuroimaging data analysis;
Nonparametric and computational Bayesian methods in Neuroimaging data analysis;
Manifold learning, classification, clustering and regression in Neuroimaging data analysis;

All deadlines are at 11:59 PM EDT.

SPECIAL SESSION DATE October 5-8th, 2019

We invite submission of unpublished original research papers that are not under review elsewhere. All papers will be peer reviewed.
The paper length allowed for the papers in the Research and Application tracks is a maximum of ten (10) pages.
The format for both types of papers is the standard 2-column U.S. letter style IEEE Conference template. See the IEEE Proceedings Author Guidelines: for further information and instructions.

All submissions will be blind reviewed by the Program Committee on the basis of technical quality, relevance to the conference’s topics of interest, originality, significance, and clarity. Author names and affiliations must not appear in the submissions, and bibliographic references must be adjusted to preserve author anonymity. Submissions failing to comply with paper formatting and authors anonymity will be rejected without reviews.

All accepted papers and posters will be published by IEEE and will be submitted for inclusion in the IEEE Xplore Digital Library. The conference proceedings will be submitted for EI indexing through INSPEC by IEEE. Top quality papers accepted and presented at the conference will be selected for extension and invited to the special issues of International Journal of Data Science and Analytics (JDSA, Springer).

Submission Website
Submissions to the main conference, including Research Track and Applications Track are available from Easy Chair (

Professor Evgeny Burnaev – contact person,
Professor Andrzej Cichocki,
Professor Alexander Bernstein,
Leading researcher Maxim Sharaev,

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