Dear colleagues,

we are happy to inform you that, due to many requests, the paper 
submission deadline for IEEE AI4H:B2E 2019 has been extended to February 
04, 2019 (firm and final).
We do hope you will take this opportunity to submit a paper.
Please find below the Call for Papers.
Please accept our deepest apologies if you receive multiple copies.
We do thank you very much for your kind attention.




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AI4H:B2E 2019 - IEEE Special Track on Artificial Intelligence for 
Healthcare: from black box to explainable models
Instituto Maimónides de Investigación Biomédica de Córdoba, Spain June 
05-07 2019 - http://www.ai4hb2e.icar.cnr.it/

in conjunction with the 32nd IEEE CBMS International Symposium on 
Computer-Based Medical Systems (IEEE CBMS 2019)
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MISSION:
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The special track on “Artificial Intelligence for Healthcare: from black 
box to explainable models” - AI4H:B2E 2019 - aims at bringing together 
researchers from academia, industry, government and medical centers in 
order to present the state of the art and discuss the latest advances in 
the emerging area of the use of Artificial Intelligence (AI) and Soft 
Computing (SC) techniques in the fields of medicine, biology, healthcare 
and wellbeing.

In general, in recent years, methods based on AI and SC have proved to 
be extremely useful in a wide variety of areas, and are becoming more 
and more widespread, in some cases a sort of a “de facto” standard.

Currently, many of the algorithms on offer are often black box in nature 
(defined as a system which can be viewed in terms of its inputs and 
outputs without any knowledge of its internal workings). This may not be 
an issue for certain practical AI solutions in healthcare, yet in other 
systems it may indeed be a serious limitation. This holds true when a 
clear explanation should be provided to a user about the reasons why a 
solution is proposed by an AI-based system. In fact, if the predictive 
models are not transparent and explainable, we lose the trust of experts 
such as healthcare practitioners. Moreover, without access to the 
knowledge of how an algorithm works we cannot truly understand the 
underlying meaning of the output.

Given the above general framework, AI4H:B2E is expected to cover the 
whole range of methodological and practical aspects related to the use 
of AI and SC in Healthcare:
- we request papers that explore methods to combine state-of-the-art 
data analytics for exploiting the huge data resources available, while 
ensuring that these systems are explainable to domain experts. This will 
result in systems that not only generate new insights but are also more 
fully trusted.
- we also request papers that describe more generally the successful 
application of AI and SC methodologies to issues as machine learning, 
deep learning, knowledge discovery, decision support, regression, 
forecasting, optimization and feature selection in the healthcare, 
biology, medicine and wellbeing domains.

TOPICS:
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The topics of interest include, but are not limited to:

- explainable AI models:
         - Rule and Logic Based Explanation;
         - Deep Learning and methods to explain Hidden Layers;
         - Assistive Technology (AT);
         - Recommender Systems;
         - Natural Language for Explanation;
         - Visualisation & Interactive Interfaces;

- the general application of AI and SC methodologies, in Health, Biology 
and Medicine to issues such as:
         - Knowledge Management of Health Data;
         - Data Mining and Knowledge Discovery in Healthcare;
         - Machine and Deep learning approaches for Health Data;
         - Decision Support Systems for Healthcare and Wellbeing;
         - Optimization for Healthcare problems;
         - Regression and Forecasting for medical and/or biomedical signals;
         - Healthcare Information Systems;
         - Wellness Information Systems;
         - Medical Signal and Image Processing and Techniques;
         - Medical Expert Systems;
         - Diagnosis and Therapy Support Systems;
         - Biomedical Applications;
         - Applications of AI in Healthcare and Wellbeing Systems;
         - Machine Learning-based Medical Systems;
         - Medical Data and Knowledge Bases;
         - Neural Networks in Medicine;
         - Ambient Intelligence and Pervasive Computing in Medicine and 
Healthcare.

PAPER SUBMISSION:
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Authors are invited to submit their papers written in English. Each 
contribution must be prepared following the IEEE two-column format, and 
should not exceed the length of 6 (six) Letter-sized pages; the authors 
may use LaTeX or Microsoft Word templates when preparing their 
manuscripts. Instructions and Templates are available at 
http://www.ai4hb2e.icar.cnr.it/submission.html

All papers must be submitted electronically using the Easychair 
conference management system available online at: 
https://easychair.org/conferences/?conf=cbms2019

All submissions will be peer-reviewed by three reviewers of the Program 
Committee. All accepted papers will be included in the conference 
proceedings, and will be published by the IEEE. For each accepted paper, 
at least one author must register at the conference before the Author 
Registration Deadline.


BEST PAPER AWARD:
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A "Best Paper Award" will be conferred on the author(s) of a paper 
presented at the Special Track, selected by the Chairs based on the best 
combined marks of paper reviewing, assessed by the Program Committee. 
This best paper award is technically sponsored by the Institute of High 
Performance and Computing of the National Research Council of Italy 
(ICAR - CNR).


IMPORTANT DATES:
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Submission deadline: February 04, 2019 (extended - firm and final)
Notification of paper acceptance: March 28, 2019
Submission of camera-ready papers: April 15, 2019

VENUE:
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Instituto Maimónides de Investigación Biomédica de Córdoba, Spain

FOR ANY OTHER INFORMATION http://www.ai4hb2e.icar.cnr.it/

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