====================================================================
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)
====================================================================
MISSION:
------------------------------------------------------------------------------
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:
------------------------------------------------------------------------------
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:
------------------------------------------------------------------------------
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:
------------------------------------------------------------------------------
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:
------------------------------------------------------------------------------
Submission deadline: January 14, 2019
Notification of paper acceptance: March 01, 2019
Submission of camera-ready papers: March 15, 2019
VENUE:
------------------------------------------------------------------------------
Instituto Maimónides de Investigación Biomédica de Córdoba, Spain
FOR ANY OTHER INFORMATION http://www.ai4hb2e.icar.cnr.it/
====================================================================
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)
====================================================================
MISSION:
------------------------------------------------------------------------------
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:
------------------------------------------------------------------------------
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:
------------------------------------------------------------------------------
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:
------------------------------------------------------------------------------
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:
------------------------------------------------------------------------------
Submission deadline: January 14, 2019
Notification of paper acceptance: March 01, 2019
Submission of camera-ready papers: March 15, 2019
VENUE:
------------------------------------------------------------------------------
Instituto Maimónides de Investigación Biomédica de Córdoba, Spain
FOR ANY OTHER INFORMATION http://www.ai4hb2e.icar.cnr.it/