Dear colleagues,
please find below the Call for Papers for the IEEE AI4H:B2E 2019.
It will take place in Cordoba, Spain, on 05-07 June 2019.
The deadline is approaching fast, as the CfP expires on February 04, 2019.
This is a firm deadline.
We do hope you will find this CfP interesting.
Please accept our deepest apologies if you receive multiple copies.
We do thank you very much for your kind attention.
====================================================================
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: February 04, 2019 (extended - firm and final)
Notification of paper acceptance: March 28, 2019
Submission of camera-ready papers: April 15, 2019
VENUE:
------------------------------------------------------------------------------
Instituto Maimónides de Investigación Biomédica de Córdoba, Spain
FOR ANY OTHER INFORMATION http://www.ai4hb2e.icar.cnr.it/
The CAIP2019 Organizing Committee invites proposals for workshops and
tutorials in conjunction with the 18th International Conference on
Computer Analysis of Images and Patterns. The workshops and tutorials
will be held as side events of the main conference.
*Proposals for Workshop*
The CAIP2019 workshops will provide forums where participants will have
opportunities to discuss technical topics and actively share ideas. The
topics of the workshops should be at the frontiers of academic research
or important applications in the domain of computer vision and pattern
recognition. Each proposal will be assessed for its scientific content,
structure and relevance. Cogently, good proposals would encourage
discussion and interaction between the participants, achievable in a
several ways, e.g., through presentations of submitted work, panel
discussions and hands-on sessions.
Download here the Call for Workshops
<http://caip2019.unisa.it/pages/submission/callcaip2019workshop.pdf>
*Proposals For Tutorials*
The CAIP 2019 Organizing Committee invites proposals for tutorials to be
held as side events of the main conference in Salerno, Italy. Tutorials
should serve one or more of the following objectives:
*
Introduce students and newcomers to major topics of CAIP research
*
Provide instruction on established practices and methodologies
*
Survey a mature area of CAIP research and/or practice
*
Motivate and explain a CAIP topic of emerging importance
*
Introduce expert non-specialists to a CAIP research area
Proposals should contain the following information:
*
The title and a brief description of the tutorial
*
A detailed outline of the tutorial, including preferred length of
tutorial: either 3 hours (half day) or 6 hours (full day). If it is
a full-day tutorial, please give a brief justification
*
Characterization of the potential target audience for the tutorial,
including prerequisite knowledge and estimated number of attendees
*
A description of why the tutorial topic would be of interest to a
substantial part of the CAIP audience
*
A brief resume of the presenter(s), which should include name,
title, affiliation, e-mail address, background in the tutorial area,
example of work in the area (e.g. publications and/or industrial work).
Download here the Call for Tutorials
<http://caip2019.unisa.it/pages/submission/callcaip2019tutorials.pdf>
*Submission*
Proposals should be submitted by electronic mail to the CAIP Organizing
Committee (caip2019(a)unisa.it <mailto:caip2019@unisa.it>)
*Important Dates*
Deadline for workshop proposal: *March 1, 2019
*Notification of Acceptance: *March 15, 2019*
This is K. Kaushik Reddy from India. I'm a self taught data scientist and
machine learning enthusiast. I spend time learning and coding on my Linux
machine, mostly I prefer python.
Learning is my very fun. The Wikimedia community played and is playing an
important role in my learning phase, especially Wikipedia. Also, very
positive towards my participation in GSoC'19 for Wikimedia. To present my
contributions.
That's why I'm here to contribute and learn something cool.
Best,
K. Kaushik Reddy.
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.
====================================================================
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: February 04, 2019 (extended - firm and final)
Notification of paper acceptance: March 28, 2019
Submission of camera-ready papers: April 15, 2019
VENUE:
------------------------------------------------------------------------------
Instituto Maimónides de Investigación Biomédica de Córdoba, Spain
FOR ANY OTHER INFORMATION http://www.ai4hb2e.icar.cnr.it/
Forwarding.
Pine
( https://meta.wikimedia.org/wiki/User:Pine )
---------- Forwarded message ---------
From: Markus Kroetzsch <markus.kroetzsch(a)tu-dresden.de>
Date: Thu, Jan 3, 2019 at 3:54 PM
Subject: [Wikidata] Fully funded PhD positions at TU Dresden
To: Discussion list for the Wikidata project. <wikidata(a)lists.wikimedia.org>
Dear Wikidatans,
We are currently looking to fill two 100%-funded researcher positions in
the field of knowledge representation, AI, and data analysis. This might
be of interest to some of you, or to someone you know:
https://iccl.inf.tu-dresden.de/web/Jobs/en
Applicants should have (or be about to finish) a very good MSc degree or
equivalent in computer science or a related field (esp. mathematics).
Knowledge of Wikidata and related technologies is a plus but not a
requirement. Postdocs can also apply if their research is related to the
project.
Our research group is international, with English as the main language
in everyday work. The positions are part of a major collaborative
research project that aims at improving human understanding of software
systems, and which is starting just now; see
https://www.perspicuous-computing.science/ We aim to further increase
the share of female researchers in our team, so we'd like to encourage
women to apply [1].
I am happy to answer informal questions by email. The application
deadline is quite soon but it can (and probably will) be extended until
the positions are filled. Please feel free to forward this to anyone you
know who might be interested.
Cheers,
Markus
[1] All other genders, including men, are welcome too.
--
Prof. Dr. Markus Kroetzsch
Knowledge-Based Systems Group
Center for Advancing Electronics Dresden (cfaed)
Faculty of Computer Science
TU Dresden
+49 351 463 38486
https://kbs.inf.tu-dresden.de/
_______________________________________________
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https://lists.wikimedia.org/mailman/listinfo/wikidata