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Workshops

The purpose of workshops is to provide a more interactive and focused platform for presenting and discussing new and emerging ideas. The format of paper presentations may include oral presentations, poster presentations, keynote lectures and panels. Depending on the number of presentations, workshops can be scheduled for 1 day or 2 days. All accepted papers will be published in a special section of the conference proceedings book, under an ISBN reference, and on digital support. All papers presented at the conference venue will be available at the SCITEPRESS Digital Library. SCITEPRESS is a member of CrossRef and every paper is given a DOI (Digital Object Identifier). The proceedings are submitted for indexation by DBLP, Web of Science / Conference Proceedings Citation Index, EI and SCOPUS.

WORKSHOPS LIST

AI4Health 2018International Workshop on Artificial Intelligence for Health (BIOSTEC)
Chair(s): Angelo Cangelosi, Ivanoe De Falco and Giovanna Sannino

International Workshop on
Artificial Intelligence for Health
 - AI4Health 2018

Paper Submission: November 20, 2017 (expired)
Authors Notification: November 21, 2017 (expired)
Camera Ready and Registration: November 29, 2017 (expired)

Co-chairs

Angelo Cangelosi
University of Plymouth
United Kingdom
 
Ivanoe De Falco
CNR - ICAR
Italy
 
Giovanna Sannino
CNR - ICAR
Italy
 
Scope

The workshop on Artificial Intelligence for Health - AI4Health 2018 - 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 and Soft Computing techniques in the fields of medicine, health care and wellbeing. AI4Health is expected to cover the whole range of theoretical and practical aspects, technologies and systems related to the application of artificial intelligence and soft computing methodologies to issues as machine learning, deep learning, knowledge discovery, decision support, regression, forecasting, optimization, and feature selection in the healthcare and wellbeing domain.




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