[{"url":"\/node\/4348","title":"INISTA2023 - Special Session on \"Data Science at the Service of Biology and Healthcare\" DSSBH 2023","body":"

We are pleased to invite you to submit a paper for presentation in the special session on \"Data Science at the Service of Biology and Healthcare (DSSBH 2023)\" that will be part of the \u201cThe 17th International Symposium on INnovations in Intelligent SysTems and Applications\u201d (INISTA 2023, Hammamet, Tunisia, 20-23 September 2023).<\/p>\r\n\r\n

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CONFERENCE INFORMATION:<\/strong><\/p>\r\n\r\n

Core Ranking: C<\/strong> (http:\/\/portal.core.edu.au\/conf-ranks\/1391\/)<\/p>\r\n\r\n

Indexing: IEEE, DBLP, SCOPUS, \u2026<\/p>\r\n\r\n

Proceedings: https:\/\/ieeexplore.ieee.org\/xpl\/conhome\/1803839\/all-proceedings<\/p>\r\n\r\n

Special Session Website: https:\/\/conferences.sigappfr.org\/inista2023\/dssbh-2023\/<\/p>\r\n\r\n

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AIMS AND SCOPE:<\/strong><\/p>\r\n\r\n

Medical and biology data are among the most data analyzed and treated. Biological and medical experimentations in vitro are very expensive, because they are characterized by their complexities and big volumes and results are very sensitive about the health of human. Thus, the exploitation of new technologies and computer science models becomes a necessity, firstly to reduce the cost of experimentations and secondly to help experts (doctors and biologists) to make the good decision. The virus Covid\u201919 is a good lesson and motivation for humanities to continuously develop technologies and computer science programs. In fact, predict diseases or the severity level of virus before any diagnostics become a real challenge for our society and for many researchers from various disciplines (Biology, Medicine, Statistics, Computer Science, etc.).<\/p>\r\n\r\n

Today, there are many processes used for processing data in order to deal with many real-world issues, such as classification, prediction, regression and clustering. The main goal of these processes is to discover knowledge from data in order to make a precise decision. Also, in this kind of problems, the tolerance of errors rate is very low, because the decision concerns the health of human. In addition, it is a challenge for researchers to propose their optimal works in short time. Since many decades, researchers try to win dangerous diseases, while not neglecting the fact that research in this regard is developing from day to day.<\/p>\r\n\r\n

The main goal of the DSSBH2023 special session is to present the recent researches, and their results, on data sciences techniques for the analysis of biology and healthcare data. This session provides a more focused, in-depth venue for presentations, discussions and interactions of a very important subject.<\/p>\r\n\r\n

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TOPICS OF INTERESTS:<\/strong><\/p>\r\n\r\n

The scope of the DSSBH2023 includes, but is not limited to, the following topics:<\/p>\r\n\r\n

Data science models for biological sequence analysis<\/p>\r\n\r\n

Bioinformatics<\/p>\r\n\r\n

Computational Biology<\/p>\r\n\r\n

Health informatics<\/p>\r\n\r\n

Evolutionary and swarm optimization techniques for biology and healthcare applications<\/p>\r\n\r\n

Hybridization of exact and heuristic methods in biology and healthcare<\/p>\r\n\r\n

Computer Vision applied in biology and healthcare<\/p>\r\n\r\n

Cancer diagnosis using machine and deep learning techniques<\/p>\r\n\r\n

Explainable AI in biology and healthcare<\/p>\r\n\r\n

Medical image interpretable AI<\/p>\r\n\r\n

Machine learning for prediction in biology and healthcare<\/p>\r\n\r\n

Dealing with unbalanced classification and regression data in biology and healthcare<\/p>\r\n\r\n

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SUBMISSION PROCESS & INFORMATION:<\/strong><\/p>\r\n\r\n

Manuscripts should conform to the IEEE template\/format as indicated in the Information for Authors section of the Article Submission Guidelines. All manuscripts to be considered for publication must be submitted by the deadline through the Easychair, while selecting the Track \u201cData Science at the Service of Biology and Healthcare\u201d from the option-box.<\/p>\r\n\r\n

Page Limit: Papers have a maximum page limit of 6 pages including references and graphs. INISTA will offer the option to buy a limited number of extra pages for submission (there will be a charge of 100 euros per extra page).<\/p>\r\n\r\n

Accepted papers will appear in the conference proceedings, and be indexed in the Web of Science Core Collection databases. The authors of selected best papers will be invited to extend their contributions for special issues.<\/p>\r\n\r\n

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IMPORTANT DATES<\/strong><\/p>\r\n\r\n

Paper submission deadline: May 1st, 2023<\/p>\r\n\r\n

Paper acceptance notification: June 1st, 2023<\/p>\r\n\r\n

Camera-ready Submission & Registration: June 10th, 2023<\/p>\r\n\r\n

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The organizing committee:<\/strong><\/p>\r\n\r\n

Prof. Walid Barhoumi, LIMTIC Laboratory, University of Tunis El Manar<\/p>\r\n\r\n

ENICarthage, University of Carthage, Tunisia<\/p>\r\n\r\n

E-mail: walid.barhoumi@enicarthage.rnu.tn<\/p>\r\n\r\n

<\/p>\r\n\r\n

Dr. Ramzi Guesmi, LETI Laboratory, University of Sfax<\/p>\r\n\r\n

ISLAIB, University of Jendouba, Tunisia<\/p>\r\n\r\n

E-mail: ramzi.guesmi@islaib.u-jendouba.tn<\/p>\r\n\r\n

<\/p>\r\n\r\n

Dr. Faouzi Mhamdi, LaTICE Laboratory, University of Tunis<\/p>\r\n\r\n

ISLAIB, University of Jendouba, Tunisia<\/p>\r\n\r\n

E-mail: faouzi.mhamdi@ensi.rnu.tn<\/p>\r\n","start":"2023-09-20","end":"2023-09-23"}]

Recrutement

Application des techniques de Machine Learning pour l’estimation des temps de fabrication dans l’industrie de la métallurgie