Machine learning in health informatics and biological systems CIBB 2018 Special session

15th International Conference on Computational Intelligence methods for Bioinformatics and Biostatistcs
Universidade Nova de Lisboa, Caparica, Almada, Portugal, EU
Thursday 6th, Friday 7th, Saturday 8th September 2018

Proceedings publication

2020-01-22 Update: The proceedings of the CIBB 2018 conference have been published as a book of the Lecture in Bioinformatics (LNBI) series of Springer.

The proceedings include the following papers of our special session:

• 1. "Designing and evaluating deep learning models for cancer detection on gene expression data"
  by Arif Canakoglu, Luca Nanni, Artur Sokolovsky, and Stefano Ceri

• 2. "Network propagation-based semi-supervised identification of genes associated with autism spectrum disorder"
  by Hugo F. M. C. Martiniano, Muhammad Asif, Astrid Moura Vicente, and Luís Correia

• 3. "Exposing and characterizing subpopulations of distinctly regulated genes by k-plane regression"
  by Fabrizio Frasca, Matteo Matteucci, Marco J. Morelli, and Marco Masseroli

Scientific programme

The special session is confirmed and will happen during the CIBB 2018 conference. Here is the list of the papers that will be presented:

• 1. "The scourge of anti-microbial resistance: a machine learning approach for prescription patterns analytics"
  by Davide Castaldi, Ilaria Giordani, Antonio Candelieri, Francesco Archetti, and Roberto Mattina

• 2. "Designing and evaluating deep learning methods for cancer classification on gene expression data"
  by Arif Canakoglu, Luca Nanni, Artur Sokolovsky, and Stefano Ceri

• 3. "A semi-supervised learning approach to the identification and prioritization of genes associated with autism spectrum disorder"
  by Hugo Martiniano, Muhammad Asif, Astrid Vicente, and Luís Correia

• 4. "Unveiling gene expression histonic regulative patterns by hyperplanes clustering"
  by Fabrizio Frasca, Matteo Matteucci, Marco Morelli and Marco Masseroli

• 5. "Identification of real and imaginary movements in EEG using machine learning models"
  by Joana Moreira, Mariana Moreira, Nuno Pombo, and Nuno Garcia

Call for papers

This is the webpage for the call for papers for the special session Machine learning in health informatics and biological systems within the 15th International Conference on Computational Intelligence methods for Bioinformatics and Biostatistcs (CIBB 2018) that will be held at Universidade Nova de Lisboa in Almada, Portugal, EU.

If you are working on a project related to the topics described below, you are warmly invited to submit a short paper to our special session.

Aim and scope

Machine learning has become a pivotal tool to analyze biomedical and biological datasets, especially in the Big Data era. In fact, machine learning algorithms can identify hidden relationships and structures in health care data, and even take advantage of them to make accurate predictions about similar or future data instances. For example, machine learning software has been able to predict the diagnosis of tumor patients just by processing patients' clinical features, allowing scientists to save time and money compared to wet lab experiments. Computational researchers have also exploited machine learning to infer knowledge about patients by analyzing biological datasets, especially the ones featuring genetics and epigenomic traits. Data mining approaches applied to such datasets, in fact, can lead to relevant discoveries both to understand molecular biology and to gain new knowledge about patients’ diseases.

Our special session on "Machine learning in health informatics and biological systems" aims at boosting these scientific fields, calling for researchers able to show the potential and the advance of machine learning algorithms to make accurate computational predictions in health care datasets and in patient-oriented biological datasets.

Topics of interest include:

• Machine learning methods applied to health care and biomedical datasets
• Machine learning methods applied to genetics and epigenomics datasets, to understand the conditions of healthy and/or sick patients
• Machine learning methods applied to biological datasets to understand the underlying biomolecular scenario
• Machine learning software and tools in the health care and biological domain
• Statistical models to analyze health care, biomedical, and biological datasets
• Data mining applications in the heachairs & organizerslth care and biological domain

Special session organizers

Davide Chicco*, Princess Margaret Cancer Centre, Toronto, Ontario, Canada
Marco Masseroli**, Politecnico di Milano, Milan, Italy
Annalisa Barla, Università di Genova, Genoa, Italy
Anne-Christin Hauschild, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada

    

Reviewers

The organizers thank the paper reviewers for their extraordinary work:

• Anne-Christin Hauschild (Centre for Addiction and Mental Health)
• Arif Canakoglu (Politecnico di Milano)
• Davide Chicco (Princess Margaret Cancer Centre)
• Deena Gendoo (Nottingham Trent University)
• Joao Ribeiro Pinto (Universidade do Porto)
• Mehran Karimzadeh (University of Toronto)
• Mickael Mendez (University of Toronto)
• Wail Ba-Alawi (Princess Margaret Cancer Centre)

Paper format

Prospective authors should submit papers prepared according to the following instructions:

• The papers must be submitted in .pdf format (this is the only accepted format)
• The papers length should be at least 4 pages and should not exceed 6 pages
• Please use the CIBB 2018 LaTeX template (.zip archive here) for your papers. In case you have issues with LaTeX, you can use other programs (such as LibreOffice or Microsoft Word) to reproduce the format and style of the sample paper available in the LaTeX style. In any case, the submitted paper must be a .pdf file.
• Papers should adhere, as much as appropriate, to the following structure and sections: 
  1. Scientific background
  2. Materials and methods
  3. Results
  4. Conclusions
  5. References

The accepted papers will be distributed at the conference as .pdf files. At least one author of an accepted paper is required to register and present their paper at the conference.

Post conference publication

Authors of accepted papers will be invited to submit an extended version of their work to a post-conference monograph.

All the authors will be invited to prepare extended versions of their accepted paper to be submitted as chapter to a Springer Lecture Notes in Bionformatics (LNBI) containing the proceedings of the conference. Continuing the tradition of CIBB, the conference organizers are also planning to invite the best papers, as an alternative to the publication on LNBI, to a special issue of an international scientific journal (such as BMC Bioinformatics, as in the latest editions).

Examples of previous CIBB edition post-publications:

• Springer Lecture Notes in Bioinformatics (LNBI) book of CIBB 2016
• BMC Bioinformatics journal supplement of CIBB 2015 and CIBB 2016

        

Dates and deadlines

Paper submission deadline: 1st July 2018
Acceptance notification: 19th July 2018
Early registration due: 6th August 2018
Camera ready due: 6th August 2018
Conference: 6th, 7th, 8th September 2018

Share this call for papers

Please share this call for papers and the URL to this website:
https://davidechicco.github.io/cibb2018specialsession/

Contacts

For any question, please contact Davide Chicco at davidechicco(AT)davidechicco.it