| |||||||||||||||
IEEE ICHI Healthcare Data 2021 : IEEE ICHI2021 - 1st Workshop on Machine Learning in Healthcare Data for Precision Medicine | |||||||||||||||
Link: http://healthcaredata.gsu.edu.tr/ | |||||||||||||||
| |||||||||||||||
Call For Papers | |||||||||||||||
Call For Paper
Precision medicine is a revolutionary advance in current healthcare transitioning from a one-size-fits-all approach towards a data-driven where medical decisions are evidence-based on individual patient characteristics, environment, and lifestyle. Precision medicine is deeply connected to and dependent on data science, specifically machine learning which have proven during recent years to be promising in predicting disease risk from available multidimensional clinical and biological data. In this context, electronic health records (EHRs) offer great promise for accelerating such predictive analysis by identifying similarities among patients based on their medical information, which is a key step in precision medicine. In addition, explanations supporting the output of a ML model are crucial in precision medicine, where experts require far more information from the model than a simple binary prediction for supporting their diagnosis. Therefore, eXplainable Artificial Intelligence (XAI) allows healthcare experts to make reasonable and data-driven decisions to provide more personalized and precise treatments. The general purpose of this workshop in IEEE ICHI 2021 conference is to bring together researchers, academicians and sector employees from different fields and disciplines and provide them an independent platform to exchange information on their researches, ideas and findings about healthcare data and its analytics. It is also aimed to encourage debate on how big data can effectively support the healthcare in terms of diagnosis, treatment and population health, and to develop a common understanding for research conducted in this multidisciplinary field. Topics of interest include, but are not limited to, the following: Health data collection and analysis for precision medicine Electronic health records (EHR) mining Pervasive and personalized healthcare information systems and services Analysis and visualization of biological and clinical data EXplainable Artificial Intelligence (XAI) on healthcare Personalized clinical decision support systems Context-aware systems in precision medicine Machine learning in medical diagnosis and management Machine Learning in sensing devices and wearable health information for precision medicine Application of big data analysis in precision medicine Examples of precision medicine in human disease treatment and prevention Special Session Organizers: Sultan Turhan (sturhan@gsu.edu.tr), PhD., Department of Computer Engineering, Galatasaray University Assist. Prof. Ozgun Pinarer (opinarer@gsu.edu.tr), Department of Computer Engineering, Galatasaray University Pedro A. Moreno-Sanchez (pedro.morenosanchez@seamk.fi), PhD., RDI Expert/Researcher - Seinäjoki University of Applied Sciences Important Dates: Paper submission deadline: 11.05.2021 Notification of acceptance: 15.05.2021 Camera-ready copy due: 21.05.2021 Conference website: ichi2021.institute4hi.org/authors/call-for-workshops/ Workshop web site: healthcaredata.gsu.edu.tr Submission Instructions: Please submit a full-length paper (up to 8 page IEEE 2-column format) through the online submission system. Papers should be formatted to IEEE Computer Society Proceedings Manuscript Formatting Guidelines. Detailed instructions for the authors can be found at the conference website. All submissions will be published in IEEE Xplore and indexed in other Abstracting and Indexing (A&I) databases. Accepted papers have an oral presentation slot at the conference. All accepted papers must be presented by one of the author/s in the conference to include the article in the proceedings. For more information about the submission, please visit the conference web site: https://ichi2021.institute4hi.org/authors/call-for-workshops/ If you have any questions about the workshop, please do not hesitate to contact us. |
|