IJCAI International Workshop on Biomedical infOrmatics with Optimization and Machine learning (BOOM)

Country: USA

City: New York

Abstr. due: 18.04.2016

Dates: 09.07.16 — 11.07.16

Area Of Sciences: Medicine;

Organizing comittee e-mail: ijcai1boom@gmail.com

Organizers: EURASIP

 

Fast-growing biomedical and healthcare data have encompassed multiple scales ranging from molecules, individuals, to populations and have connected various entities in healthcare systems (providers, pharma, payers) with increasing bandwidth, depth, and resolution. Those data are becoming an enabling resource for accelerating basic science discoveries and facilitating evidence-based clinical solutions. Meanwhile, the sheer volume and complexity of the data present major barriers toward their translation into effective clinical actions. There is thus a compelling demand for novel algorithms, including machine learning, data mining and optimization, that specifically tackle the unique challenges associated with biomedical and healthcare data and allow decision-makers and stakeholders to better interpret and exploit the data.

The First International Workshop on Biomedical infOrmatics with Optimization and Machine learning (BOOM), which will be held in conjunction with the 25th International Joint Conference on Artificial Intelligence (IJCAI), aims at catalyzing synergies among biomedical informatics, machine learning, and optimization as well as fostering interactions among a diverse audience of applied mathematicians, computer scientists, industrial engineers, bioinformaticians, computational biologists, clinicians and healthcare researchers.

BOOM-16 solicits (1) full papers that describe original research work that have not been published before, which will be published in a special issue of EURASIP Journal on Bioinformatics and Systems Biology (JBSB; see http://www.bsb.eurasipjournals.com/about...) and (2) short abstracts that either highlight significant works that have been published or accepted recently or report unpublished research findings, which will be included in workshop proceedings.

All submissions will be considered for oral and poster presentations at BOOM. The decision on presentation format for accepted submissions will be based primarily on an assessment of breadth of interest, and the construction of balanced and topically coherent sessions, while full papers will be given some priority for oral presentations. We will give out best presentation awards sponsored by Microsoft. We are also seeking funding for travel awards for students or postdocs.




Topics of interest

We encourage submissions from, but not limited to, the following inter-linked areas:

Category I: Machine Learning and Optimization Algorithms

● Applying cutting-edge machine learning (e.g., deep learning) and optimization techniques to tackle real-world medical and healthcare problems.

● Addressing challenges and roadblocks in biomedical informatics with reference to the data-driven machine learning, such as imbalanced dataset, weakly-structured or unstructured data, noisy and ambiguous labeling, and more.

● Designing novel, applicable numerical optimization algorithms for biomedical data, that is usually large-scale, high-dimensional, heterogeneous, and noisy.

● Re-visiting traditional machine learning topics such as clustering, classification, regression and dimension reduction, that find application values in newly-emerging biomedical informatic problems.

● Other closely-related disciplines, such as image processing, data mining, new computing technologies and paradigms (e.g., cloud computing), control theory, and system engineering.

Category II: Biomedical Informatics Applications

● Computational Biology, including the advanced interpretation of critical biological findings, using databases and cutting-edge computational infrastructure.

● Clinical Informatics, including the scenarios of using computation and data for health care, spanning medicine, dentistry, nursing, pharmacy, and allied health.

● Public Health Informatics, including the studies of patients and populations to improve the public health system and to elucidate epidemiology.

We encourage papers with important new insights and experiences at the intersection of machine learning, optimization and bioinformatics. Those contributions should shed light on at least one topic mentioned above, while the above topics have obvious overlaps. For topics in Category I, we invite both theoretically novel and application-driven papers. For those in Category II, the idea is to keep the interested application domain focused yet broad, echoing multiple scales, ranging from molecules, individuals, to populations.

Conference Web-Site: http://www.ijcai-boom.org/

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