IJCAI International Workshop on Biomedical infOrmatics with Optimization and Machine learning(IJCAI BOOM 2016)
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When : 2016-07-09
Where : US
Submission Deadline : 2016-04-18
Categories : Informatics , Machine Learning
IJCAI International Workshop on Biomedical infOrmatics with Optimization and Machine learning(IJCAI BOOM 2016)
July 9-11, 2016
US
Call For Papers
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.
Topics
- 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.
- 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.