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.

Recent years have witnessed major breakthroughs in machine learning that is equipped with powerful optimization technologies. For example, the concept of “deep learning” often leads to automated feature discovery from data and it has achieved impressive performances than traditional learning methods when processing large unstructured corpora. For biomedical informatics needs, deep learning methods have recently made notable advances in processing brain-imaging data and making neuroscience discovery, although their utilities to more biomedical informatics use-cases still awaits further assessment. On a general note, biomedical data often feature large volumes, high dimensions, imbalance between classes, heterogeneous sources, noises, incompleteness, and rich contexts. Such demanding features are also driving the development of numerical optimization algorithms in tandem with that of machine learning algorithms.
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The BOOM workshop aims at catalyzing synergies among biomedical informatics, machine learning, and optimization. This workshop is targeting an audience of applied mathematicians, computer scientists, industrial engineers, bioinformaticians, computational biologists, clinicians and healthcare researchers who are interested in exploring the emerging and fascinating interdisciplinary topics. It is designed to foster exchange of ideas between often-disparate groups that are unaware of each other's research, and to stimulate fruitful collaborations among different disciplines.​