MAI 2014 - The AAAI 2014 Workshop on Modern Artificial Intelligence for Health Analytics

The proliferation of health-related information presents unprecedented opportunities to improve patient care. However, medical experts are currently overwhelmed by information, and existing artificial intelligence (AI) technologies are often inadequate for the challenges associated with analyzing clinical data. Novel computational methods are needed to process, organize, and make sense of these data. The objective of this workshop is to discuss computational methods that transform healthcare data into knowledge that ultimately improves patient care. Moreover, this workshop will focus on community building, by bringing together AI researchers interested in health and physicians interested in AI. The workshop will include a structured discussion around venues for this sort of emerging, interdisciplinary work. It will also include invited talks by leaders in the field.
Topics
We solicit papers in three tracks (further detailed below): (1) novel AI methods for healthcare, (2) clinical applications of AI, and (3) open AI challenges in health. We are particularly interested in work done in collaboration with clinicians and clinical researchers. Potential topics include:
Machine Learning
Predicting individual patient outcomes from past data
Patient risk stratification and clustering
Handling core methodological challenges (for example, data sparsity)
Exploiting resources to augment training data
Computer Vision
Vitals monitoring
Medical imaging
Brain imaging (fMRI)
Natural Language Processing
Extracting structured data from free-text (for example, clinical notes)
Biomedical text classification
Parsing biomedical literature
Information Retrieval and Organization
Identifying relevant literature
Clinical question answering
Ontology learning
We define healthcare information broadly, including heterogeneous data such as clinical trial results, patient health records, genomic data, wearable health monitor outputs, online physician reviews, and medical images.