#4. Human expert-level automated sleep stage prediction and feature discovery by deep convolutional neural networks.
Michael Sokolovsky, Francisco Guerrero, Sarun Paisarnsrisomsuk, Carolina Ruiz and Sergio Alvarez.

#9. Automatic Classification of Prostate Cancer Gleason Scores from Digitized Whole Slide Tissue Biopsies.
Hongming Xu, Sunho Park and Tae Hyun Hwang.

#10. Deep Learning Benchmarks on Gene Expression Data.
Matthew Mcdermott, Jennifer Wang, Wen Ning Zhao, Steven D. Sheridan, Peter Szolovits, Isaac Kohane, Stephen J. Haggarty and Roy Perlis.

#14. A Data-driven Approach to Predict Epileptic Seizures From Brain-wide Calcium Imaging Video Data.
Jingyi Zheng, Fushing Hsieh and Linqiang Ge.

#20. DeepNcFun: a deep-learning based approach for non-coding RNA functional prediction.
Teresa Maria Rosaria Noviello, Michele Ceccarelli and Luigi Cerulo.

#2. GRAFENE: Graphlet-based alignment-free network approach integrates 3D structural and sequence (residue order) data to improve protein structural comparison.
Khalique Newaz, Fazle Faisal, Julie Chaney, Jun Li, Scott Emrich, Patricia Clark and Tijana Milenkovic.

#12. Genomic positional conservation identifies topological anchor point RNAs linked to developmental loci.
Namshik Han.

#6. DeepRibo: precise gene annotation of prokaryotes using deep learning and ribosome profiling data.
Jim Clauwaert, Gerben Menschaert and Willem Waegeman.

#7. Adverse Event detection in Twitter: results from the WEB-RADR consortium.
Lucie Gattepaille, Tomas Bergvall, Sara Hedfors Vidlin and Johan Ellenius.

#8. Deep learning for de-identification of case narratives in reports of suspected adverse drug reactions.
Eva-Lisa Meldau, Sara Hedfors Vidlin, Lucie Gattepaille, Henric Taavola, Lovisa Sandberg, Yasunori Aoki and G. Niklas Norén.

#18. Opioid Data Analytics: Challenges and Opportunities.
Gowtham Atluri and Taehyun Hwang.