Big Data and Machine Learning to Advance Medicine | AIChE

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Big Data and Machine Learning to Advance Medicine

Chair(s)

Shekhar, K., Broad Institute of MIT and Harvard

Co-chair(s)

Kurian, V., University Fo Delaware

Machine learning and big data combined with bioinformatics techniques are revolutionizing medicine from development of artificial organs to novel contrast agents for imaging and treatment. This session highlights these important advancements.

Presentations

8:00 AM
(284a) Data-Driven QSAR Modeling for the Iterative Identification of Chemical Motifs from Limited Data
8:19 AM
(284b) Single Sequence Prediction of Protein Structure and Impacts on Computational Protein Design
8:38 AM
(284c) Hierarchical Graph-Based Representation Drives Prediction of Stapled Peptide Drug-like Properties
8:57 AM
(284d) Data-Driven Approach for the Prediction of MHC Class II Epitopes Using Oscillations of Physicochemical Properties
9:16 AM
(284e) Automated Detection of Apoptotic Bodies in Label-Free Time-Lapse High-Throughput Microscopy Using Deep Convolutional Neural Networks
9:35 AM
(284f) Single-Cell Transcriptomic Analysis of Neural Development
9:54 AM
(284g) Structure-Guided Functional Phylogenetic Trees of Human Channel Proteins and Kinases for Drug Discovery
10:13 AM
(284h) Machine Learning Enabled Cancer and Immune Cells Segmentation on Clinical Images

Topics 

Medicine

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Pricing

Individuals

AIChE Pro Members $150.00
AIChE Emeritus Members $105.00
AIChE Graduate Student Members Free
AIChE Undergraduate Student Members Free
AIChE Explorer Members $225.00
Non-Members $225.00

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