Suicide is the second leading cause of death of adolescents, yet research has not been able to surface many indicators with high predictive power. Machine …
Manual curation of primary literature is a common, time-intensive approach for identifying genes associated with a disease of interest. This project aims to minimize the …
Risk calculators for predicting mortality in stroke patients can be used to identify which patients require additional attention and could ultimately result in fewer deaths …
Cis-regulatory-modules are the “computational unit” of the gene regulatory network. CRMs are where transcription factors bind and activate the production of more transcription factors or …
Glioblastoma is an aggressive form of brain cancer that accounts for around 52% of all primary brain tumors. Accurate survival outcome prediction for glioblastoma is …
The iTrapz is an instrumented replacement trapezium that can convert in vivo strain gauge readings into loading data, then wirelessly transmit it. The device’s load …
Recent advances in deep learning have enabled new generative models for 3D objects, in particular manufactured shapes (e.g. chairs, tables, airplanes, cars, ...). The most …
This project seeks to evaluate the APACHE-II prognostic model for risk of in-hospital mortality among critical care patients by applying it to the MIMIC-III dataset1,2. …
Currently, there is a large focus worldwide to better identify sepsis in the clinical setting. We aimed to build predictive algorithms for diagnosing sepsis from …
To better understand and identify the four top quark production event in proton-proton collisions at the Large Hadron Collider, a machine learning approach is used. …
Surgical site infection (SSI) is a rare, but serious complication for patients undergoing total joint replacements. We aimed to create a machine learning algorithm that …