Did my master thesis at Sahlgrenska University Hospital.
This master thesis describes a journaling system for compression ultrasonography and a clinical assessment system for deep vein thrombosis (DVT). We evaluate Support Vector Machines (SVM) models with linear- and radial basis function-kernels for predicting deep vein thrombosis, and for facilitating creation of new clinical DVT assessment.
Data from 159 patients where analysed, with our dataset, Wells Score with a high clinical probability have an accuracy of 58%, sensitivity 60% and specificity of 57% these figured should be compared to those of our base models accuracy of 81%, sensitivity 66% and specificity 84%. A 23 percentage point increase in accuracy.The diagnostic odds ratio went from 2.12 to 11.26. However a larger dataset is required to report anything conclusive.
As our system is both a journaling and prediction system, every patient examined helps the accuracy of the assessment.
2011-10 - 2012-4
Co-founder & Lead Developer
Throw is an Mac OS X application for transferring files in a more convenient and safe manner using SSL.
Used technologies: C, Objective-C, Cocoa, Xcode, Clang
2011-4 - 2012-4
iOS - Betslip compliment app
Showcasing a betslip compliment app written by me and my colleague. Uses offline SVM for OCR and ...
iOS - Proof Of Concept - Point of Sale
Proof Of Concept - Point of Sale (PoS) we did for the board of directors at Svenska Spel. The iOS...
iOS - Clinical Assessment for Deep Vein Thrombosis using Support Vector Machines