Engineering Commons^™

Modular Machine Learning Methods For Computer-Aided Diagnosis Of Breast Cancer, Mia Kathleen Markey '94

Doctoral Dissertations

The purpose of this study was to improve breast cancer diagnosis by reducing the number of benign biopsies performed. To this end, we investigated modular and ensemble systems of machine learning methods for computer-aided diagnosis (CAD) of breast cancer. A modular system partitions the input space into smaller domains, each of which is handled by a local model. An ensemble system uses multiple models for the same cases and combines the models' predictions.

Five supervised machine learning techniques (LDA, SVM, BP-ANN, CBR, CART) were trained to predict the biopsy outcome from mammographic findings (BIRADS™) and patient age based on a …

Using Commercial Finite Element Code Called Abaqus In Modeling Hybrid Constrained Layers Damping Beam Structure And Quantitative Determination Of The Stability Of Implant-Bone Interface Using Resonance Frequency Analysis, Daniel Delgado Jr.

Theses and Dissertations - UTB/UTPA

In Chapter 1, it has been demonstrated that the damping treatments for beam and plate structures are effective, and the vibrational behaviors of the systems considered are influenced by many geometrical and material parameters. This has led to an interest in developing advanced “intelligent” structures. In the past, passive and active damping mechanisms have been used to reduce vibration. The uses of passive constrained layers are limited, but it has dissipative qualities for all the modes of the structure; and the uses of active constrained layers are limited to a single mode control. Recent published papers, many have suggested that …