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Full-Text Articles in Biochemistry, Biophysics, and Structural Biology
Predicting Outcomes Of Hormone And Chemotherapy In The Molecular Taxonomy Of Breast Cancer International Consortium (Metabric) Study By Biochemically-Inspired Machine Learning, Peter Rogan, Eliseos J. Mucaki, Katherina Baranova, Huy Q. Pham, Iman Rezaeian, Dimo Angelov, Alioune Ngom, Luis Rueda
Predicting Outcomes Of Hormone And Chemotherapy In The Molecular Taxonomy Of Breast Cancer International Consortium (Metabric) Study By Biochemically-Inspired Machine Learning, Peter Rogan, Eliseos J. Mucaki, Katherina Baranova, Huy Q. Pham, Iman Rezaeian, Dimo Angelov, Alioune Ngom, Luis Rueda
Biochemistry Publications
Genomic aberrations and gene expression-defined subtypes in the large METABRIC patient cohort have been used to stratify and predict survival. The present study used normalized gene expression signatures of paclitaxel drug response to predict outcome for different survival times in METABRIC patients receiving hormone (HT) and, in some cases, chemotherapy (CT) agents. This machine learning method, which distinguishes sensitivity vs. resistance in breast cancer cell lines and validates predictions in patients; was also used to derive gene signatures of other HT (tamoxifen) and CT agents (methotrexate, epirubicin, doxorubicin, and 5-fluorouracil) used in METABRIC. Paclitaxel gene signatures exhibited the best performance, …
First-Order Statistical Speckle Models Improve Robustness And Reproducibility Of Contrast-Enhanced Ultrasound Perfusion Estimates, Matthew R. Lowerison
First-Order Statistical Speckle Models Improve Robustness And Reproducibility Of Contrast-Enhanced Ultrasound Perfusion Estimates, Matthew R. Lowerison
Electronic Thesis and Dissertation Repository
Contrast-enhanced ultrasound (CEUS) permits the quantification and monitoring of adaptive tumor responses in the face of anti-angiogenic treatment, with the goal of informing targeted therapy. However, conventional CEUS image analysis relies on mean signal intensity as an estimate of tracer concentration in indicator-dilution modeling. This discounts additional information that may be available from the first-order speckle statistics in a CEUS image. Heterogeneous vascular networks, typical of tumor-induced angiogenesis, lead to heterogeneous contrast enhancement of the imaged tumor cross-section.
To address this, a linear (B-mode) processing approach was developed to quantify the change in the first-order speckle statistics of B-mode cine …