OBJECTIVES: Early diagnosis of triple-negative (TN) and human epidermal growth factor receptor 2 positive (HER2+) breast cancer is important due to its increased risk of micrometastatic spread necessitating early treatment and for guiding targeted th...
MOTIVATION: Predicting pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) in triple-negative breast cancer (TNBC) patients accurately is direly needed for clinical decision making. pCR is also regarded as a strong predictor of ove...
Triple-negative breast cancer (TNBC) has been a challenging breast cancer subtype for oncological therapy. Normally, it can be classified into different molecular subtypes. Accurate and stable classification of the six subtypes is essential for perso...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2019
Recurrence is a significant prognostic factor in patients with triple negative breast cancer, and the ability to accurately predict it is essential for treatment optimization. Machine learning is a preferred strategy for recurrence prediction. Most c...
PURPOSE: The majority of patients with cancer receive treatments that are minimally informed by omics data. We propose a precision medicine computational framework, PANOPLY (Precision Cancer Genomic Report: Single Sample Inventory), to identify and p...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Aug 1, 2015
A major impediment to anti-cancer drug development is the lack of a reliable and inexpensive tumor model to test the efficacy of candidate compounds. This need has emerged due to the insufficiency of widely-used monolayer cultures to predict drug eff...
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