Search Results - "Lagree, Andrew"

A review and comparison of breast tumor cell nuclei segmentation performances using deep convolutional neural networks by Lagree, Andrew, Mohebpour, Majidreza, Meti, Nicholas, Saednia, Khadijeh, Lu, Fang-I., Slodkowska, Elzbieta, Gandhi, Sonal, Rakovitch, Eileen, Shenfield, Alex, Sadeghi-Naini, Ali, Tran, William T.

“…Breast cancer is currently the second most common cause of cancer-related death in women. Presently, the clinical benchmark in cancer diagnosis is tissue…”
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Quantitative digital histopathology and machine learning to predict pathological complete response to chemotherapy in breast cancer patients using pre-treatment tumor biopsies by Saednia, Khadijeh, Lagree, Andrew, Alera, Marie A., Fleshner, Lauren, Shiner, Audrey, Law, Ethan, Law, Brianna, Dodington, David W., Lu, Fang-I, Tran, William T., Sadeghi-Naini, Ali

“…Complete pathological response (pCR) to neoadjuvant chemotherapy (NAC) is a prognostic factor for breast cancer (BC) patients and is correlated with improved…”
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Assessment of Digital Pathology Imaging Biomarkers Associated with Breast Cancer Histologic Grade by Lagree, Andrew, Shiner, Audrey, Alera, Marie Angeli, Fleshner, Lauren, Law, Ethan, Law, Brianna, Lu, Fang-I, Dodington, David, Gandhi, Sonal, Slodkowska, Elzbieta A, Shenfield, Alex, Jerzak, Katarzyna J, Sadeghi-Naini, Ali, Tran, William T

“…Evaluating histologic grade for breast cancer diagnosis is standard and associated with prognostic outcomes. Current challenges include the time required for…”
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Predictive quantitative ultrasound radiomic markers associated with treatment response in head and neck cancer by Tran, William T, Suraweera, Harini, Quaioit, Karina, Cardenas, Daniel, Leong, Kai X, Karam, Irene, Poon, Ian, Jang, Deok, Sannachi, Lakshmanan, Gangeh, Mehrdad, Tabbarah, Sami, Lagree, Andrew, Sadeghi-Naini, Ali, Czarnota, Gregory J

“…We aimed to identify quantitative ultrasound (QUS)-radiomic markers to predict radiotherapy response in metastatic lymph nodes of head and neck cancer…”
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Quantitative Thermal Imaging Biomarkers to Detect Acute Skin Toxicity From Breast Radiation Therapy Using Supervised Machine Learning by Saednia, Khadijeh, Tabbarah, Sami, Lagree, Andrew, Wu, Tina, Klein, Jonathan, Garcia, Eduardo, Hall, Michael, Chow, Edward, Rakovitch, Eileen, Childs, Charmaine, Sadeghi-Naini, Ali, Tran, William T.

“…Radiation-induced dermatitis is a common side effect of breast radiation therapy (RT). Current methods to evaluate breast skin toxicity include clinical…”
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Analysis of tumor nuclear features using artificial intelligence to predict response to neoadjuvant chemotherapy in high-risk breast cancer patients by Dodington, David W., Lagree, Andrew, Tabbarah, Sami, Mohebpour, Majid, Sadeghi-Naini, Ali, Tran, William T., Lu, Fang-I

“…Purpose Neoadjuvant chemotherapy (NAC) is used to treat patients with high-risk breast cancer. The tumor response to NAC can be classified as either a…”
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Drivers of Emergency Department Use Among Oncology Patients in the Era of Novel Cancer Therapeutics: A Systematic Review by Fleshner, Lauren, Lagree, Andrew, Shiner, Audrey, Alera, Marie Angeli, Bielecki, Mateusz, Grant, Robert, Kiss, Alex, Krzyzanowska, Monika K, Cheng, Ivy, Tran, William T, Gandhi, Sonal

“…Patients diagnosed with cancer are frequent users of the emergency department (ED). While many visits are unavoidable, a significant portion may be potentially…”
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Personalized Breast Cancer Treatments Using Artificial Intelligence in Radiomics and Pathomics by Tran, William T., Jerzak, Katarzyna, Lu, Fang-I, Klein, Jonathan, Tabbarah, Sami, Lagree, Andrew, Wu, Tina, Rosado-Mendez, Ivan, Law, Ethan, Saednia, Khadijeh, Sadeghi-Naini, Ali

“…Progress in computing power and advances in medical imaging over recent decades have culminated in new opportunities for artificial intelligence (AI), computer…”
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Machine learning analysis of breast ultrasound to classify triple negative and HER2+ breast cancer subtypes by Ferre, Romuald, Elst, Janne, Senthilnathan, Seanthan, Lagree, Andrew, Tabbarah, Sami, Lu, Fang-I, Sadeghi-Naini, Ali, Tran, William T, Curpen, Belinda

“…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…”
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Predictive Models for Neoadjuvant Chemotherapy Response in Breast Cancer Patients Using Quantitative Digital Pathology Imaging Biomarkers by Wu, Tina, Tabbarah, Sami, Lagree, Andrew, Tran, William

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Identifying Oncology Patients at High Risk for Potentially Preventable Emergency Department Visits Using a Novel Definition by Fleshner, Lauren, Gandhi, Sonal, Lagree, Andrew, Boulard, Louise, Grant, Robert C, Kiss, Alex, Krzyzanowska, Monika K, Cheng, Ivy, Tran, William T

“…Patients with cancer visit the emergency department (ED) frequently. While some ED visits are necessary, others may be potentially preventable ED visits…”
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Comparative Evaluation of Tumor-Infiltrating Lymphocytes in Companion Animals: Immuno-Oncology as a Relevant Translational Model for Cancer Therapy by Pinard, Christopher J, Lagree, Andrew, Lu, Fang-I, Klein, Jonathan, Oblak, Michelle L, Salgado, Roberto, Cardenas, Juan Carlos Pinto, Brunetti, Barbara, Muscatello, Luisa Vera, Sarli, Giuseppe, Foschini, Maria Pia, Hardas, Alexandros, Castillo, Simon P, AbdulJabbar, Khalid, Yuan, Yinyin, Moore, David A, Tran, William T

“…Despite the important role of preclinical experiments to characterize tumor biology and molecular pathways, there are ongoing challenges to model the tumor…”
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Predicting Patterns of Distant Metastasis in Breast Cancer Patients following Local Regional Therapy Using Machine Learning by Shiner, Audrey, Kiss, Alex, Saednia, Khadijeh, Jerzak, Katarzyna J, Gandhi, Sonal, Lu, Fang-I, Emmenegger, Urban, Fleshner, Lauren, Lagree, Andrew, Alera, Marie Angeli, Bielecki, Mateusz, Law, Ethan, Law, Brianna, Kam, Dylan, Klein, Jonathan, Pinard, Christopher J, Shenfield, Alex, Sadeghi-Naini, Ali, Tran, William T

“…Up to 30% of breast cancer (BC) patients will develop distant metastases (DM), for which there is no cure. Here, statistical and machine learning (ML) models…”
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Thermoradiomic Markers of Radiation-Induced Skin Toxicity: Updated Results of a Phase II Study by Saednia, Khadijeh, Tabbarah, Sami, Lagree, Andrew, Wu, Tina, Klein, Jonathan, Garcia, Eduardo, Hall, Michael, Chow, Edward, Rakovitch, Eileen, Childs, Charmaine, Sadeghi-Naini, Ali, Tran, William T.

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