Revolutionizing Breast Imaging: Artificial Intelligence’s Role in Precisely Differentiating Benign from Malignant Lesions

Vivianne Freitas; Renata Pinto

Authors

Vivianne Freitas, MD, MSc. Assistant Professor of University of Toronto, Toronto, ON
Renata Pinto, MD, MSc. Assistant Physician at Brazil National Cancer Institute (INCA)

Abstract

Recent advancements in artificial intelligence (AI) have leveraged computer science with large datasets to improve predictive and classification capabilities, which are crucial for problem‑solving in radiology. Machine Learning (ML), the driving force behind AI’s effectiveness, harnesses computational models and algorithms to analyze raw data for classification and prediction tasks. AI utilizes a multi-layered network of interconnected nodes emulating the intricate neuronal structure of the human brain. These include an input layer that initially receives data, a hidden layer that discerns data patterns, and an output layer that presents the results of the processed data.

Author Biographies

Vivianne Freitas, MD, MSc., Assistant Professor of University of Toronto, Toronto, ON

Dr. Vivianne Freitas is an Assistant Professor at the University of Toronto, and a staff member of the Joint Department of Medical Imaging (JDMI), Breast Division, Toronto, has held a full-time appointment with the University since 2017.

Renata Pinto, MD, MSc., Assistant Physician at Brazil National Cancer Institute (INCA)

Dr. Renata Pinto is a Breast Imaging Radiologist currently a Postdoctoral Fellow at Lunenfeld-Tanenbaum Research Institute, University of Toronto, and leading the Breast Imaging Department at Unimed Hospital since 2010 and Brazil National Cancer Institute (INCA) since 2011.

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Revolutionizing Breast Imaging: Artificial Intelligence’s Role in Precisely Differentiating Benign from Malignant Lesions

Authors

Abstract

Author Biographies

Vivianne Freitas, MD, MSc., Assistant Professor of University of Toronto, Toronto, ON

Renata Pinto, MD, MSc., Assistant Physician at Brazil National Cancer Institute (INCA)

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