Artificial intelligence in cancer imaging: clinical challenges and applications

WL Bi, A Hosny, MB Schabath, ML Giger… - CA: a cancer journal …, 2019 - Wiley Online Library
Judgement, as one of the core tenets of medicine, relies upon the integration of multilayered
data with nuanced decision making. Cancer offers a unique context for medical decisions …

Artificial intelligence in cancer diagnosis and therapy: Current status and future perspective

M Sufyan, Z Shokat, UA Ashfaq - Computers in Biology and Medicine, 2023 - Elsevier
Artificial intelligence (AI) in healthcare plays a pivotal role in combating many fatal diseases,
such as skin, breast, and lung cancer. AI is an advanced form of technology that uses …

YOLO based breast masses detection and classification in full-field digital mammograms

GH Aly, M Marey, SA El-Sayed, MF Tolba - Computer methods and …, 2021 - Elsevier
Abstract Background and Objective With the recent development in deep learning since
2012, the use of Convolutional Neural Networks (CNNs) in bioinformatics, especially …

Diagnostic accuracy of digital screening mammography with and without computer-aided detection

CD Lehman, RD Wellman, DSM Buist… - JAMA internal …, 2015 - jamanetwork.com
Importance After the US Food and Drug Administration (FDA) approved computer-aided
detection (CAD) for mammography in 1998, and the Centers for Medicare and Medicaid …

Fragile algorithms and fallible decision-makers: lessons from the justice system

J Ludwig, S Mullainathan - Journal of Economic Perspectives, 2021 - aeaweb.org
Algorithms (in some form) are already widely used in the criminal justice system. We draw
lessons from this experience for what is to come for the rest of society as machine learning …

A deep feature based framework for breast masses classification

Z Jiao, X Gao, Y Wang, J Li - Neurocomputing, 2016 - Elsevier
Characteristic classification of mass plays a role of vital importance in diagnosis of breast
cancer. The existing computer aided diagnosis (CAD) methods used to benefit a lot from low …

Radiological images and machine learning: trends, perspectives, and prospects

Z Zhang, E Sejdić - Computers in biology and medicine, 2019 - Elsevier
The application of machine learning to radiological images is an increasingly active
research area that is expected to grow in the next five to ten years. Recent advances in …

Computer-aided diagnosis in medical imaging: historical review, current status and future potential

K Doi - Computerized medical imaging and graphics, 2007 - Elsevier
Computer-aided diagnosis (CAD) has become one of the major research subjects in
medical imaging and diagnostic radiology. In this article, the motivation and philosophy for …

Computer-aided detection/diagnosis of breast cancer in mammography and ultrasound: a review

A Jalalian, SBT Mashohor, HR Mahmud, MIB Saripan… - Clinical imaging, 2013 - Elsevier
Breast cancer is the most common form of cancer among women worldwide. Early detection
of breast cancer can increase treatment options and patients' survivability. Mammography is …

[图书][B] Digital image processing for medical applications

G Dougherty - 2009 - books.google.com
El procesamiento de imágenes es una práctica en la disciplina, y la mejor manera de
aprender es haciendo. Este texto toma su motivación de aplicaciones médicas y utiliza …