From patterns to patients: Advances in clinical machine learning for cancer diagnosis, prognosis, and treatment
Machine learning (ML) is increasingly used in clinical oncology to diagnose cancers, predict
patient outcomes, and inform treatment planning. Here, we review recent applications of ML …
patient outcomes, and inform treatment planning. Here, we review recent applications of ML …
Artificial intelligence and machine learning in cancer imaging
An increasing array of tools is being developed using artificial intelligence (AI) and machine
learning (ML) for cancer imaging. The development of an optimal tool requires …
learning (ML) for cancer imaging. The development of an optimal tool requires …
Breast cancer screening for women at higher-than-average risk: updated recommendations from the ACR
Early detection decreases breast cancer death. The ACR recommends annual screening
beginning at age 40 for women of average risk and earlier and/or more intensive screening …
beginning at age 40 for women of average risk and earlier and/or more intensive screening …
[HTML][HTML] Application of deep learning in breast cancer imaging
This review gives an overview of the current state of deep learning research in breast cancer
imaging. Breast imaging plays a major role in detecting breast cancer at an earlier stage, as …
imaging. Breast imaging plays a major role in detecting breast cancer at an earlier stage, as …
Toward robust mammography-based models for breast cancer risk
Improved breast cancer risk models enable targeted screening strategies that achieve
earlier detection and less screening harm than existing guidelines. To bring deep learning …
earlier detection and less screening harm than existing guidelines. To bring deep learning …
[HTML][HTML] Artificial intelligence for breast cancer detection in mammography and digital breast tomosynthesis: State of the art
Screening for breast cancer with mammography has been introduced in various countries
over the last 30 years, initially using analog screen-film-based systems and, over the last 20 …
over the last 30 years, initially using analog screen-film-based systems and, over the last 20 …
Toward generalizability in the deployment of artificial intelligence in radiology: role of computation stress testing to overcome underspecification
T Eche, LH Schwartz, FZ Mokrane… - Radiology: Artificial …, 2021 - pubs.rsna.org
The clinical deployment of artificial intelligence (AI) applications in medical imaging is
perhaps the greatest challenge facing radiology in the next decade. One of the main …
perhaps the greatest challenge facing radiology in the next decade. One of the main …
Predicting breast cancer 5-year survival using machine learning: A systematic review
J Li, Z Zhou, J Dong, Y Fu, Y Li, Z Luan, X Peng - PloS one, 2021 - journals.plos.org
Background Accurately predicting the survival rate of breast cancer patients is a major issue
for cancer researchers. Machine learning (ML) has attracted much attention with the hope …
for cancer researchers. Machine learning (ML) has attracted much attention with the hope …
Novel approaches to screening for breast cancer
Screening for breast cancer reduces breast cancer–related mortality and earlier detection
facilitates less aggressive treatment. Unfortunately, current screening modalities are …
facilitates less aggressive treatment. Unfortunately, current screening modalities are …
[HTML][HTML] Artificial intelligence and early detection of pancreatic cancer: 2020 summative review
Despite considerable research efforts, pancreatic cancer is associated with a dire prognosis
and a 5-year survival rate of only 10%. Early symptoms of the disease are mostly …
and a 5-year survival rate of only 10%. Early symptoms of the disease are mostly …