An official website of the United States government
The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.
The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.
- Publications
- Account settings
Trending Articles
- Streptococcus anginosus promotes gastric inflammation, atrophy, and tumorigenesis in mice. Fu K, et al. Cell. 2024. PMID: 39461336 No abstract available.
- Tobacco Smoke Plays an Important Role in Initiation and Development of Lung Cancer by Promoting the Characteristics of Cancer Stem Cells. Lu L, et al. Cancer Manag Res. 2020. PMID: 33116833 Free PMC article. Review.
- Amino acid is a major carbon source for hepatic lipogenesis. Liao Y, et al. Cell Metab. 2024. PMID: 39461344
- CAR-Macrophage Therapy Alleviates Myocardial Ischemia-Reperfusion Injury. Wang J, et al. Circ Res. 2024. PMID: 39465245
- Transcatheter Aortic-Valve Replacement for Asymptomatic Severe Aortic Stenosis. Généreux P, et al. N Engl J Med. 2024. PMID: 39466903
Latest Literature
- Cochrane Database Syst Rev (1)
- Gastroenterology (2)
- J Am Coll Cardiol (8)
- J Biol Chem (9)
- J Neurosci (2)
- Nature (53)
NCBI Literature Resources
MeSH PMC Bookshelf Disclaimer
The PubMed wordmark and PubMed logo are registered trademarks of the U.S. Department of Health and Human Services (HHS). Unauthorized use of these marks is strictly prohibited.
IMAGES
VIDEO
COMMENTS
In this paper, a performance comparison between different machine learning algorithms: Support Vector Machine (SVM), Decision Tree (C4.5), Naive Bayes (NB) and k …
Our objective is to predict and diagnosis breast cancer, using machine-learning algorithms, and find out the most effective based on the performance of each classifier in terms …
We reviewed the first 300 articles on machine learning (ML) for breast cancer (BC) risk prediction, focusing on those used for risk prediction. The best methods for each …
The motive of this research is to find out the best machine-learning technique which provides the most accuracy for the detection of breast cancer. The precision of machine learning models...
Breast cancer has two types—benign and malignant. This paper focuses on machine learning prediction algorithms that can be used for helping in early detection and classification.
This study presents a thorough mathematical framework that incorporates machine learning optimization to model the interactions between breast cancer cells and the …
This paper presented a comparative study of five machine learning techniques for the prediction of breast cancer, namely support vector machine, K-nearest neighbors, random forests, artificial neural networks, and …
Background: For patients with breast cancer undergoing neoadjuvant chemotherapy (NACT), most of the existing prediction models of pathologic complete response (pCR) using …