Results 51 to 60 of about 8,124,451 (335)

Study of microRNAs-21/221 as potential breast cancer biomarkers in Egyptian women [PDF]

, 2016
microRNAs (miRNAs) play an important role in cancer prognosis. They are small molecules, approximately 17–25 nucleotides in length, and their high stability in human serum supports their use as novel diagnostic biomarkers of cancer and other pathological
El Masry, Maha Rafik, Mohareb, Fady R., Motawi, Tarek Mohamed Kamal, Sadik, Nermin Abdel Hamid, Shaker, Olfat Gamil   +4 more
core   +1 more source

OncoTree: A Cancer Classification System for Precision Oncology.

JCO Clinical Cancer Informatics, 2021
PURPOSE Cancer classification is foundational for patient care and oncology research. Systems such as International Classification of Diseases for Oncology (ICD-O), Systematized Nomenclature of Medicine Clinical Terms (SNOMED-CT), and National Cancer ...
Ritika Kundra, Hongxin Zhang, R. Sheridan, S. Sirintrapun, Avery Wang, Angelica Ochoa, Manda Wilson, Benjamin E. Gross, Yichao Sun, Ramyasree Madupuri, B. Satravada, Dalicia Reales, E. Vakiani, H. Al-Ahmadie, A. Dogan, M. Arcila, A. Zehir, S. Maron, M. Berger, C. Viaplana, K. Janeway, Matthew Ducar, L. Sholl, S. Dogan, Philippe Bédard, Lea F. Surrey, Iker Huerga Sanchez, Aijazuddin Syed, A. Rema, D. Chakravarty, S. Suehnholz, Moriah H. Nissan, G. Iyer, R. Murali, N. Bouvier, R. Soslow, D. Hyman, A. Younes, A. Intlekofer, J. Harding, R. Carvajal, P. Sabbatini, G. Abou-Alfa, L. Morris, Y. Janjigian, M. Gallagher, Tara A Soumerai, I. Mellinghoff, A. Hakimi, M. Fury, J. Huse, A. Bagrodia, M. Hameed, S. Thomas, Stuart M. Gardos, E. Cerami, T. Mazor, P. Kumari, Pichai Raman, Priyanka Shivdasani, Suzanne P. MacFarland, S. Newman, A. Waanders, Jianjiong Gao, D. Solit, N. Schultz   +65 more
semanticscholar   +1 more source

Improve the performance of transfer learning without fine-tuning using dissimilarity-based multi-view learning for breast cancer histology images [PDF]

, 2018
Breast cancer is one of the most common types of cancer and leading cancer-related death causes for women. In the context of ICIAR 2018 Grand Challenge on Breast Cancer Histology Images, we compare one handcrafted feature extractor and five transfer ...
FA Spanhol, G Biau, H Aerts, J Bill, JK Chan, JS Meyer, NA Hamilton, T Araújo, TP Coroller   +8 more
core   +5 more sources

A transfer-learning approach to feature extraction from cancer transcriptomes with deep autoencoders [PDF]

, 2019
Publicado en Lecture Notes in Computer Science.The diagnosis and prognosis of cancer are among the more challenging tasks that oncology medicine deals with.
A Bashiri, GE Hinton, I Guyon, J Bergstra, JN Weinstein, JS Parker, K Kourou, N Srivastava, SC Schuster, SJ Pan, Y LeCun, Y Saeys, Y Xiao, Z Wang   +13 more
core   +1 more source

Unsupervised Hierarchical Classification Approach for Imprecise Data in the Breast Cancer Detection

Entropy, 2022
(1) Background: in recent years, a lot of the research of statistical methods focused on the classification problem in presence of imprecise data. A particular case of imprecise data is the interval-valued data. Following this research line, in this work
Mario Fordellone, Paolo Chiodini
doaj   +1 more source

A comprehensive investigation of multimodal deep learning fusion strategies for breast cancer classification

Artificial Intelligence Review
In breast cancer research, diverse data types and formats, such as radiological images, clinical records, histological data, and expression analysis, are employed.
F. Nakach, Ali Idri, Evgin Göçeri
semanticscholar   +1 more source

Richer fusion network for breast cancer classification based on multimodal data

BMC Medical Informatics and Decision Making, 2021
Deep learning algorithms significantly improve the accuracy of pathological image classification, but the accuracy of breast cancer classification using only single-mode pathological images still cannot meet the needs of clinical practice.
Rui Yan, Fa Zhang, Xiaosong Rao, Zhilong Lv, Jintao Li, Linglin Zhang, Shuang Liang, Yilin Li, Fei Ren, Chunhou Zheng, Jun Liang   +10 more
semanticscholar   +1 more source

HMGA1 in cancer: Cancer classification by location [PDF]

Journal of Cellular and Molecular Medicine, 2019
AbstractThe high mobility group A1 (HMGA1) gene plays an important role in numerous malignant cancers. HMGA1 is an oncofoetal gene, and we have a certain understanding of the biological function of HMGA1 based on its activities in various neoplasms.
Yuhong Wang, Lin Hu, Yushuang Zheng, Lingchuan Guo   +3 more
openaire   +2 more sources

RCCNet: An Efficient Convolutional Neural Network for Histological Routine Colon Cancer Nuclei Classification

, 2019
Efficient and precise classification of histological cell nuclei is of utmost importance due to its potential applications in the field of medical image analysis.
Babu, Kancharagunta Kishan, Basha, S H Shabbeer, Dubey, Shiv Ram, Ghosh, Soumen, Mukherjee, Snehasis, Pulabaigari, Viswanath   +5 more
core   +1 more source

Enhancement of Mammographic Images Using Histogram-Based Techniques for Their Classification Using CNN

Sensors, 2022
In the world, one in eight women will develop breast cancer. Men can also develop it, but less frequently. This condition starts with uncontrolled cell division brought on by a change in the genes that regulate cell division and growth, which leads to ...
Khalaf Alshamrani, Hassan A. Alshamrani, Fawaz F. Alqahtani, Bander S. Almutairi   +3 more
doaj   +1 more source