J Liao, X Li, Y Gan, S Han, P Rong, W Wang… - Frontiers in …, 2023 - frontiersin.org
… Since NGS produces high-dimensional and complex data, NGS methods for cancer diagnosis usually need higher-dimensional and deeper-seated data coverage to enhance the …
… This research focuses on the diagnosis of cervical cancer by using the data mining techniques. Cervical cancer is one of the most fatal cancer, the reason being the delay in diagnosis of …
EJ Feuer, LM Wun - American journal of epidemiology, 1992 - academic.oup.com
… This temporarily increased awareness of breast cancer screening is temporally associated with the diagnosis of breast cancer in several prominent public figures (including both Betty …
… cancer (PCa) is the most commonly diagnosedcancer among men in the United States. In this paper, we survey computer aided-diagnosis … detection and diagnosis of prostate cancer. …
… Constructing improved risk stratification models requires data and biological samples from large cohorts, ideally in prediagnostic populations that are followed for any cancerdiagnoses. …
… ensemble machine learning methods for the diagnosis of specific human cancer types. In fact, full-text English-language articles that focus on identifying one or more specific cancers …
S Li, Y Zhang, J Xu, L Li, Q Zeng, L Lin, Z Guo… - Applied Physics …, 2014 - pubs.aip.org
… method for prostate cancerdiagnosis, this study employs Ag-based SERS technique combined with SVM to classify serum SERS spectra between prostate cancer patients and normal …
MM Ershadi, ZR Rise, STA Niaki - Computers in Biology and Medicine, 2022 - Elsevier
… developed methods and machine-learning algorithms exist to cope with different cancers in today's world. Most of these methods help with a cancerdiagnosis and detect cancer lev…
… In order to overcome the complexity of cancer data, researchers have developed a variety of AI tools to help with cancerdiagnosis and treatment. As mentioned, a large number of AI …