… information about the patient’s cancer, allowing clinicians to make better-… cancers. This
study also exhibits a good survey of the machine or deep learning techniques used in cancer …

… their 10 or 7 mistakes to a error-free performance in the total 253 test samples, giving rise
to truly excellent diagnosis accuracy for ovarian cancer based on serum proteomic data. …

… cancer. The results of empirical research work done on the data based identification of
estimation models for cancer diagnoses … , and information about the diagnosis of tumors we have …

… In the following, we present some of the recent proposed CAD systems for breast cancer
detection or diagnosis on various modalities such as mammography, ultrasound, MRI, and …

… The rise of AI has given new vitality to liver surgery, as well as individualized treatment …
cancer diagnosis and treatment from six aspects: virtual assistants, medical imaging diagnosis, …

… of the various machine learning and deep learning models used for skin cancer diagnosis. …
Figure 7 conceptualizes the machine learning models in skin cancer diagnosis discussed in …

… of cancer. While early results are promising, this is a rapidly evolving field with new knowledge
emerging in both cancer … may be applied in cancer diagnosis, prognosis and treatment …

… diagnosis of breast cancer is an important, real-world medical problem. In this paper we focus
on the Wisconsin breast cancer diagnosis … as to automatically produce diagnostic systems. …

… for breast cancer diagnosis in the presence and absence of clinical features. This evaluation
is done within the context of training machine learning classifiers to predict the diagnostic of …

… , pathologists examine biopsies to make diagnostic … On the other hand, computational
diagnostic tools enable … steps in automated cancer diagnosis based on histopathology. These …