{'fraction_non_alphanumeric': 0.01384083044982699, 'fraction_numerical': 0.002306805074971165, 'mean_word_length': 5.382352941176471, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Specified Diagnosis of Breast Cancer on the basis of Immunogistochemical Images Analysis

The article shows that cancer is a global problem of the 21st century. The work provides the relevance of scientific research on the diagnosis automation. The object of research is breast cancer. The authors analyzed modern methods of automated diagnosis. It is shown that the main methods for making an automated diagnosis are convolutional neural networks, Naive Bayes, SVM, Decision Tree. The researchers analyzed the immunohistochemical method for clarifying the diagnosis based on histological analysis. Approach has been developed to a more specified diagnosis based on the analysis of immunohistochemical images. The module for automated diagnosis is implemented in software. Computer experiments have been carried out to clarify the diagnosis of breast cancer subtypes.