{"id":1264,"date":"2021-07-23T10:37:11","date_gmt":"2021-07-23T08:37:11","guid":{"rendered":"https:\/\/www.iit.cnr.it\/?post_type=news&p=1264"},"modified":"2021-07-23T10:37:12","modified_gmt":"2021-07-23T08:37:12","slug":"artificial-intelligence-could-be-helpful-against-breast-cancer","status":"publish","type":"news","link":"https:\/\/www.iit.cnr.it\/en\/news\/artificial-intelligence-could-be-helpful-against-breast-cancer\/","title":{"rendered":"Artificial intelligence could be helpful against breast cancer"},"content":{"rendered":"\n

It is estimated that for 2020 in the US the expected number of new cases of breast cancer in female patients is about 276,000 (30% of all new tumor cases in female patients) and the expected number of deaths caused by breast cancer in female patients is about 42,000 (15% of all deaths due to tumors in female patients), thus making breast cancer the first type of cancer for the number of new cases<\/strong>, and the second type of cancer as cause of death in female patients. Similar rankings are observed in Europe and China.

For a patient with breast cancer who has undergone surgery, it is essential to decide on a post-operative treatment<\/strong> that prevents the recurrence of the tumor disease and the formation of metastases. Bioinformatics intervenes here, alongside the so-called precision medicine<\/strong>, precisely to help oncologists calculate the real effectiveness of the proposed treatments and the patient’s survival prospects.

A study signed by Marco Pellegrini<\/a>, IIT-CNR Research Director, has recently been published on Scientific Reports<\/a>, a journal of the Nature group, and can represent an important milestone in this sector<\/strong>. The article, entitled “Accurate prediction of breast cancer survival through coherent voting networks with gene expression profiling”<\/em>, describes how Pellegrini identified a new classification method supervised by machine learning<\/strong>. Pellegrini applied it to survival prediction at 5 years for patients with surgically removed breast cancer, using gene expression levels measured from tumor samples and obviously taking into account post-operation therapies. More than 2000 data <\/strong>from a list of cancer patients were used to train, validate and test artificial intelligence: the final result indicates a predictive capacity superior to that of the other methods currently in use<\/strong>.<\/p>\n\n\n\n

“Our methodology followed two directions”<\/em>, explains Marco Pellegrini. “On the one hand we drew on genetic sequencing and biomarkers of excised tissue samples; on the other hand we inserted and analyzed these data in a “predictor”, an artificial intelligence tool based on a new algorithm. This made it possible to achieve a prediction accuracy of 80% – 90%”<\/em>.<\/p>\n\n\n\n

This new methodology identified by Pellegrini can provide an important contribution to clinical decisions on breast cancer therapy<\/strong> and give doctors an additional tool to personalize therapies and increase the chances of survival of their patients. For this reason, the discovery was filed for a patent application<\/strong> in Italy, the United States and the European Community.<\/p>\n","protected":false},"featured_media":1209,"template":"","categories":[],"tags":[68,11,13,154,156,155,153],"class_list":["post-1264","news","type-news","status-publish","has-post-thumbnail","hentry","tag-ai-2","tag-bioinformatics","tag-biology","tag-brest-cancer","tag-computational-biology","tag-ehealth","tag-machine-learning-2"],"acf":[],"_links":{"self":[{"href":"https:\/\/www.iit.cnr.it\/en\/wp-json\/wp\/v2\/news\/1264","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.iit.cnr.it\/en\/wp-json\/wp\/v2\/news"}],"about":[{"href":"https:\/\/www.iit.cnr.it\/en\/wp-json\/wp\/v2\/types\/news"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.iit.cnr.it\/en\/wp-json\/wp\/v2\/media\/1209"}],"wp:attachment":[{"href":"https:\/\/www.iit.cnr.it\/en\/wp-json\/wp\/v2\/media?parent=1264"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.iit.cnr.it\/en\/wp-json\/wp\/v2\/categories?post=1264"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.iit.cnr.it\/en\/wp-json\/wp\/v2\/tags?post=1264"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}