{"id":44563,"date":"2025-10-13T11:40:43","date_gmt":"2025-10-13T03:40:43","guid":{"rendered":"https:\/\/www.1ai.net\/?p=44563"},"modified":"2025-10-13T11:40:43","modified_gmt":"2025-10-13T03:40:43","slug":"%e8%85%be%e8%ae%af-ai-%e5%ae%9e%e7%8e%b0%e8%82%ba%e7%99%8c%e5%9f%ba%e5%9b%a0%e7%aa%81%e5%8f%98%e9%a2%84%e6%b5%8b%ef%bc%8c%e7%b2%be%e5%ba%a6%e6%9c%80%e9%ab%98-99","status":"publish","type":"post","link":"https:\/\/www.1ai.net\/en\/44563.html","title":{"rendered":"I'VE GOT THE HIGHEST ACCURACY OF 991 TP3T"},"content":{"rendered":"

The news of October 13 is thatTencent<\/a>Today, it is announced that the University of Guangzhou Institute of Respiratory Health developed jointly with Guangzhou Medical University Hospital No. 1\u00a0DeepGEM<\/a> Large pathology model<\/a><\/strong>, alreadyLung cancer<\/a>Large-scale validation of genetic mutation predictions -- just a routine pathological biopsy image, one minute for lung cancer genetic mutation predictions~99%<\/strong>.<\/p>\n

\"86d652edj00t41wtf00fmd000umxp\"<\/p>\n

IN OTHER WORDS, IT'S A NEW PATH THAT DOES NOT DEPEND ON GENE SEQUENCING, BUT ONLY PATHOLOGICAL IMAGES CAN USE AI TO PREDICT MUTATION. THE RESULTS OF THE TESTS, WHICH IN THE PAST WERE SET TO WAIT FOR ONE OR TWO WEEKS, ARE EXPECTED TO BE SEVERAL TIMES LOWER IN THE FUTURE OR ONLY A FEW MINUTES\u3002<\/p>\n

DeepGEM's core capability is based on AI's \"reading\" gene mutations from normal pathology images -<\/p>\n

Although pathological slices do not intuitively reflect mutation itself, a great deal of research has found a statistical correlation between morphological signals such as tumour cell sequencing, morphological characteristics, reaction of surrounding tissues, and certain genetic mutations. DeepGEM is the result of a lot of pathological data, in a typical imageCatch the details of what might mean a mutation<\/strong>.<\/p>\n

THE MODEL USES A MULTI-EXAMPLE LEARNING (MIL) STRUCTURE, WHICH DOES NOT REQUIRE A MANUAL ADVANCE MARKING OF THE TUMOR AREA, BUT RATHER A DIRECT INPUT OF THE WHOLE IMAGE INTO THE MODEL, WHERE AI WILL DETERMINE WHICH AREAS ARE OF INTEREST AND GIVE THE RESULTS OF THE PROJECTIONS ACCORDINGLY\u3002<\/p>\n

At the same time, the model also produces a \"spatial map\" of gene mutations, displaying mutations in different regions within the same tumor, and helping doctors to quickly identify areas with high mutations when observing slices, improving observation efficiency and supporting decision-making\u3002<\/p>\n

Of course, the pathological samples of different patients vary, either from post-operative to post-surgery, or from perforation to post-prevalence, even with some quality differences. DeepGEM took these realities into account at the beginning of its design, as long as it was a routine pathological slice, it was able to handle it, with a strong fit and low threshold\u3002<\/p>\n

At present, in multiple data setsDeepGEM's large model has a predictive accuracy of 78%-99%, which is already comparable to traditional genetic testing methods<\/strong>I don't know. In other words, when the test cycle is too long, the samples are insufficient, or the patient cannot afford to wait, the results can be quickly referenced through the DeepGEM model, which helps doctors to make decisions as quickly as possible\u3002<\/p>\n

1AI was informed from the announcement that, following the DeepGEM model run, the next steps were officially launched: an AI-based joint initiative will be established, with the release of the first hospital attached to Guangzhou Medical University, the Guangzhou Institute of Respiratory Health and Ginjiang MedicinePathology-Geomodular Large Model Platform<\/strong>IN ADDITION TO THIS, IT IS IMPORTANT TO PROMOTE THE APPLICATION OF AI TECHNOLOGY TO MORE PARTS OF THE POPULATION AND TO ASSIST IN THE DIAGNOSIS OF CANCER\u3002<\/p>","protected":false},"excerpt":{"rendered":"

On October 13th, it was announced today that the DeepGEM pathological model developed by the Life Sciences Laboratory in conjunction with Guangzhou Medical University Hospital No. 1 and Guangzhou Institute of Respiratory Health has been massively validated in the lung cancer genetic mutation prediction - only a routine pathological slice image, a genetic mutation of lung cancer prediction of 78%~99% within 1 minute. In other words, it's a new path that does not depend on gene sequencing, but only pathological images can use AI to predict mutation. The results of the tests, which in the past were set to wait for one or two weeks, are expected to be several times lower in the future or only a few minutes. DeepGEM's core capability is based on AI's \"reading\" gene mutations from normal pathology images - although<\/p>","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[146],"tags":[7720,7719,7718,323],"collection":[],"class_list":["post-44563","post","type-post","status-publish","format-standard","hentry","category-news","tag-deepgem","tag-7719","tag-7718","tag-323"],"acf":[],"_links":{"self":[{"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/posts\/44563","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/comments?post=44563"}],"version-history":[{"count":0,"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/posts\/44563\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/media?parent=44563"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/categories?post=44563"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/tags?post=44563"},{"taxonomy":"collection","embeddable":true,"href":"https:\/\/www.1ai.net\/en\/wp-json\/wp\/v2\/collection?post=44563"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}