{"id":6361,"date":"2023-10-11T20:13:23","date_gmt":"2023-10-11T20:13:23","guid":{"rendered":"https:\/\/dailyai.com\/?p=6361"},"modified":"2023-10-11T20:21:52","modified_gmt":"2023-10-11T20:21:52","slug":"ai-models-helps-brain-surgeons-detect-and-analyze-tumor-types-on-the-fly","status":"publish","type":"post","link":"https:\/\/dailyai.com\/pt\/2023\/10\/ai-models-helps-brain-surgeons-detect-and-analyze-tumor-types-on-the-fly\/","title":{"rendered":"Novo modelo de IA ajuda os neurocirurgi\u00f5es a analisar tumores em tempo real"},"content":{"rendered":"

Os cirurgi\u00f5es cerebrais debatem-se frequentemente com decis\u00f5es cr\u00edticas durante o processo de remo\u00e7\u00e3o do tumor.\u00a0<\/b><\/p>\n

Agora, cientistas holandeses introduziram uma ferramenta de IA para ajudar o processo de tomada de decis\u00f5es intra-cir\u00fargicas, fornecendo aos cirurgi\u00f5es informa\u00e7\u00f5es ultra-r\u00e1pidas sobre os tipos e subtipos de tumores.<\/p>\n

De acordo com um recente <\/span>estudo publicado na Nature<\/span><\/a>A IA examina segmentos espec\u00edficos do ADN de um tumor, identificando estruturas qu\u00edmicas distintas. <\/span><\/p>\n

Esta an\u00e1lise fornece informa\u00e7\u00f5es sobre o tipo de tumor e, possivelmente, o seu subtipo. Esta informa\u00e7\u00e3o atempada pode orientar os cirurgi\u00f5es na sua abordagem \u00e0 opera\u00e7\u00e3o cir\u00fargica.<\/span><\/p>\n

\"\u00c9 imperativo que o subtipo de tumor seja conhecido na altura da cirurgia\", declarou Jeroen de Ridder, professor associado da UMC Utrecht. \"O que conseguimos agora, de forma \u00fanica, \u00e9 permitir que este diagn\u00f3stico muito fino, robusto e detalhado seja efectuado j\u00e1 durante a cirurgia.\"<\/span><\/p>\n

O seu sistema de aprendizagem profunda, denominado Sturgeon, foi sujeito a testes rigorosos. Em certos testes iniciais, a IA absteve-se de efetuar o diagn\u00f3stico devido a dados amb\u00edguos.<\/span><\/p>\n

No geral, os investigadores demonstraram a efic\u00e1cia do modelo em tempo real em 25 cirurgias, conseguindo um tempo de resposta r\u00e1pido para o diagn\u00f3stico inferior a 90 minutos, muito mais r\u00e1pido do que os m\u00e9todos tradicionais. 72% dos diagn\u00f3sticos estavam correctos, mas sete n\u00e3o atingiram o limiar de confian\u00e7a exigido.<\/p>\n

Embora o processo de diagn\u00f3stico padr\u00e3o envolva um exame microsc\u00f3pico de amostras de tumores cerebrais, a sequencia\u00e7\u00e3o gen\u00e9tica exaustiva oferece conhecimentos mais profundos. No entanto, como salientou o Dr. Alan Cohen, da Johns Hopkins, \"temos de come\u00e7ar o tratamento sem saber o que estamos a tratar\".<\/span><\/p>\n

O Dr. de Ridder explicou ainda as capacidades da IA: \"Consegue descobrir por si pr\u00f3pria o que est\u00e1 a ver e fazer uma classifica\u00e7\u00e3o robusta\".<\/span><\/p>\n

Ainda assim, persistem alguns desafios. A variabilidade dentro do tumor, o tamanho da amostra e certos tumores dif\u00edceis de identificar podem colocar dificuldades. A este respeito, Marc Pag\u00e8s-Gallego, coautor de um estudo, forneceu algum contexto sobre a forma como estas quest\u00f5es foram abordadas.<\/span><\/p>\n

O Dr. Sebastian Brandner, da University College London, comentou os aspectos pr\u00e1ticos, afirmando que \"a aplica\u00e7\u00e3o em si \u00e9 menos simples do que muitas vezes se sugere\".<\/span><\/p>\n

Embora a ferramenta represente um avan\u00e7o significativo, tem as suas limita\u00e7\u00f5es.\u00a0<\/span><\/p>\n

A<\/span>O Dr. Cohen admitiu que \"obtivemos alguns ganhos, mas n\u00e3o tantos no tratamento como na compreens\u00e3o do perfil molecular dos tumores\".<\/span><\/p>\n

Mais informa\u00e7\u00f5es sobre o estudo<\/span><\/h2>\n

A ferramenta inovadora \"Sturgeon\" utiliza a aprendizagem profunda para melhorar a classifica\u00e7\u00e3o intra-operat\u00f3ria dos tumores cerebrais, contribuindo para uma melhor tomada de decis\u00f5es cir\u00fargicas.\u00a0<\/span><\/p>\n

O modelo foi concebido para ser \"ultrarr\u00e1pido\" na classifica\u00e7\u00e3o dos tipos e subtipos de tumores.<\/span><\/p>\n

    \n
  • Desafios:<\/b> A classifica\u00e7\u00e3o dos tumores durante a cirurgia \u00e9 dif\u00edcil devido ao tempo limitado de sequencia\u00e7\u00e3o e \u00e0 cobertura incerta dos dados.\u00a0<\/span><\/li>\n
  • A solu\u00e7\u00e3o de Sturgeon:<\/b> Este sistema de aprendizagem profunda utiliza dados derivados de dados de matriz de metila\u00e7\u00e3o amplamente dispon\u00edveis, que s\u00e3o utilizados para tra\u00e7ar o perfil de tumores cerebrais. O Sturgeon externaliza tarefas computacionais intensivas para minimizar os recursos computacionais durante a cirurgia.<\/span><\/li>\n
  • Desempenho:<\/b> O modelo apresentou resultados consistentes, mas muitas vezes n\u00e3o tem em conta a diversidade intratumoral. Forneceu o diagn\u00f3stico correto em 72% dos testes cir\u00fargicos.\u00a0<\/span><\/li>\n
  • Desenvolvimento futuro:<\/b> \u00c0 medida que forem sendo adquiridos mais dados, os dados de Sturgeon ser\u00e3o melhorados, embora as restri\u00e7\u00f5es \u00e0 partilha de dados devido a preocupa\u00e7\u00f5es com a privacidade tornem dif\u00edcil a aprendizagem interinstitucional.\u00a0<\/span><\/li>\n
  • Limita\u00e7\u00f5es:<\/b> Uma limita\u00e7\u00e3o potencial \u00e9 a quantidade de tecido necess\u00e1ria. O modelo requer um tamanho de amostra de cerca de 5 x 5 x 5 mm para obter os melhores resultados, mas foi extra\u00eddo com sucesso ADN suficiente de amostras mais pequenas.<\/span><\/li>\n<\/ul>\n

    Crucialmente, com o Sturgeon, os resultados do diagn\u00f3stico de tumores podem ser obtidos em 90 minutos, alinhando-se com os prazos cir\u00fargicos. Isto d\u00e1 aos cirurgi\u00f5es conhecimentos em tempo real, permitindo-lhes tomar melhores decis\u00f5es durante a cirurgia.\u00a0<\/span><\/p>\n

    Embora os dados de Sturgeon sejam ben\u00e9ficos, o ideal seria que fossem utilizados juntamente com a avalia\u00e7\u00e3o de um patologista treinado, de acordo com o estudo.\u00a0<\/span><\/p>\n

    Sturgeon junta-se a uma legi\u00e3o de modelos de IA de ponta orientados para a medicina criados este ano, ilustrando a capacidade da tecnologia para transformar os resultados dos cuidados de sa\u00fade.<\/p>","protected":false},"excerpt":{"rendered":"

    Os cirurgi\u00f5es cerebrais debatem-se frequentemente com decis\u00f5es cr\u00edticas durante o processo de remo\u00e7\u00e3o de tumores. Agora, cientistas holandeses introduziram uma ferramenta de IA para auxiliar o processo de tomada de decis\u00f5es intra-cir\u00fargicas, fornecendo aos cirurgi\u00f5es informa\u00e7\u00f5es ultra-r\u00e1pidas sobre os tipos e subtipos de tumores. De acordo com um estudo recente publicado na revista Nature, a IA examina segmentos espec\u00edficos do ADN de um tumor, identificando estruturas qu\u00edmicas distintas. Esta an\u00e1lise fornece informa\u00e7\u00f5es sobre o tipo de tumor e, possivelmente, o seu subtipo. Esta informa\u00e7\u00e3o atempada pode orientar os cirurgi\u00f5es na sua abordagem \u00e0 opera\u00e7\u00e3o cir\u00fargica. \"\u00c9 imperativo que o subtipo de tumor seja conhecido na altura da cirurgia\", afirmou Jeroen de Ridder, um dos respons\u00e1veis pela IA.<\/p>","protected":false},"author":2,"featured_media":6362,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[88],"tags":[203,204,101],"class_list":["post-6361","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ethics","tag-biotech","tag-healthcare","tag-medtech"],"yoast_head":"\nNew AI model helps brain surgeons analyze tumors on the fly | DailyAI<\/title>\n<meta name=\"description\" content=\"Brain surgeons often grapple with critical decisions when addressing the boundaries of tumors.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, 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