{"id":13265,"date":"2024-07-04T18:38:04","date_gmt":"2024-07-04T18:38:04","guid":{"rendered":"https:\/\/dailyai.com\/?p=13265"},"modified":"2024-07-04T23:28:31","modified_gmt":"2024-07-04T23:28:31","slug":"new-ai-model-successfully-identifies-alzheimers-disease-using-speech-analysis","status":"publish","type":"post","link":"https:\/\/dailyai.com\/pt\/2024\/07\/new-ai-model-successfully-identifies-alzheimers-disease-using-speech-analysis\/","title":{"rendered":"Novo sistema de IA identifica com \u00eaxito a doen\u00e7a de Alzheimer atrav\u00e9s da an\u00e1lise do discurso"},"content":{"rendered":"

Atrav\u00e9s da an\u00e1lise dos padr\u00f5es de discurso, os investigadores da Universidade de Boston desenvolveram um sistema de IA que consegue prever com uma precis\u00e3o de quase 80% se uma pessoa com um d\u00e9fice cognitivo ligeiro ir\u00e1 desenvolver a doen\u00e7a de Alzheimer no prazo de seis anos.<\/b><\/p>\n

O <\/span>estudo<\/span><\/a>publicado na revista Alzheimer's & Dementia, utiliza a IA para extrair informa\u00e7\u00f5es valiosas de diagn\u00f3stico das avalia\u00e7\u00f5es cognitivas, acelerando o diagn\u00f3stico e, por sua vez, o tratamento da doen\u00e7a de Alzheimer.\u00a0<\/span><\/p>\n

O modelo de IA da equipa alcan\u00e7ou uma precis\u00e3o de 78,5% e uma sensibilidade de 81,1% na previs\u00e3o da progress\u00e3o do d\u00e9fice cognitivo ligeiro (MCI) para a doen\u00e7a de Alzheimer num per\u00edodo de seis anos. Este resultado \u00e9 superior ao de outros testes tradicionais e n\u00e3o invasivos.<\/span><\/p>\n

No entanto, o mais importante \u00e9 que o sistema se baseia apenas em dados facilmente obtidos: discurso transcrito de avalia\u00e7\u00f5es cognitivas e informa\u00e7\u00f5es demogr\u00e1ficas b\u00e1sicas como idade, sexo e n\u00edvel de educa\u00e7\u00e3o. <\/span><\/p>\n

As avalia\u00e7\u00f5es cognitivas, como o Teste de Nomea\u00e7\u00e3o de Boston, envolvem um m\u00e9dico a falar com o doente. O \u00e1udio destes testes \u00e9 frequentemente gravado para an\u00e1lise posterior.\u00a0<\/span><\/p>\n

\"Quer\u00edamos prever o que iria acontecer nos pr\u00f3ximos seis anos - e descobrimos que podemos fazer essa previs\u00e3o com uma confian\u00e7a e precis\u00e3o relativamente boas\". <\/span>disse Ioannis (Yannis) Paschalidis<\/span><\/a>diretor do BU Rafik B. Hariri Institute for Computing and Computational Science & Engineering e um dos principais investigadores do estudo.<\/span><\/p>\n

\"Se conseguirmos prever o que vai acontecer, temos mais oportunidades e uma janela de tempo para intervir com medicamentos e, pelo menos, tentar manter a estabilidade da doen\u00e7a e evitar a transi\u00e7\u00e3o para formas mais graves de dem\u00eancia\".<\/span><\/p>\n

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

Eis um resumo do funcionamento do estudo:<\/span><\/p>\n

    \n
  1. A equipa de investiga\u00e7\u00e3o come\u00e7ou por recolher grava\u00e7\u00f5es \u00e1udio de avalia\u00e7\u00f5es cognitivas de 166 participantes diagnosticados com d\u00e9fice cognitivo ligeiro (DCL). De seguida, seguiram estes indiv\u00edduos durante um per\u00edodo de seis anos para determinar quem progrediu para a doen\u00e7a de Alzheimer e quem se manteve est\u00e1vel.<\/span><\/li>\n
  2. A equipa utilizou tecnologia avan\u00e7ada de reconhecimento de voz para transcrever as grava\u00e7\u00f5es \u00e1udio e preparar os dados para an\u00e1lise.\u00a0<\/span><\/li>\n
  3. Em seguida, os investigadores aplicaram t\u00e9cnicas sofisticadas de processamento da linguagem natural para extrair uma vasta gama de caracter\u00edsticas e padr\u00f5es lingu\u00edsticos que, segundo eles, poderiam servir como indicadores do risco de Alzheimer.<\/span><\/li>\n
  4. Em seguida, utilizaram as caracter\u00edsticas do discurso e as informa\u00e7\u00f5es demogr\u00e1ficas para desenvolver v\u00e1rios modelos de aprendizagem autom\u00e1tica.<\/li>\n
  5. Estes modelos de IA foram concebidos para prever a probabilidade de um determinado indiv\u00edduo evoluir de um d\u00e9fice cognitivo ligeiro para a doen\u00e7a de Alzheimer com base nos seus padr\u00f5es de discurso e caracter\u00edsticas pessoais \u00fanicos.<\/span><\/li>\n
  6. Os modelos atingiram uma exatid\u00e3o de 78,5% e uma sensibilidade de 81,1% na previs\u00e3o dos participantes que desenvolveriam a doen\u00e7a de Alzheimer durante o per\u00edodo de estudo de seis anos.<\/span><\/li>\n
  7. Numa an\u00e1lise final, a equipa de investiga\u00e7\u00e3o identificou os testes cognitivos com maior poder de previs\u00e3o do risco de Alzheimer, como o Boston Naming Test, testes de semelhan\u00e7a e a Wechsler Adult Intelligence Scale.<\/span><\/li>\n<\/ol>\n

    \"O digital \u00e9 o novo sangue\", afirmou Rhoda Au, professora da Escola de Medicina Chobanian & Avedisian da BU e coautora do estudo.\u00a0<\/span><\/p>\n

    \"Podemos recolh\u00ea-lo, analis\u00e1-lo para o que se sabe hoje, armazen\u00e1-lo e reanalis\u00e1-lo para o que quer que surja de novo amanh\u00e3.\"<\/span><\/p>\n

    Um dos aspectos mais interessantes do estudo foi o facto de certas partes das avalia\u00e7\u00f5es cognitivas serem especialmente preditivas do risco futuro de Alzheimer.\u00a0<\/span><\/p>\n

    \"A nossa an\u00e1lise revelou que os subtestes relacionados com quest\u00f5es demogr\u00e1ficas, o Boston Naming Test, os testes de semelhan\u00e7a e a Wechsler Adult Intelligence Scale surgiram como as principais caracter\u00edsticas que impulsionam o desempenho do nosso modelo\", referem os investigadores.\u00a0<\/span><\/p>\n

    Este facto poder\u00e1 contribuir para o desenvolvimento de avalia\u00e7\u00f5es cognitivas mais espec\u00edficas, simplificando ainda mais o processo de rastreio.<\/span><\/p>\n

    Embora os resultados sejam prometedores, os investigadores admitem a necessidade de uma maior valida\u00e7\u00e3o em popula\u00e7\u00f5es maiores e mais diversificadas.\u00a0<\/span><\/p>\n

    O reconhecimento da fala pode abrir a porta ao diagn\u00f3stico precoce<\/h2>\n

    A an\u00e1lise da fala revelou-se uma t\u00e9cnica valiosa para prever a doen\u00e7a de Alzheimer e outras doen\u00e7as. <\/span><\/p>\n

    Num <\/span>Estudo de 2020<\/span><\/a> \u00e0 semelhan\u00e7a do estudo da Universidade de Boston, os investigadores da Universidade de Sheffield demonstraram a capacidade da sua IA para distinguir entre os participantes com doen\u00e7a de Alzheimer ou defici\u00eancia cognitiva ligeira e os participantes com perturba\u00e7\u00e3o cognitiva funcional ou controlos saud\u00e1veis com uma precis\u00e3o de 86,7%.\u00a0<\/span><\/p>\n

    Os investigadores da Klick Labs tamb\u00e9m <\/span>desenvolveu um modelo de IA<\/span><\/a> que consegue detetar a diabetes tipo 2 atrav\u00e9s de breves grava\u00e7\u00f5es de voz de apenas 6 a 10 segundos. <\/span>A diabetes avan\u00e7ada pode afetar a voz atrav\u00e9s de danos nos nervos, diminui\u00e7\u00e3o do fluxo sangu\u00edneo e boca seca, resultando em altera\u00e7\u00f5es detect\u00e1veis.\u00a0<\/span><\/p>\n

    O estudo analisou 18.000 grava\u00e7\u00f5es para identificar diferen\u00e7as ac\u00fasticas subtis entre indiv\u00edduos diab\u00e9ticos e n\u00e3o diab\u00e9ticos. <\/span><\/p>\n

    Quando combinado com factores como a idade e o IMC, o modelo atingiu uma precis\u00e3o m\u00e1xima de teste de 89% para as mulheres e 86% para os homens.<\/span><\/p>\n

    Em conjunto, estes estudos provam que os testes e m\u00e9todos de diagn\u00f3stico n\u00e3o invasivos apoiados pela IA podem conduzir a um tratamento mais r\u00e1pido e mais eficaz, mesmo na aus\u00eancia de m\u00e9dicos e equipamento especializado.<\/p>","protected":false},"excerpt":{"rendered":"

    Atrav\u00e9s da an\u00e1lise dos padr\u00f5es de discurso, os investigadores da Universidade de Boston desenvolveram um sistema de IA capaz de prever, com uma precis\u00e3o de quase 80%, se uma pessoa com d\u00e9fice cognitivo ligeiro ir\u00e1 desenvolver a doen\u00e7a de Alzheimer no prazo de seis anos. O estudo, publicado na revista Alzheimer's & Dementia, utiliza a IA para extrair informa\u00e7\u00f5es valiosas de diagn\u00f3stico das avalia\u00e7\u00f5es cognitivas, acelerando o diagn\u00f3stico e, por sua vez, o tratamento da doen\u00e7a de Alzheimer. O modelo de IA da equipa alcan\u00e7ou uma precis\u00e3o de 78,5% e uma sensibilidade de 81,1% na previs\u00e3o da progress\u00e3o do d\u00e9fice cognitivo ligeiro (MCI) para a doen\u00e7a de Alzheimer num per\u00edodo de seis anos. Este resultado \u00e9 superior ao de outros testes tradicionais e n\u00e3o invasivos. No entanto, o mais importante \u00e9 o facto de o sistema se basear<\/p>","protected":false},"author":2,"featured_media":13269,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[88],"tags":[353,204,178],"class_list":["post-13265","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ethics","tag-biology","tag-healthcare","tag-medicine"],"yoast_head":"\nNew AI system successfully identifies Alzheimer's disease using speech analysis | DailyAI<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/dailyai.com\/pt\/2024\/07\/new-ai-model-successfully-identifies-alzheimers-disease-using-speech-analysis\/\" \/>\n<meta property=\"og:locale\" content=\"pt_PT\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"New AI system successfully identifies Alzheimer's disease using speech analysis | DailyAI\" \/>\n<meta property=\"og:description\" content=\"By analyzing speech patterns, researchers at Boston University have developed an AI system that can predict with nearly 80% accuracy whether someone with mild cognitive impairment will develop Alzheimer’s disease within six years. The study, published in the journal Alzheimer’s & Dementia, uses AI to extract valuable diagnostic information from cognitive assessments, accelerating Alzheimer\u2019s diagnosis and, in turn, treatment.\u00a0 The team’s AI model achieved an accuracy of 78.5% and a sensitivity of 81.1% in predicting progression from mild cognitive impairment (MCI) to Alzheimer’s disease within a six-year timeframe. This beats other traditional and non-invasive tests. Crucially, though, the system relies\" \/>\n<meta property=\"og:url\" content=\"https:\/\/dailyai.com\/pt\/2024\/07\/new-ai-model-successfully-identifies-alzheimers-disease-using-speech-analysis\/\" \/>\n<meta property=\"og:site_name\" content=\"DailyAI\" \/>\n<meta property=\"article:published_time\" content=\"2024-07-04T18:38:04+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2024-07-04T23:28:31+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/dailyai.com\/wp-content\/uploads\/2024\/07\/DALL\u00b7E-2024-07-04-19.41.55-A-high-quality-landscape-image-of-an-AI-brain-analyzing-speech-patterns-to-identify-Alzheimers-disease.-The-scene-is-simple-and-futuristic-featurin.webp\" \/>\n\t<meta property=\"og:image:width\" content=\"1792\" \/>\n\t<meta property=\"og:image:height\" content=\"1024\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/webp\" \/>\n<meta name=\"author\" content=\"Sam Jeans\" \/>\n<meta name=\"twitter:card\" 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