{"id":9477,"date":"2026-06-18T10:15:00","date_gmt":"2026-06-18T02:15:00","guid":{"rendered":"https:\/\/ozellemed.com\/?p=9477"},"modified":"2026-06-18T10:58:26","modified_gmt":"2026-06-18T02:58:26","slug":"the-fourth-generation-of-hematology-analysis-has-begun","status":"publish","type":"post","link":"https:\/\/ozellemed.com\/pt\/the-fourth-generation-of-hematology-analysis-has-begun\/","title":{"rendered":"A quarta gera\u00e7\u00e3o de an\u00e1lises hematol\u00f3gicas j\u00e1 come\u00e7ou"},"content":{"rendered":"

H\u00e1 mais de setenta anos que a an\u00e1lise hematol\u00f3gica tem vindo a evoluir gra\u00e7as a sucessivos avan\u00e7os tecnol\u00f3gicos. Desde a contagem automatizada de c\u00e9lulas at\u00e9 \u00e0 citometria de fluxo multiparam\u00e9trica e \u00e0 morfologia digital, cada gera\u00e7\u00e3o de inova\u00e7\u00f5es tem alargado a forma como os laborat\u00f3rios observam e compreendem o sangue.<\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n

No entanto, uma das dimens\u00f5es mais ricas em informa\u00e7\u00e3o da hematologia tem-se mantido dif\u00edcil de ampliar: a morfologia celular. Durante d\u00e9cadas, a identifica\u00e7\u00e3o de c\u00e9lulas anormais tem dependido do olhar treinado de especialistas experientes. A an\u00e1lise microsc\u00f3pica oferece uma vis\u00e3o diagn\u00f3stica aprofundada, mas \u00e9 intrinsecamente dif\u00edcil de padronizar e alargar aos sistemas de sa\u00fade modernos.<\/p>\n\n\n\n

Atualmente, o panorama dos cuidados de sa\u00fade est\u00e1 a mudar. O diagn\u00f3stico j\u00e1 n\u00e3o se limita aos laborat\u00f3rios centralizados. Em hospitais, cl\u00ednicas e redes de cuidados de sa\u00fade distribu\u00eddas, os exames de diagn\u00f3stico est\u00e3o a tornar-se uma infraestrutura cl\u00ednica de elevada frequ\u00eancia que apoia as decis\u00f5es m\u00e9dicas do dia a dia. Neste contexto, os sistemas de diagn\u00f3stico t\u00eam de funcionar de forma fi\u00e1vel em diferentes contextos cl\u00ednicos, com v\u00e1rios n\u00edveis de experi\u00eancia dos operadores e com cargas de trabalho reais.<\/p>\n\n\n\n

A precis\u00e3o, por si s\u00f3, j\u00e1 n\u00e3o \u00e9 suficiente. As tecnologias de diagn\u00f3stico t\u00eam tamb\u00e9m de garantir consist\u00eancia, estabilidade operacional e escalabilidade em todas as redes de cuidados de sa\u00fade. Esta mudan\u00e7a est\u00e1 a redefinir o que a tecnologia de diagn\u00f3stico deve vir a ser. Ao mesmo tempo, tem vindo a ocorrer outra transforma\u00e7\u00e3o: a evolu\u00e7\u00e3o da intelig\u00eancia artificial.<\/p>\n\n\n\n

<\/p>\n\n\n\n

Desenvolvido a par da evolu\u00e7\u00e3o da intelig\u00eancia artificial<\/h2>\n\n\n\n

Ozelle <\/a>foi fundada em 2014 num laborat\u00f3rio do Vale do Sil\u00edcio, durante a primeira vaga do deep learning. Desde o in\u00edcio, a Ozelle centrou-se na aplica\u00e7\u00e3o da intelig\u00eancia artificial a um dos desafios mais complexos do diagn\u00f3stico laboratorial: a an\u00e1lise da morfologia celular.<\/p>\n\n\n\n

Entre 2014 e 2019, Ozelle foi pioneiro na integra\u00e7\u00e3o da aprendizagem profunda com a imagiologia celular de alta resolu\u00e7\u00e3o, alcan\u00e7ando avan\u00e7os iniciais no reconhecimento morfol\u00f3gico automatizado. Este esfor\u00e7o reuniu uma equipa interdisciplinar que abrangeu a biologia estrutural, a ci\u00eancia da imagiologia e a vis\u00e3o computacional. Entre os principais colaboradores destacaram-se John Wu, PhD, cuja especializa\u00e7\u00e3o em biologia estrutural computacional ajudou a traduzir estruturas biol\u00f3gicas complexas e padr\u00f5es celulares em representa\u00e7\u00f5es interpret\u00e1veis por m\u00e1quinas, e G. Cong, PhD, inventor de v\u00e1rias patentes norte-americanas na \u00e1rea da an\u00e1lise de imagens celulares, cujo trabalho contribuiu para o avan\u00e7o dos fundamentos algor\u00edtmicos da classifica\u00e7\u00e3o celular automatizada.<\/p>\n\n\n\n

\u00c0 medida que a intelig\u00eancia artificial evoluiu para a era dos modelos de base e da aprendizagem por transfer\u00eancia, a Ozelle alargou a sua investiga\u00e7\u00e3o para al\u00e9m do desenvolvimento de algoritmos, rumo a aplica\u00e7\u00f5es de diagn\u00f3stico no mundo real. A partir de 2020, sob a lideran\u00e7a t\u00e9cnica de Jie Du \u2014 cujo trabalho faz a ponte entre hardware inteligente, vis\u00e3o computacional e sistemas de sensores \u2014, a equipa desenvolveu o AI \u00d7 Complete Blood Morphology (IA \u00d7 CBM)<\/a>, um quadro concebido para padronizar a an\u00e1lise morfol\u00f3gica entre instrumentos, ambientes e utilizadores cl\u00ednicos. Esta abordagem permite uma interpreta\u00e7\u00e3o morfol\u00f3gica consistente e de alta precis\u00e3o, validada em contextos cl\u00ednicos reais.<\/p>\n\n\n\n

Ao longo da \u00faltima d\u00e9cada, a Ozelle cresceu a par das sucessivas ondas de desenvolvimento da intelig\u00eancia artificial, transformando os avan\u00e7os na perce\u00e7\u00e3o computacional em capacidades de diagn\u00f3stico pr\u00e1ticas. Atualmente, a Ozelle opera a n\u00edvel global, com instala\u00e7\u00f5es em Frankfurt, na Alemanha, combinando t\u00e9cnicas avan\u00e7adas de imagiologia, intelig\u00eancia computacional e engenharia de sistemas de diagn\u00f3stico. Os sistemas da Ozelle est\u00e3o agora implementados em todo o mundo, tanto em m\u00e9dico <\/a>e veterin\u00e1ria<\/a> mercados.<\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n

<\/p>\n\n\n\n

Transformar a morfologia em intelig\u00eancia escal\u00e1vel<\/h2>\n\n\n\n

Os diagn\u00f3sticos hematol\u00f3gicos tradicionais fornecem par\u00e2metros num\u00e9ricos altamente fi\u00e1veis, mas a interpreta\u00e7\u00e3o morfol\u00f3gica tem continuado, em grande medida, a depender da experi\u00eancia manual. A Ozelle d\u00e1 resposta a este desafio atrav\u00e9s da IA \u00d7 CBM. A CBM garante que a morfologia celular \u00e9 captada com uma qualidade de imagem consistente em todas as amostras e instrumentos. A IA analisa, ent\u00e3o, estas caracter\u00edsticas morfol\u00f3gicas para produzir interpreta\u00e7\u00f5es padronizadas dos padr\u00f5es celulares.<\/p>\n\n\n\n

Em conjunto, a IA e a CBM transformam a an\u00e1lise morfol\u00f3gica de uma compet\u00eancia individual de especialistas numa capacidade de diagn\u00f3stico consistente que pode ser aplicada em laborat\u00f3rios, cl\u00ednicas e redes de cuidados de sa\u00fade. Esta transforma\u00e7\u00e3o marca o in\u00edcio da quarta gera\u00e7\u00e3o de an\u00e1lises hematol\u00f3gicas.<\/p>\n\n\n\n

<\/p>\n\n\n\n

Diagn\u00f3stico concebido como um sistema<\/h2>\n\n\n\n

Os ambientes cl\u00ednicos reais raramente se assemelham \u00e0s condi\u00e7\u00f5es controladas de laborat\u00f3rio. As cargas de trabalho variam, os operadores t\u00eam n\u00edveis de experi\u00eancia diferentes e nem sempre \u00e9 poss\u00edvel contar imediatamente com a opini\u00e3o de um especialista. Por esta raz\u00e3o, a Ozelle encara os diagn\u00f3sticos n\u00e3o como instrumentos isolados, mas como sistemas integrados concebidos para os ambientes cl\u00ednicos do dia a dia.<\/p>\n\n\n\n

Na base est\u00e3o analisadores concebidos para um funcionamento est\u00e1vel em ambientes de cuidados de sa\u00fade distribu\u00eddos. Para al\u00e9m do desempenho anal\u00edtico, os sistemas foram concebidos para garantir a consist\u00eancia das medi\u00e7\u00f5es a longo prazo, uma manuten\u00e7\u00e3o m\u00ednima e uma menor depend\u00eancia do operador.<\/p>\n\n\n\n

\u00c9 sobre esta base que se assenta o AI \u00d7 CBM, que converte a morfologia celular em informa\u00e7\u00e3o estruturada e interpret\u00e1vel por m\u00e1quinas. Ao combinar imagens padronizadas com uma interpreta\u00e7\u00e3o baseada em IA, \u00e9 poss\u00edvel obter informa\u00e7\u00f5es sobre a morfologia de forma consistente entre diferentes instrumentos e centros cl\u00ednicos.<\/p>\n\n\n\n

A apoiar o fluxo de trabalho est\u00e1 o AI Workbench, uma plataforma integrada que organiza os dados de diagn\u00f3stico, destaca achados celulares anormais e apresenta evid\u00eancias morfol\u00f3gicas claras aos m\u00e9dicos e aos profissionais de laborat\u00f3rio. \u00c0 medida que os exames de diagn\u00f3stico se expandem para al\u00e9m dos laborat\u00f3rios especializados, os m\u00e9dicos t\u00eam de interpretar volumes crescentes de dados de diagn\u00f3stico, enquanto o acesso a especialistas em morfologia continua a ser limitado. Padr\u00f5es celulares raros ou at\u00edpicos podem surgir apenas ocasionalmente na pr\u00e1tica de rotina, dificultando o seu reconhecimento consistente em diferentes contextos cl\u00ednicos.<\/p>\n\n\n\n

O AI Workbench responde a este desafio ao integrar a an\u00e1lise inteligente diretamente no fluxo de trabalho de diagn\u00f3stico. Em vez de substituir a experi\u00eancia cl\u00ednica, o sistema ajuda a identificar padr\u00f5es at\u00edpicos, a reduzir o risco de resultados serem ignorados e a promover uma avalia\u00e7\u00e3o diagn\u00f3stica mais consistente. Atrav\u00e9s desta arquitetura, os exames de diagn\u00f3stico evoluem de medi\u00e7\u00f5es isoladas para uma intelig\u00eancia cl\u00ednica estruturada, integrada nos fluxos de trabalho de rotina.<\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n

<\/p>\n\n\n\n

Concebido para a pr\u00e1tica cl\u00ednica quotidiana<\/h2>\n\n\n\n

Os sistemas Ozelle foram concebidos para se integrarem perfeitamente em ambientes cl\u00ednicos de rotina. Atrav\u00e9s de um design de sistema que facilita a manuten\u00e7\u00e3o, da elabora\u00e7\u00e3o de relat\u00f3rios assistida por IA e da integra\u00e7\u00e3o inteligente de dados, os profissionais de sa\u00fade podem obter tempos de resposta diagn\u00f3sticos mais r\u00e1pidos, uma interpreta\u00e7\u00e3o mais clara de dados biol\u00f3gicos complexos e resultados mais consistentes entre utilizadores e locais.<\/p>\n\n\n\n

O objetivo \u00e9 simples: integrar intelig\u00eancia diagn\u00f3stica avan\u00e7ada na pr\u00e1tica cl\u00ednica quotidiana \u2014 sem aumentar a complexidade operacional.<\/p>\n\n\n\n

<\/p>\n\n\n\n

O Futuro do Diagn\u00f3stico<\/h2>\n\n\n\n

A miss\u00e3o da Ozelle \u00e9 simples, mas ambiciosa: garantir que os diagn\u00f3sticos inteligentes funcionem de forma fi\u00e1vel no mundo real. Ao transformar fluxos de trabalho laboratoriais complexos em sistemas integrados baseados em IA, assentes na combina\u00e7\u00e3o de IA \u00d7 CBM, a Ozelle permite que a an\u00e1lise hematol\u00f3gica ao n\u00edvel dos especialistas se torne acess\u00edvel, escal\u00e1vel e fi\u00e1vel em ambientes cl\u00ednicos do dia a dia em todo o mundo.<\/p>","protected":false},"excerpt":{"rendered":"

For more than seventy years, hematology analysis has advanced through successive technological breakthroughs. From automated cell counting to multi-parameter flow cytometry and digital morphology, each generation of innovation has expanded how laboratories observe and understand blood. Yet one of the most information-rich dimensions of hematology has remained difficult to scale: cellular morphology. For decades, identifying […]<\/p>\n","protected":false},"author":17,"featured_media":9481,"comment_status":"closed","ping_status":"closed","sticky":true,"template":"","format":"standard","meta":{"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"set","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"footnotes":""},"categories":[22],"tags":[55,60,61,62,63],"class_list":["post-9477","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-22","tag-cbm","tag-ehbt-50","tag-ehbt-75","tag-ehvt-50","tag-ehvt-75"],"yoast_head":"\nThe Fourth Generation of Hematology Analysis Has Begun - Ozelle<\/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:\/\/ozellemed.com\/pt\/the-fourth-generation-of-hematology-analysis-has-begun\/\" \/>\n<meta property=\"og:locale\" content=\"pt_PT\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"The Fourth Generation of Hematology Analysis Has Begun\" \/>\n<meta property=\"og:description\" content=\"For more than seventy years, hematology analysis has advanced through successive technological breakthroughs. From automated cell counting to multi-parameter flow cytometry and digital morphology, each generation of innovation has expanded how laboratories observe and understand blood. Yet one of the most information-rich dimensions of hematology has remained difficult to scale: cellular morphology. 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