Integration and acceleration of virtual microscopy as the key to successful implementation into the routine diagnostic process

<p>Abstract</p> <p>Background</p> <p>The virtual microscopy is widely accepted in Pathology for educational purposes and teleconsultation but is far from the routine use in surgical pathology due to the technical requirements and some limitations. A technical problem is the limited bandwidth of a usual network and the delayed transmission rate and presentation time on the screen.</p> <p>Methods</p> <p>In this study the process of secondary diagnostic was evaluated using the "T.Konsult Pathologie" service of the Professional Association of German Pathologists within the German breast cancer screening program. The characteristics of the access to the WSI (Whole Slide Images) have been analyzed to explore the possibilities of prefetching and caching to reduce the presentation and transfer time with the goal to increase user acceptance. The log files of the web server were analyzed to reconstruct the movements of the pathologist on the WSI and to create the observation path. Using a specialized tool the observation paths were extracted automatically from the log files. The attributes linearity, 3-point-linearity, changes per request, and number of consecutive requests were calculated to design, develop and evaluate different caching and prefetching strategies.</p> <p>Results</p> <p>The analysis of the observation paths showed that a complete accordance of two image requests is a very rare event. But more frequently a partial covering of two requested image areas can be found. In total 257 diagnostic paths from 131 WSI have been extracted and analysed. On average a diagnostic path consists of 16 image requests and takes 189 seconds between first and last image request. The mean linearity was 0,41 and the mean 3-point-linearity 0,85. Three different caching algorithms have been compared with respect to hit rate and additional image requests on the WSI server. Tests demonstrated that 95% of the diagnostic paths could be loaded without any deletion of entries in the cache (cache size 12,2 Megapixel). If the image parts are stored after JPEG compression this complies with less than 2 MB.</p> <p>Discussion</p> <p>WSI telepathology is a technology which offers the possibility to break the limitations of conventional static telepathology. The complete histological slide may be investigated instead of sets of images of lesions sampled by the presenting pathologist. The benefit is demonstrated by the high diagnostic security of 95% accordance between first and second diagnosis.</p

Sistemas interativos e distribuídos para telemedicina

doutoramento Ciências da ComputaçãoDurante as últimas décadas, as organizações de saúde têm vindo a adotar continuadamente as tecnologias de informação para melhorar o funcionamento dos seus serviços. Recentemente, em parte devido à crise financeira, algumas reformas no sector de saúde incentivaram o aparecimento de novas soluções de telemedicina para otimizar a utilização de recursos humanos e de equipamentos. Algumas tecnologias como a computação em nuvem, a computação móvel e os sistemas Web, têm sido importantes para o sucesso destas novas aplicações de telemedicina. As funcionalidades emergentes de computação distribuída facilitam a ligação de comunidades médicas, promovem serviços de telemedicina e a colaboração em tempo real. Também são evidentes algumas vantagens que os dispositivos móveis podem introduzir, tais como facilitar o trabalho remoto a qualquer hora e em qualquer lugar. Por outro lado, muitas funcionalidades que se tornaram comuns nas redes sociais, tais como a partilha de dados, a troca de mensagens, os fóruns de discussão e a videoconferência, têm o potencial para promover a colaboração no sector da saúde. Esta tese teve como objetivo principal investigar soluções computacionais mais ágeis que permitam promover a partilha de dados clínicos e facilitar a criação de fluxos de trabalho colaborativos em radiologia. Através da exploração das atuais tecnologias Web e de computação móvel, concebemos uma solução ubíqua para a visualização de imagens médicas e desenvolvemos um sistema colaborativo para a área de radiologia, baseado na tecnologia da computação em nuvem. Neste percurso, foram investigadas metodologias de mineração de texto, de representação semântica e de recuperação de informação baseada no conteúdo da imagem. Para garantir a privacidade dos pacientes e agilizar o processo de partilha de dados em ambientes colaborativos, propomos ainda uma metodologia que usa aprendizagem automática para anonimizar as imagens médicasDuring the last decades, healthcare organizations have been increasingly relying on information technologies to improve their services. At the same time, the optimization of resources, both professionals and equipment, have promoted the emergence of telemedicine solutions. Some technologies including cloud computing, mobile computing, web systems and distributed computing can be used to facilitate the creation of medical communities, and the promotion of telemedicine services and real-time collaboration. On the other hand, many features that have become commonplace in social networks, such as data sharing, message exchange, discussion forums, and a videoconference, have also the potential to foster collaboration in the health sector. The main objective of this research work was to investigate computational solutions that allow us to promote the sharing of clinical data and to facilitate the creation of collaborative workflows in radiology. By exploring computing and mobile computing technologies, we have designed a solution for medical imaging visualization, and developed a collaborative system for radiology, based on cloud computing technology. To extract more information from data, we investigated several methodologies such as text mining, semantic representation, content-based information retrieval. Finally, to ensure patient privacy and to streamline the data sharing in collaborative environments, we propose a machine learning methodology to anonymize medical images

Métodos computacionais para otimização de desempenho em redes de imagem médica

Over the last few years, the medical imaging has consolidated its position as a major mean of clinical diagnosis. The amount of data generated by the medical imaging practice is increasing tremendously. As a result, repositories are turning into rich databanks of semi-structured data related to patients, ailments, equipment and other stakeholders involved in the medical imaging panorama. The exploration of these repositories for secondary uses of data promises to elevate the quality standards and efficiency of the medical practice. However, supporting these advanced usage scenarios in traditional institutional systems raises many technical challenges that are yet to be overcome. Moreover, the reported poor performance of standard protocols opened doors to the general usage of proprietary solutions, compromising the interoperability necessary for supporting these advanced scenarios. This thesis has researched, developed, and now proposes a series of computer methods and architectures intended to maximize the performance of multi-institutional medical imaging environments. The methods are intended to improve the performance of standard protocols for medical imaging content discovery and retrieval. The main goal is to use them to increase the acceptance of vendor-neutral solutions through the improvement of their performance. Moreover, it intends to promote the adoption of such standard technologies in advanced scenarios that are still a mirage nowadays, such as clinical research or data analytics directly on top of live institutional repositories. Finally, these achievements will facilitate the cooperation between healthcare institutions and researchers, resulting in an increment of healthcare quality and institutional efficiency.As diversas modalidades de imagem médica têm vindo a consolidar a sua posição dominante como meio complementar de diagnóstico. O número de procedimentos realizados e o volume de dados gerados aumentou significativamente nos últimos anos, colocando pressão nas redes e sistemas que permitem o arquivo e distribuição destes estudos. Os repositórios de estudos imagiológicos são fontes de dados ricas contendo dados semiestruturados relacionados com pacientes, patologias, procedimentos e equipamentos. A exploração destes repositórios para fins de investigação e inteligência empresarial, tem potencial para melhorar os padrões de qualidade e eficiência da prática clínica. No entanto, estes cenários avançados são difíceis de acomodar na realidade atual dos sistemas e redes institucionais. O pobre desempenho de alguns protocolos standard usados em ambiente de produção, conduziu ao uso de soluções proprietárias nestes nichos aplicacionais, limitando a interoperabilidade de sistemas e a integração de fontes de dados. Este doutoramento investigou, desenvolveu e propõe um conjunto de métodos computacionais cujo objetivo é maximizar o desempenho das atuais redes de imagem médica em serviços de pesquisa e recuperação de conteúdos, promovendo a sua utilização em ambientes de elevados requisitos aplicacionais. As propostas foram instanciadas sobre uma plataforma de código aberto e espera-se que ajudem a promover o seu uso generalizado como solução vendor-neutral. As metodologias foram ainda instanciadas e validadas em cenários de uso avançado. Finalmente, é expectável que o trabalho desenvolvido possa facilitar a investigação em ambiente hospitalar de produção, promovendo, desta forma, um aumento da qualidade e eficiência dos serviços.Programa Doutoral em Engenharia Informátic

Desain Metode PrefetchCache untuk Peningkatan Kinerja Aplikasi Web

Internet dan teknologi web telah menyediakan sarana yang dapat diandalkan untuk berbagi data dan aplikasi. Namun, latensi pemuatan data masih menjadi kendala. Dalam beberapa literatur, metode cache terbukti meningkatkan waktu penyajian halaman web dengan mengurangi proses permintaan pada database. Namun, metode ini tidak mencegah web mengakses server untuk mengambil data cache dalam database, latensi dalam memuat data masih terjadi. Makalah ini menyajikan metode prefetch dengan mengubah data menjadi file data yang diformat JSON sebagai cache, data diperoleh dengan mudah tanpa harus melakukan proses permintaan. Hasil pengujian menunjukkan bahwa aplikasi web menjadi lebih responsif dalam menyajikan data

Serviços de imagem médica suportados na cloud

Mestrado em Engenharia de Computadores e TelemáticaHoje em dia, as instituições de cuidados de saúde, utilizam a telemedicina para suportar ambientes colaborativos. Na área da imagem médica digital, a quantidade de dados tem crescido substancialmente nos últimos anos, requerendo mais infraestruturas para fornecer um serviço com a qualidade desejada. Os computadores e dispositivos com acesso à Internet estão acessíveis em qualquer altura e em qualquer lugar, criando oportunidades para partilhar e utilizar recursos online. Uma enorme quantidade de processamento computacional e armazenamento são utilizados como uma comodidade no quotidiano. Esta dissertação apresenta uma plataforma para suportar serviços de telemedicina sobre a cloud, permitindo que aplicações armazenem e comuniquem facilmente, utilizando qualquer fornecedor de cloud. Deste modo, os programadores não necessitam de se preocupar onde os recursos vão ser instalados a as suas aplicações não ficam limitadas a um único fornecedor. Foram desenvolvidas duas aplicações para tele-imagiologia com esta plataforma: repositório de imagens médicas e uma infraestrutura de comunicações entre centros hospitalares. Finalmente, a arquitetura desenvolvida é genérica e flexível permitindo facilmente a sua expansão para outras áreas aplicacionais e outros serviços de cloud.Healthcare institutions resort largely, nowadays, to telemedicine in order to support collaborative environments. In the medical imaging area, the huge amount of medical volume data has increased over the past few years, requiring high-performance infrastructures to provide services with required quality. Computing devices and Internet access are now available anywhere and at anytime, creating new opportunities to share and use online resources. A tremendous amount of ubiquitous computational power and an unprecedented number of Internet resources and services are used every day as a normal commodity. This thesis presents a telemedicine service platform over the Cloud that allows applications to store information and to communicate easier, using any Internet cloud provider. With this platform, developers do not concern where the resources will be deployed and the applications will not be restricted to a specific cloud vendor. Two tele-imagiologic applications were developed along with this platform: a medical imaging repository and an interinstitutional communications infrastructure. Lastly, the architecture developed is generic and flexible to expand to other application areas and cloud services

Rede peer-to-peer para imagem médica

Mestrado em Engenharia de Computadores e TelemáticaNos últimos anos, a imagem médica em formato digital tem sido uma ferramenta cada vez mais importante quer para o diagnóstico médico quer para o auxílio ao tratamento. Assim, equipamentos de aquisição digital e repositórios de imagem médica são cada vez mais comuns em instituições de saúde, podendo até haver mais que um repositório numa instituição. No entanto, esta proliferação de repositórios leva a que a informação esteja dispersa nos vários locais. Esta dispersão da informação juntamente com as diferenças no armazenamento entre instituições são claros obstáculos à pesquisa e acesso integrado a essa informação. Esta dissertação visa o estudo da tecnologia Peer-to-Peer de forma a minimizar os problemas associados à dispersão e heterogeneidade da informação.In the last years, digital medical imaging has been an increasingly important tool for both medical diagnostic and treatment assistance. Therefore, digital image acquisition equipments and medical imaging repositories are more and more common in a healthcare institution, being possible even more than one repository in one institution. However, this proliferation of repositories leads to dispersion of data between many places. This data dispersion associated with differences in the data storage between institutions are evident obstacles to the search for medical data. This dissertation aims to the study of the Peer-to- Peer technology in order to minimize the problems related to the dispersion and heterogeneity of medical data

Wiki-health: from quantified self to self-understanding

Today, healthcare providers are experiencing explosive growth in data, and medical imaging represents a significant portion of that data. Meanwhile, the pervasive use of mobile phones and the rising adoption of sensing devices, enabling people to collect data independently at any time or place is leading to a torrent of sensor data. The scale and richness of the sensor data currently being collected and analysed is rapidly growing. The key challenges that we will be facing are how to effectively manage and make use of this abundance of easily-generated and diverse health data. This thesis investigates the challenges posed by the explosive growth of available healthcare data and proposes a number of potential solutions to the problem. As a result, a big data service platform, named Wiki-Health, is presented to provide a unified solution for collecting, storing, tagging, retrieving, searching and analysing personal health sensor data. Additionally, it allows users to reuse and remix data, along with analysis results and analysis models, to make health-related knowledge discovery more available to individual users on a massive scale. To tackle the challenge of efficiently managing the high volume and diversity of big data, Wiki-Health introduces a hybrid data storage approach capable of storing structured, semi-structured and unstructured sensor data and sensor metadata separately. A multi-tier cloud storage system—CACSS has been developed and serves as a component for the Wiki-Health platform, allowing it to manage the storage of unstructured data and semi-structured data, such as medical imaging files. CACSS has enabled comprehensive features such as global data de-duplication, performance-awareness and data caching services. The design of such a hybrid approach allows Wiki-Health to potentially handle heterogeneous formats of sensor data. To evaluate the proposed approach, we have developed an ECG-based health monitoring service and a virtual sensing service on top of the Wiki-Health platform. The two services demonstrate the feasibility and potential of using the Wiki-Health framework to enable better utilisation and comprehension of the vast amounts of sensor data available from different sources, and both show significant potential for real-world applications.Open Acces

Unterstützung von Prozessen der intersektoralen Vernetzung mit medizinischen Bildern unter Berücksichtigung der Qualitätssicherung

Im Gesundheitswesen wird der elektronische Austausch von Daten zwischen professionellen Anwendern wie Ärzten, Pflegekräften oder Medizinisch-technischen Assistenten/innen sowie zwischen Ärzten und Patienten immer wichtiger. Aber dennoch ist Kollaborationssoftware in diesem Bereich nach wie vor noch nicht großflächig im Einsatz, so dass sich folgende Fragen ergeben: Welche technischen Voraussetzungen müssen geschaffen werden, um den medizinischen Workflow zu unterstützen beziehungsweise zu verbessern? Und wie können Vernetzung, Qualitätssicherung, Daten- und damit auch Patientensicherheit miteinander vereint werden, um eine bessere Behandlung zu gewährleisten? In dieser Arbeit wurden unterschiedliche Methoden zur Unterstützung von Prozessen der intersektoralen Vernetzung vor allem mit medizinischen Bildern entwickelt und implementiert. Die vorgenommenen Realisierungen fanden dabei insbesondere mit Blick auf die Qualitätssicherung statt. Durch Weiterentwicklungen im Bereich von DICOM E-Mail wurden Verfahren zur einfachen Administration von Netzwerken und automatisierten Konstanzprüfung dem @GIT-Whitepaper ‚Empfehlung für ein standardisiertes Teleradiologie Übertragungsformat‘ hinzugefügt. Die Implementierung einer Multiknotenstatistik erlaubt die zeitunabhängige Nachverfolgung eines Transfers von radiologischen Bilddaten in heterogenen Netzwerken, auch über mehrere Empfangsknoten hinweg. Neben DICOM E-Mail kommen hier verschiedene Übertragungsprotokolle zum Einsatz. Die entwickelten Verfahren zur Verwaltung von DICOM E-Mail Netzwerken wurden durch die @GIT in ein IHE-Profil überführt, von welchem schlussendlich ein Teil in einem Change Proposal als Erweiterung eines bestehenden Profils der Domäne Radiologie angenommen wurde. Im Rahmen des INFOPAT-Projekts des Universitätsklinikums Heidelberg und im Bereich der intersektoralen Vernetzung wurden zahlreiche Erweiterungen und Performanceoptimierungen bei der Entwicklung eines IHE-Adapters für Altsysteme in einem Netzwerk vorgenommen, welche es ermöglichen, auch nicht-IHE-fähige Aktoren an eine persönliche elektronische Patientenakte anzuschließen. Weiterhin wurde ein XDS-fähiger mobiler Bildbetrachter für Patienten entwickelt, der es durch ein standardisiertes Single-Sign-On erlaubt, zwischen Patientenakte, radiologischem Viewer und mobilem Bildbetrachter nahtlos zu wechseln. Um eine einfachere Kommunikation zwischen Ärzten, medizinischen Dienstleistern und Patienten zu realisieren, wurde eine bestehende Teleradiologieakte durch die Entwicklung eines konfigurierbaren Workflowmanagements sowie verschiedene Freigabe- und Exportmodule erweitert. Abschließend wurde das Monitoring-System für teleradiolgische Netzwerke weiterentwickelt, um Probleme und Engstellen bei der Kommunikation frühzeitig und proaktiv erkennen und beheben zu können. Die im Rahmen dieser Arbeit beschriebenen Weiterentwicklungen unterschiedlicher Standards im Bereich der Qualitätssicherung und Teleradiologie sowie die Softwareentwicklungen im Bereich der Telemedizin und schlussendlich der intersektoralen Vernetzung unterstützen den Arbeitsablauf der medizinischen als auch administrativen Anwender. Mit Hilfe der etablierten Lösungen kann ein reibungsloser Ablauf und das Zusammenspiel verschiedener Komponenten in heterogenen Netzwerken auch unter dem Gesichtspunkt der Qualitätssicherung gewährleistet werden. Patienten erhalten dadurch einen einfachen Zugang zu ihren Daten. Die Ergebnisse der Arbeit zeigen, dass auch heute schon ein qualitätsgesicherter und komfortabler Austausch von Bilddaten im medizinischen Umfeld ad hoc über die Grenzen von dezentralen Einrichtungen des Gesundheitswesens hinaus möglich ist. Dadurch kann die intersektorale Behandlung beschleunigt, die Behandlungsqualität verbessert und Doppeluntersuchungen vermieden werden

Enriching information extraction pipelines in clinical decision support systems

Programa Oficial de Doutoramento en Tecnoloxías da Información e as Comunicacións. 5032V01[Resumo] Os estudos sanitarios de múltiples centros son importantes para aumentar a repercusión dos resultados da investigación médica debido ao número de suxeitos que poden participar neles. Para simplificar a execución destes estudos, o proceso de intercambio de datos debería ser sinxelo, por exemplo, mediante o uso de bases de datos interoperables. Con todo, a consecución desta interoperabilidade segue sendo un tema de investigación en curso, sobre todo debido aos problemas de gobernanza e privacidade dos datos. Na primeira fase deste traballo, propoñemos varias metodoloxías para optimizar os procesos de estandarización das bases de datos sanitarias. Este traballo centrouse na estandarización de fontes de datos heteroxéneas nun esquema de datos estándar, concretamente o OMOP CDM, que foi desenvolvido e promovido pola comunidade OHDSI. Validamos a nosa proposta utilizando conxuntos de datos de pacientes con enfermidade de Alzheimer procedentes de distintas institucións. Na seguinte etapa, co obxectivo de enriquecer a información almacenada nas bases de datos de OMOP CDM, investigamos solucións para extraer conceptos clínicos de narrativas non estruturadas, utilizando técnicas de recuperación de información e de procesamento da linguaxe natural. A validación realizouse a través de conxuntos de datos proporcionados en desafíos científicos, concretamente no National NLP Clinical Challenges(n2c2). Na etapa final, propuxémonos simplificar a execución de protocolos de estudos provenientes de múltiples centros, propoñendo solucións novas para perfilar, publicar e facilitar o descubrimento de bases de datos. Algunhas das solucións desenvolvidas están a utilizarse actualmente en tres proxectos europeos destinados a crear redes federadas de bases de datos de saúde en toda Europa.[Resumen] Los estudios sanitarios de múltiples centros son importantes para aumentar la repercusión de los resultados de la investigación médica debido al número de sujetos que pueden participar en ellos. Para simplificar la ejecución de estos estudios, el proceso de intercambio de datos debería ser sencillo, por ejemplo, mediante el uso de bases de datos interoperables. Sin embargo, la consecución de esta interoperabilidad sigue siendo un tema de investigación en curso, sobre todo debido a los problemas de gobernanza y privacidad de los datos. En la primera fase de este trabajo, proponemos varias metodologías para optimizar los procesos de estandarización de las bases de datos sanitarias. Este trabajo se centró en la estandarización de fuentes de datos heterogéneas en un esquema de datos estándar, concretamente el OMOP CDM, que ha sido desarrollado y promovido por la comunidad OHDSI. Validamos nuestra propuesta utilizando conjuntos de datos de pacientes con enfermedad de Alzheimer procedentes de distintas instituciones. En la siguiente etapa, con el objetivo de enriquecer la información almacenada en las bases de datos de OMOP CDM, hemos investigado soluciones para extraer conceptos clínicos de narrativas no estructuradas, utilizando técnicas de recuperación de información y de procesamiento del lenguaje natural. La validación se realizó a través de conjuntos de datos proporcionados en desafíos científicos, concretamente en el National NLP Clinical Challenges (n2c2). En la etapa final, nos propusimos simplificar la ejecución de protocolos de estudios provenientes de múltiples centros, proponiendo soluciones novedosas para perfilar, publicar y facilitar el descubrimiento de bases de datos. Algunas de las soluciones desarrolladas se están utilizando actualmente en tres proyectos europeos destinados a crear redes federadas de bases de datos de salud en toda Europa.[Abstract] Multicentre health studies are important to increase the impact of medical research findings due to the number of subjects that they are able to engage. To simplify the execution of these studies, the data-sharing process should be effortless, for instance, through the use of interoperable databases. However, achieving this interoperability is still an ongoing research topic, namely due to data governance and privacy issues. In the first stage of this work, we propose several methodologies to optimise the harmonisation pipelines of health databases. This work was focused on harmonising heterogeneous data sources into a standard data schema, namely the OMOP CDM which has been developed and promoted by the OHDSI community. We validated our proposal using data sets of Alzheimer’s disease patients from distinct institutions. In the following stage, aiming to enrich the information stored in OMOP CDM databases, we have investigated solutions to extract clinical concepts from unstructured narratives, using information retrieval and natural language processing techniques. The validation was performed through datasets provided in scientific challenges, namely in the National NLP Clinical Challenges (n2c2). In the final stage, we aimed to simplify the protocol execution of multicentre studies, by proposing novel solutions for profiling, publishing and facilitating the discovery of databases. Some of the developed solutions are currently being used in three European projects aiming to create federated networks of health databases across Europe

Efficient interaction with large medical imaging databases

Everyday, a wide quantity of hospitals and medical centers around the world are producing large amounts of imaging content to support clinical decisions, medical research, and education. With the current trend towards Evidence-based medicine, there is an increasing need of strategies that allow pathologists to properly interact with the valuable information such imaging repositories host and extract relevant content for supporting decision making. Unfortunately, current systems are very limited at providing access to content and extracting information from it because of different semantic and computational challenges. This thesis presents a whole pipeline, comprising 3 building blocks, that aims to to improve the way pathologists and systems interact. The first building block consists in an adaptable strategy oriented to ease the access and visualization of histopathology imaging content. The second block explores the extraction of relevant information from such imaging content by exploiting low- and mid-level information obtained from from morphology and architecture of cell nuclei. The third block aims to integrate high-level information from the expert in the process of identifying relevant information in the imaging content. This final block not only attempts to deal with the semantic gap but also to present an alternative to manual annotation, a time consuming and prone-to-error task. Different experiments were carried out and demonstrated that the introduced pipeline not only allows pathologist to navigate and visualize images but also to extract diagnostic and prognostic information that potentially could support clinical decisions.Resumen: Diariamente, gran cantidad de hospitales y centros médicos de todo el mundo producen grandes cantidades de imágenes diagnósticas para respaldar decisiones clínicas y apoyar labores de investigación y educación. Con la tendencia actual hacia la medicina basada en evidencia, existe una creciente necesidad de estrategias que permitan a los médicos patólogos interactuar adecuadamente con la información que albergan dichos repositorios de imágenes y extraer contenido relevante que pueda ser empleado para respaldar la toma de decisiones. Desafortunadamente, los sistemas actuales son muy limitados en cuanto al acceso y extracción de contenido de las imágenes debido a diferentes desafíos semánticos y computacionales. Esta tesis presenta un marco de trabajo completo para patología, el cual se compone de 3 bloques y tiene como objetivo mejorar la forma en que interactúan los patólogos y los sistemas. El primer bloque de construcción consiste en una estrategia adaptable orientada a facilitar el acceso y la visualización del contenido de imágenes histopatológicas. El segundo bloque explora la extracción de información relevante de las imágenes mediante la explotación de información de características visuales y estructurales de la morfología y la arquitectura de los núcleos celulares. El tercer bloque apunta a integrar información de alto nivel del experto en el proceso de identificación de información relevante en las imágenes. Este bloque final no solo intenta lidiar con la brecha semántica, sino que también presenta una alternativa a la anotación manual, una tarea que demanda mucho tiempo y es propensa a errores. Se llevaron a cabo diferentes experimentos que demostraron que el marco de trabajo presentado no solo permite que el patólogo navegue y visualice imágenes, sino que también extraiga información de diagnóstico y pronóstico que potencialmente podría respaldar decisiones clínicas.Doctorad