This workshop provides a comprehensive overview of digital pathology, its core principles, tools, and applications that are revolutionising the classical pathology field. Targeting pathologists, laboratory technicians, healthcare administrators, IT professionals, and students, ths workshop covera the fundamentals of digital pathology and discuss advanced technologies like whole slide imaging, AI-assisted analysis, and pathology cloud platforms. Participants will learn the advantages of digital pathology in enhancing diagnostic accuracy and improving workflow efficiency while addressing challenges such as implementation barriers and interoperability in digitally-enabled pathology environment. Case studies will showcase successful digital pathology adoptions in healthcare organisation, capaccitating attendees with the knowledge needed to navigate this evolving landscape effectively.
This workshop provides participants with a foundational understanding of Artificial Intelligence (AI) in pathology, emphasising its transformative impact on diagnostics, workflow optimization, and research. Targeting pathologists, laboratory technicians, healthcare administrators, AI developers, and students, this workshop covers AI applications, including machine learning and deep learning techniques. Participants will explore how AI enhances diagnostic accuracy and efficiency while integrating tools like image analysis and predictive modelling into pathology workflows. Challenges such as data quality, bias, and regulatory compliance will also be discussed. Case studies will illustrate successful AI implementations, showcasing their potential to advance pathology and precision medicine.
This workshop is designed to capacitate participants with the essential knowledge and skills to utilise Artificial Intelligence (AI) in analysing pathology images, aiming at enhancing diagnostic precision and efficiency. With pathologists, laboratory technicians, AI developers, researchers, and students, this workshop covers AI-driven tools and techniques used in image analysis, including deep learning and convolutional neural networks. Participants will explore applications of AI in detecting patterns and quantifying biomarkers, while also discussing challenges related to data quality and ethical considerations. Case studies will illustrate successful AI implementations, demonstrating its potential to improve clinical outcomes in pathology.
This workshop provides a methodological approach to implementing digital pathology and AI solutions in pathology laboratories, aimed at enhancing diagnostic workflows and operational efficiency. Targeting pathology lab managers, pathologists, IT specialists, policymakers, and students, participants will learn essential steps for planning and executing successful integration of digital tools. Infrastructure requirements, strategies for embedding AI into existing workflows, and challenges such as change management and interoperability are covered. Best practices for ensuring regulatory compliance and data security are also be discussed. Selected case studies are demonsratred illustrating successful roadmaps, and providing practical insights for participants to drive effective digital transformation in their laboratories.
This workshop introduces participants to the transformative applications of generative AI in pathology, emphasising potential to revolutionise diagnostics, research, and workflow optimization. Aimed at pathologists, AI developers, healthcare administrators, and students, this workshop provides a comprehensive overview of generative AI technologies and their applications in image synthesis, augmentation, and report generation. Participants will explore how generative AI can enhance diagnostic accuracy and create training datasets, particularly for rare diseases. Also, this workshop addresses critical generative AI challenges, legal, social, ethical and professional considerations, and requirements validation, supplemented by case studies reflecting successful implementations of generative AI in pathology.
This workshop provides critical insights and strategies for effective data management within digital pathology and AI contexts. Targeted at pathology lab managers, IT specialists, pathologists, AI developers, and students, this workshop explores best practices for ensuring data accuracy, security, and interoperability. Participants will learn approaches for managing the vast data generated by digital systems, including strategies for data quality and standardisation critical for AI model training. Key challenges, such as compliance with GDPR and HIPAA, data privacy, and security, are discussed addressed. Selected case studies with reference to successful data management strategies in digital pathology and AI contexts are provided with practical examples of effective implementation in healthcare.
This workshop aims to develop critical understanding of the ethical issues associated with digital pathology and AI in healthcare. Aimed at pathologists, healthcare professionals, administrators, AI developers, and students, ethical principles such as equity, transparency, accountability, and informed consent are critically discussed. Participants are also introduced to challenges related to AI biases affecting diagnostic accuracy and patient care, while addressing concerns around data privacy, security, and ownership. The workshop reflects on the need for regulatory compliance and ethical standards in AI deployment and provides strategies to ensure equitable access to digital tools. Real-world case studies are utilised in group-based settings to illustrate ethical dilemmas and their resolutions in digital pathology.
This workshop aims to capacitate participants with essential knowledge and skills to implement effective quality assurance (QA) and validation frameworks for AI-based digital pathology systems. Designed for pathologists, laboratory managers, healthcare administrators, AI developers, and students, this workshop focuses on ensuring the accuracy, reliability, and clinical utility of AI tools in pathology workflows. Participants will learn about QA principles, evaluation metrics, and validation methods AI-based pathology using case studies data. Also, this workshop addresses regulatory standards, including ISO and FDA guidelines, while highlighting challenges like algorithm bias and interoperability. Best practices and case studies are utilised in group-base settings to illustrate successful QA processes in AI pathology applications.
This workshop aims to introduce participants to multimodal approaches in digital pathology, focusing on the integration of diverse data sources—including imaging, clinical data, and genomic information—to enhance diagnostic accuracy and personalised care. Aimed at pathologists, data scientists, healthcare administrators, researchers, and students, the workshop covers principles of multimodal integration and the role of AI in analysing complex multimodal datasets. Participants will engage in group-based setting to reflect on how these approaches can improve patient outcomes while addressing challenges such as data standardisation and interoperability. Examples of selected case studies are utilised to illustrate the impact of multimodal strategies on clinical diagnostics and research advancements, capacitating attendees with practical implementation methods.
This workshop focuses on integrating telepathology and AI to enhance remote diagnostics and improve accessibility to pathology services. Aimed at pathologists, healthcare administrators, AI developers, researchers, and students, this workshop covers the core principles of telepathology and its synergy with AI methods technologies. Participants will explore applications such as automated slide analysis and decision support, reflecting the benefits of telepathology in providing diagnostics to, for example underserved areas. Additionally, the workshop addresses ethical issues regarding the implementation of AI-empowered telepathology and challenges regarding data security and connectivity. Selected case studies are discussed in group-based settings to leave participants with practical strategies for adopting and scaling such transformative approach to AI-empowered telepathology solutions in their practices.