The future of pathology is digital

Area of Science:

• Medical Informatics
• Digital Pathology
• Artificial Intelligence in Medicine

Background:

• Modern medicine extensively utilizes information systems, archives, and artificial intelligence (AI).
• Established standards exist for information models and workflows in radiology.
• Pathology, cardiology, and radiation therapy are increasingly defining their own system demands.

Purpose of the Study:

• To highlight the growing role of AI and digital systems in supporting medical workflows.
• To discuss the specific technical demands and data challenges in digital pathology.
• To explore the transition from traditional microscopy to virtual microscopy supported by AI.

Main Methods:

• Review of current information system applications in medicine.
• Analysis of established standards in radiology and emerging demands in other disciplines.
• Examination of digital pathology workflows, including slide digitization and AI/machine learning tools.

Main Results:

• AI and digital systems are integral to modern medical workflows, providing essential support.
• Pathology presents significant technical challenges due to complex workflows and large data volumes from digitized slides (gigabytes per biopsy).
• Digital pathology enables virtual microscopy, integrating AI and machine learning to assist pathologists.

Conclusions:

• AI and digital systems are crucial for advancing medical practices, especially in data-intensive fields like pathology.
• The digitization of pathology slides and the implementation of AI tools represent a significant technological shift in histopathological diagnosis.
• Virtual microscopy powered by AI promises to enhance pathologist support and diagnostic capabilities.