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Abstract
<p class="first" id="d4376923e89">In modern clinical practice, digital pathology has
a crucial role and is increasingly
a technological requirement in the scientific laboratory environment. The advent of
whole-slide imaging, availability of faster networks, and cheaper storage solutions
has made it easier for pathologists to manage digital slide images and share them
for clinical use. In parallel, unprecedented advances in machine learning have enabled
the synergy of artificial intelligence and digital pathology, which offers image-based
diagnosis possibilities that were once limited only to radiology and cardiology. Integration
of digital slides into the pathology workflow, advanced algorithms, and computer-aided
diagnostic techniques extend the frontiers of the pathologist's view beyond a microscopic
slide and enable true utilisation and integration of knowledge that is beyond human
limits and boundaries, and we believe there is clear potential for artificial intelligence
breakthroughs in the pathology setting. In this Review, we discuss advancements in
digital slide-based image diagnosis for cancer along with some challenges and opportunities
for artificial intelligence in digital pathology.
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