Related Experiment Video
Updated: Jan 24, 2026
05:33
Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System
Published on: July 11, 2025
841
Artificial intelligence in digital pathology: a roadmap to routine use in clinical practice
Richard Colling1, Helen Pitman2, Karin Oien3
1Nuffield Department of Surgical Sciences, University of Oxford, John Radcliffe Hospital, Oxford UK.
The Journal of Pathology
|May 31, 2019
Summary
Artificial intelligence (AI) is set to revolutionize histopathology through image analysis. A new roadmap guides the development of AI tools for clinical use, addressing workforce shortages and ensuring regulatory approval.
Area of Science:
- Digital pathology and computational analysis.
- Integration of artificial intelligence (AI) in medical diagnostics.
- Pathology informatics and regulatory science.
Background:
- The field of histopathology is undergoing a digital transformation, driven by advancements in image analysis and machine learning.
- Artificial intelligence (AI) is poised to significantly impact clinical practice, particularly in diagnostic histopathology.
- A growing number of image analysis software tools are emerging, presenting both opportunities and challenges for clinical integration.
Purpose of the Study:
- To outline a roadmap for the development and clinical implementation of AI-driven software tools in histopathology.
- To foster collaboration between academia, industry, and clinicians in creating evidence-based AI solutions.
- To ensure that new AI tools meet regulatory approval for routine clinical use.
Main Methods:
- Development of a strategic roadmap by the NCRI Cellular Molecular Pathology (CM-Path) initiative and the British In Vitro Diagnostics Association (BIVDA).
- Focus on establishing a framework for the collaborative development of AI software tools.
- Emphasis on evidence-based development to meet regulatory standards.
Main Results:
- The roadmap provides a structured approach for advancing AI in histopathology.
- It addresses the need for a robust framework to guide the development of new diagnostic tools.
- The initiative aims to facilitate the transition of AI software from development to approved clinical application.
Conclusions:
- The integration of AI and image analysis in histopathology offers potential for novel clinical insights and addressing workforce challenges.
- A collaborative, evidence-based framework is crucial for the successful development and regulatory approval of AI tools.
- The outlined roadmap serves as a guide for stakeholders to navigate the complexities of implementing AI in diagnostic pathology.
Related Concept Videos
01:27Intelligence
8.5K
The term "intelligence" is complex because it refers to both behavior and individuals, and its interpretation varies across cultures. European Americans tend to link intelligence with reasoning and cognitive skills, while in Kenya, it is tied to responsible participation in family and social life. In Uganda, intelligence is seen as the ability to know the right actions and carry them out effectively, while the Iatmul people of Papua New Guinea associate it with the capacity to remember...
8.5K
01:29Measures of Intelligence
8.4K
Psychologists measure intelligence by using standardized tests that produce a score known as the intelligence quotient or IQ. To understand IQ tests, it's important to recognize the key principles behind their construction: validity, reliability, and standardization.
Validity refers to how well a test measures what it claims to measure. An intelligence test should accurately assess intelligence rather than another characteristic, like anxiety. Criterion validity is one way to evaluate this;...
Validity refers to how well a test measures what it claims to measure. An intelligence test should accurately assess intelligence rather than another characteristic, like anxiety. Criterion validity is one way to evaluate this;...
8.4K
01:20Multiple Intelligences Theory
8.9K
Howard Gardner's theory of Multiple Intelligence proposes that there are nine distinct types of intelligence, each reflecting different ways of interacting with the world. Introduced in 1983 and expanded in subsequent years, Gardner's framework challenges the traditional notion of a single, generalized intelligence.
8.9K
01:25Cattell's Theory of Intelligence
8.0K
Raymond Cattell, along with John Horn, made significant contributions to our understanding of intelligence by distinguishing between two types: fluid intelligence and crystallized intelligence.
Fluid intelligence involves the capacity to solve new problems and adapt to unfamiliar situations. It's the type of intelligence individuals use when they encounter a novel problem or puzzle that requires innovative thinking. For instance, figuring out how to operate a new gadget relies heavily on...
Fluid intelligence involves the capacity to solve new problems and adapt to unfamiliar situations. It's the type of intelligence individuals use when they encounter a novel problem or puzzle that requires innovative thinking. For instance, figuring out how to operate a new gadget relies heavily on...
8.0K
01:24Triarchic Theory of Intelligence
9.9K
Robert Sternberg's triarchic theory of intelligence posits that intelligence is composed of three distinct but interrelated components: analytical, creative, and practical intelligence.
9.9K
01:30Biological Influences on Intelligence
513
Intelligence is often thought to be linked to brain size, but the relationship is more complex than that. While brain size does correlate modestly with some abilities, like verbal skills, the connection is weaker for others, such as spatial reasoning. Other factors, like brain structure, also play crucial roles. For instance, despite Einstein's smaller-than-average brain, his parietal cortex, which is involved in spatial reasoning, was 15% wider, suggesting that neural density might matter...
513