Articles

Navigating the Regulatory and Reimbursement Pathways to Get to Market

Navigating the Regulatory and Reimbursement Pathways to Get to Market

Artificial intelligence relies heavily on algorithms – a set of computer instructions to accomplish a task. But the power actually comes from the data. Here’s why.

Continue Reading
From AI Model to Validated Medical Device

From AI Model to Validated Medical Device

In this article, we get into why validating these tools is a pivotal step—not only to build trust among pathologists but also as a vital quality assurance for patients, ensuring accurate and reliable diagnoses in real-world settings.

Continue Reading
AI in Point-of-Care Histology: Opportunities and Obstacles

AI in Point-of-Care Histology: Opportunities and Obstacles

AI is revolutionizing many fields, and the analysis of H&E histology is no exception. This classic method, used for over a century by pathologists, has now entered the digital age. It offers new opportunities for AI to assist in diagnostics and research. However, adapting these advances to histology in a point-of-care setting brings new challenges like scarce labeled data and variations across devices and facilities.

Continue Reading
Building AI models from whole slide images

Building AI models from whole slide images

Artificial intelligence relies heavily on algorithms – a set of computer instructions to accomplish a task. But the power actually comes from the data. Here’s why.

Continue Reading
The Importance of Data in Building an AI Diagnostic

The Importance of Data in Building an AI Diagnostic

Artificial intelligence relies heavily on algorithms – a set of computer instructions to accomplish a task. But the power actually comes from the data. Here’s why.

Continue Reading
Opportunities and Obstacles for AI in Pathology

Opportunities and Obstacles for AI in Pathology

To recognize the advantages of AI tools and rely on their results in your everyday work, you need to understand how these tools are developed for pathology. With this understanding, you can make informed decisions about their use.

Continue Reading
Computer Vision: Buy or DIY?

Computer Vision: Buy or DIY?

Four reasons why you might need to build your own computer vision solution.

Continue Reading
Vision Foundation Models: When Does Size Matter?

Vision Foundation Models: When Does Size Matter?

Large vision models may seem attractive, but domain-specific models can get you farther.

Continue Reading
Getting Started with Computer Vision for Histopathology

Getting Started with Computer Vision for Histopathology

A reading list for anyone looking to adapt their machine learning expertise to computational pathology.

Continue Reading
Unlock the Potential of Your Proprietary Images with a Domain-Specific Foundation Model

Unlock the Potential of Your Proprietary Images with a Domain-Specific Foundation Model

The benefits of a self-supervised vision model for generalizability, adaptability, and more.

Continue Reading
How to Reduce the Trial-and-Error of Machine Learning Development

How to Reduce the Trial-and-Error of Machine Learning Development

Machine learning projects are complex and iterative with uncertain outcomes. These are some ways to improve the efficacy of ML development.

Continue Reading
Impact AI: 10 Most Downloaded Episodes

Impact AI: 10 Most Downloaded Episodes

The episodes that I highlight below are the 10 most downloaded. The common themes are food and disease: farming, climate risks, food waste, cancer, and medical imaging.

Continue Reading