Artificial intelligence has proven its usefulness for accurately interpreting medical scans. The systems can analyze medical images in minute detail, draw upon vast quantities of diagnostic data, and supplement the work of human pathologists. Because these capabilities will revolutionize diagnostics, IDTechEX predicts that the global market for AI medical imaging diagnostics will expand by 10,000 percent by 2040.

Breast Cancer Diagnostics

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Clinicians rely on medical imaging to detect and treat breast cancer. An AI developed by Google called LYNA has shown 99 percent accuracy in finding metastatic breast cancer tumors. Another breakthrough has emerged from researchers in Berlin, Germany, and Oslo, Norway. Their tissue-section analysis system uses AI to examine images pixel by pixel. To help pathologists check the images, the AI highlights the exact areas within the image used to reach a diagnosis.

MRI Scanner at Narayana Multispeciality Hospital, Jaipur. Credit: GeorgeWilliams21

Pathology Software Systems

The software company Proscia located in Philadelphia, Pennsylvania, has developed an imaging workflow for pathologists. The software processes digital medical images and applies AI to detect patterns that a pathologist should review.

Although the software from Proscia remains experimental, medical AI from Ibex Medical Analytics is already in use in hospitals and laboratories around the world. Ibex’s AI replicates the methods used by pathologists to study medical images. The results are fast and highly accurate cancer diagnoses that provide pathologists with rapid second opinions. The Ibex AI also can catch issues that pathologists miss.

Axial MRI FLAIR image showing abnormal hyperintense signal in the mesial dorsal thalami indicative of Wernicke Encephalopathy. Credit: Jto410

In general, pathology is often a collaborative exercise. Traditionally, pathologists have consulted with each other when images appear ambiguous. An AI system makes an expert analysis readily available.

How do you imagine AI can improve medical diagnostics?


Our globally cited analysts are mostly PhD-educated subject matter experts. Crucially, our analyst team also includes successful experienced business leaders. We conduct primary research through interviews, site visits and events across the World, getting the insight first. New technologies tend to be hyped. We focus on assessing the needs of end-users to identify problems where new technologies can add value.

Based on extensive research, we provide a clear view of the real situation in complex subject matters, regardless of the popular conception. IDTechEx hosts the World’s largest events on some of the topics we cover, in addition to daily web journals. This has helped to create a significant contact base in the topics we cover, allowing us to connect you with customers.

ABOUT Proscia

For 150 years, cancer diagnosis has been limited to the subjective interpretation of what the human eye could see under a microscope. To change the way we diagnose and research cancer, we need new tools — computational applications that leverage AI and machine learning — to show us the information hidden in every tissue sample.

That’s why we started Proscia. Our mission is to perfect cancer diagnosis with intelligent software that changes the way the world practices pathology. We’re building tools for the mind that are redefining pathology and giving pathologists better ways to fight cancer today.

ABOUT Ibex Medical Analytics

Ibex Medical Analytics is the pioneer in AI-powered cancer diagnostics in pathology. We are a multidisciplinary team of entrepreneurs, data scientists, software engineers and medical experts, working together to realize our vision: Transforming cancer diagnostics with AI and improving patient care.

Pathologists are challenged to provide accurate and timely analysis as the number of tests increases every year. Ibex uses artificial intelligence (AI) to develop clinical-grade solutions that help detect cancer as accurately as a human pathologist.

Our Galen Platform uses algorithms to analyze images, detect and grade cancer in biopsies and point to other findings with high clinical importance, helping pathologists reduce diagnostic error rates. and enable a more efficient workflow.

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