Machine learning

News • New technology in healthcare

Sectra launches vendor-neutral integration for machine learning applications

International medical imaging IT and cybersecurity company Sectra is launching vendor-neutral access to machine learning in its enterprise imaging platform. Sectra customers will be able to utilize Sectra’s own machine learning applications as well as virtually any application, regardless of vendor. This will give healthcare providers a unified entry point to a best-of-breed portfolio. It will…

News • Clinical collaboration platform

Carestream demonstrates AI tools on at SIIM machine learning showcase

Carestream Health is demonstrating advanced imaging analytics software tools designed to enhance value in the delivery of medical care as part of its Clinical Collaboration Platform at the SIIM Machine Learning Showcase being held Sept 26-27 at Johns Hopkins Hospital in Baltimore, Md.

Article • Digital Pathology

Deep Blue meets Hematoxilin and Eosin

In the nineties Deep Blue, the famous chess computer, defeated Kasparow. Only a year ago Google’s Deepmind managed to master the ancient Chinese Go, known for its utmost complexity.

Article • Evolution of a field

Will software steal the heart of cardiology?

Celebrating 40 years of PCI, cardiologists fret over their future with big data, machine learning and robots.

Article • Algorithms

Pattern recognition: Machines are learning fast

Language recognition on the smartphone, spam filters in the e-mail programme, personalised product recommendations by Amazon or Netflix – all share one feature: they are based on an algorithm that recognises patterns in a set of data. This artificial generation of knowledge is called machine learning.

Article • Technology overview

Artificial intelligence (AI) in healthcare

With the help of artificial intelligence, computers are to simulate human thought processes. Machine learning is intended to support almost all medical specialties. But what is going on inside an AI algorithm, what are its decisions based on? Can you even entrust a medical diagnosis to a machine? Clarifying these questions remains a central aspect of AI research and development.