Radiology
AIMed Champions Connect Q2 Report
This research project sought to assess the extent to which artificial intelligence (AI) is being deployed at a population health level
This research project sought to assess the extent to which artificial intelligence (AI) is being deployed at a population health level
Michael Phillips, Partner and MD of Intermountain Ventures, and Ohad Arazi, CEO of Zebra Medical Vision discuss how they are leveraging AI to analyse existing images to identify treatment gaps, coordinate care, and stratify risks accordingly.
Artificial intelligence is here, and it’s here to stay and the number of companies developing AI technologies for radiology applications is increasing rapidly.
This video examines the current hurdles to the widespread adoption of AI in Radiology and highlights the many hurdles providers need to identify to ensure they overcome them prior to investing any resources to evaluating AI.
Some might wonder why there has been such a sudden avalanche of AI algorithms in radiology. With the recent IT advancements that have allowed Machine Learning tools to be more accessible, and affordable, and radiology being one-of if not, the most data rich departments in healthcare, it’s no surpris
AI-Rad Companion Chest X-ray automatically characterizes radiographic findings for a valid chest scan in the lung and pleura.
This research project sought to assess the extent to which artificial intelligence (AI) is being deployed at a population health level
AI-Rad Companion Chest X-ray automatically characterizes radiographic findings for a valid chest scan in the lung and pleura.
Breast cancer is the most frequently diagnosed cancer among women, impacting 2.1 million women worldwide each year and causing the greatest number of cancer-related deaths amongst women. It is estimated that 627,000 women died from breast cancer in 2018, approximately 15% of all cancer-related femal