Lung cancer screening is crucial for decreasing the death count from the disease but the government can’t scan everyone’s lungs. Here is an AI that identifies people who actually need screening.

Lung cancer is the deadliest cancer type, killing over a million people annually across the globe. The disease is responsible for the highest number of cancer deaths in both men and women in the US.

In fact, the death toll from lung cancer among women and men is nearly triple that of breast cancer and prostate cancer, respectively.

The UK government says AI could be “a real game-changer” for healthcare.

A leading neurosurgeon in the UK has said that brain surgery using artificial intelligence (AI) is possible within two years, making it safer and more effective.

“You could, in a few years, have an AI system that has seen more operations than any human has ever or could ever see,” Dr. Hani Marcus told BBC. Dr. Marcus is a consultant neurosurgeon at the National Hospital for Neurology and Neurosurgery and an Honorary Associate Professor at the University College (UCL) London Queen Square Institute of Neurology.

What does it take to bring life-changing medical robotic devices to reality? This is a question Dr. Gregory Fischer, founder and CEO of AiM Medical Robotics, explored in his keynote “From Concept to Commercialization: It’s not Brain Surgery, or is it?” at BIOMEDevice Boston, MA. As a researcher, professor, and lead investigator supported by federal government grants, director of a state-funded medtech accelerator, and founder of multiple medical device companies, Fischer has a unique perspective on conceptualizing, refining, and commercializing medical devices, as well as the challenges that come with each step.

Focusing on neurosurgery, he highlighted specific challenges clinicians face during procedures including an inability to leverage real-time intraoperative MR imaging for precision — surgeons must transfer a patient mid-surgery to an MRI in a separate room and sometimes even a separate building within the hospital complex — resulting in inefficient workflow and interruptions in sterility and anesthesia during transfers. Additionally, he mentioned limited compatibility with various MRI scanners, and an increased risk of human errors because of complex manual processes.

Integrating robotic assistance, he said, enhances the reachable target area and improves dexterity and precision of motion during such difficult procedures such as neurosurgery, adds enhanced feedback and virtual fixtures, reduces procedure time, and avoids ergonomic issues. An increase in intervention accuracy through inherent integration with image guidance tools, and improved diagnostic and therapeutic outcomes are also advantages of robotic assistance, according to Fischer.