Internet of Things - Technology focus

NIH’s new Rapid Acceleration of Diagnostics initiative, or RADx Tech, aims to bring accurate, rapid, and easy-to-use COVID diagnostic tests to all Americans.

Future of Public Transit, Health & Wellness in COVID-19 Economy

Versions of Contact Tracing Apps  ABC’s Maggie Rulli is on the Isle of Wight off the coast of mainland England where they are testing out a contact tracing app in an effort to contain the spread of COVID-19.

When it comes to fighting cancer, nearly all technologies can be explored as potential solutions. Thanks to a team of engineers, doctors might have a new Artificial Intelligence (AI) program to help them and their patients fight against the deadly disease.

Researchers from the University of Central Florida's Center for Research in Computer vision created an AI with impeccable 'vision' for spotting small tumors in CT scans. Most human radiologists have a success rate of 65 percent in identifying smaller tumors on a scan, the team noted. This new AI system bumps that percentage up to 95 percent accuracy, giving the radiologists a second set of keen 'eyes' for them to use. 

Training the AI to sniff out tumors

Like many AI systems, it needed to learn what exactly a tumor looked like and how those tumors vary in different parts of the body.  “We used the brain as a model to create our system,” said Rodney LaLonde, a doctoral candidate. (In addition to being a computer science engineer, LaLonde also serves as captain of UCF’s hockey team.) LaLonde was assisted by Engineering Assistant Professor Ulas Bagci.   “You know how connections between neurons in the brain strengthen during development and learn? We used that blueprint, if you will, to help our system understand how to look for patterns in the CT scans and teach itself how to find these tiny tumors," LaLonde continued. 

The engineers took a cue from popular facial recognition algorithms, like the one found in the iPhone X. Most of that software continually scans faces in order to find a particular pattern, and in those patterns, eventually, finds a match. 

In this case, the team collaborated with the National Institute of Health and the Mayo Clinic to scan thousands of CT scans into their AI software. Each CT scan taught the AI what to look for in tumor size and shape, among other trademarks. 

Improving chances by improving technology

“I believe this will have a very big impact,” Bagci said. Bagci has worked extensively in biomedical imaging and machine learning, hoping to improve the state of clinical imaging. Before coming to UCF, he was the lab manager for NIH's Center for Infectious Disease Imaging Lab in Radiology and Imaging Sciences.

“Lung cancer is the number one cancer killer in the United States and if detected in late stages, the survival rate is only 17 percent," he explained. "By finding ways to help identify earlier, I think we can help increase survival rates.”

Jeff Welser, vice president of research at International Business Machines Corp., discusses the company's five primary areas of focus over the next five years with Bloomberg's Emily Chang

LAX is testing fever-detecting thermal cameras in an attempt to keep air travel safe amid COVID19

How can we stop the next pandemic before it starts? Disease researchers Pardis Sabeti and Christian Happi introduce Sentinel, an early warning system that detects and tracks viral threats in real time — and could help stop them before they spread. Learn more about the cutting-edge technology that powers the system and how the Sentinel team is helping scientists and health workers during the coronavirus pandemic. (This ambitious plan is a part of the Audacious Project, TED’s initiative to inspire and fund global change.)