This Week in Healthtech:
AI Beats Doctor’s Diagnosis

Week Ending 06-01-18: Artificial Intelligence beats doctor’s diagnoses, Tampa hospital makes major plans for AI implementation, FDA approves OsteoDetect

AI Beats Doctors at Cancer Diagnoses

German researchers have developed a tool that correctly identified 95% of melanomas tested. Their early research shows that the AI-powered tool, convolutional neural network (CNN), performed better at detecting skin cancer than highly trained dermatologists. Developers see this tool assisting dermatologists by providing an “expert opinion.” Read more.

Tampa General Teams up with GE Healthcare to Create Artificial Intelligence Data Center

Tampa General and GE Healthcare have plans to open a 9,000 square foot care center meant to improve patient experiences and outcomes using predictive analytics – a major move toward AI and healthcare integration. Expected to open in 2019, Tampa General CEO says, “we want to leverage this system to improve efficiency and shorten the time patients are in the hospital by better managing their care.” Read more.

Is AI Set to Transform the Future of Healthcare?

The latest article from HealthcareIT News highlights potential opportunities for the impending healthcare transformation, while combating the fear that the “health ecosystem will be run by robots.” Citing automation, streamlined processes, and increased efficiency as support for implementing AI in healthcare, all leading to improved diagnostic outcomes. Read more.

FDA Approves AI Algorithm To Help Doctors Diagnose Fractures Faster

FDA approval of OsteoDetect’s software further supports the growing tech trend in healthcare. Using artificial intelligence to detect common wrist fractures, Robert Ochs, PhD, from the FDA’s Center for Devices and Radiological Health says “artificial intelligence algorithms have tremendous potential to help health care providers diagnose and treat medical conditions.” Read more.

Providers Leverage AI to Address High-Risk Patients at the Right Time

One New Orleans hospital system is leveraging AI technology to reduce codes by identifying at-risk patients and predicting adverse events within hours. Using Epic EHR data, Ochsner Health Systems implemented a machine-learning platform that has helped reduce codes by 44% in some hospitals. Read more.