The latest medical devices can improve people's quality of life and help guide us to better ways to live. What if analyzing the data those devices produce could accelerate all those benefits?

At Abbott, we build life-changing technologies — such as the revolutionary FreeStyle Libre system that monitors glucose readings — that have changed how people understand their health and create new ways to interact with their doctors to improve their care.

In many ways, healthcare is just starting to apply the latest artificial intelligence tools to turn data into better health. Translating innovation into technologies will help people predict their risk and treat the world's most serious diseases.

How the future of health care will improve thanks to data-enabled technologies was one of the focus areas at the Wall Street Journal's Tech Health conference in San Francisco. Abbott leaders helped shape discussion around the overlap of data-driven insights and improved health outcomes.

"Using machine learning, we've found that in combination, patient demographics plus hematological measures and blood proteins are much more accurate in diagnosing heart attacks as well as heart disease than current methods," said Dr. David Spindell, divisional vice president of medical and clinical affairs for Abbott's diagnostics business, at a panel focused on how technology tools such as artificial intelligence (AI) will improve medical devices.

"AI helps us gain insights into health care," Spindell continued. "It helps us develop products for unmet needs by finding these key insights. The thing is that we can't stop at that – we have to use machine learning to continue to refine these products."

Abbott's diagnostics platforms – more than 10,000 globally – track over 1 billion anonymized test results a year back to a central database that presents an opportunity to best understand how our products perform.

This performance data is paired with clinical data from healthcare organizations globally and can provide insights such as combining a patients' age and sex with the levels of a protein found in the heart to help healthcare providers diagnose heart attacks.

From heart disease to cancer predictions to understanding hard-to-diagnose mild traumatic brain injury, the major medical problems in all markets are already being changed by AI and the potential from data analysis. "The insights and products developed through Big Data will only be implemented if they deliver health care at improved cost efficiencies or better care for the same costs," Spindell said.

Treating diabetes – with more than 400 million people living with the condition today – presents a rich opportunity for AI technologies. The data coming from a FreeStyle Libre system can be combined with other patient factors such as diet, activity level and medications taken, said Dr. Marc Taub, divisional vice president of product development for Abbott's diabetes business.

"We could then give a more personalized recommendation on how much insulin to take and give a more optimized therapy," Taub discussed. "Diabetes is a condition that's ripe for AI applications – it's generating tremendous amounts of data and patients are at the center of all that data."

In the field, the visualization of glucose reading data that comes from the new generation of connected continuous glucose monitoring devices has changed how Dr. Eden Miller of Bend, Oregon, works with her patients dealing with diabetes. Before these connected devices, relying on people to self-report their own glucose readings that required fingersticks yielded inconsistent data that wasn't particularly helpful in diagnosing the occasionally sudden swings in blood glucose levels experienced by people with diabetes, Miller said.

With just two weeks of readings, a person's distinctive glucose patterns emerge in what she calls a "roadmap" that illuminates how the body processes foods, and that data both empowers patients to better understand their condition and gives healthcare professionals insights into more effective treatments.

"It's not there to say this these readings are good or bad – it's just a roadmap," Miller said to the panel, encouraging doctors to remove emotional stigmas to sugar consumption and effects on the body. But with the glucose data "I can then overlay treatments, medications and lifestyle changes to empower the patient. It's beautiful because all that data is compiled into a snapshot that's a single page - it really provides a resource to the patient as well."

Health technology companies continue to create data-driven connected devices that give new insights into health conditions. How that data gets harnessed in ways that help treat and predict disease represents one of the most interesting areas of technology to watch.