In his May I/O 2017 keynote, Google CEO Sundar Pichai addressed an “important shift,” their sea change, from “searching and organizing the world’s information to artificial intelligence (AI) and machine learning (ML).” In his 2016 Founder’s Letter, Pichai laid out his vision: “The next big step will be for the very concept of the 'device' to fade away. Over time, the computer itself — whatever its form factor — will be an intelligent assistant helping you through your day. We will move from mobile first to an AI first world.”

Recently, Pichai made good on that promise by backing a group of startups that use AI in healthcare technology. One uses voice recognition commands for record-keeping, team collaboration and other administrative tasks, reportedly saving doctors 10 hours a week. Others use the technology for early diagnosis of sepsis, assistance for people with mobility trouble and construction of a platform for wearables.

Google is just the first of the giants to step into the fray. 

When it comes to investing in AI, a great deal has changed over the years. 

2007 saw 31 new deals take place. By 2016, the number skyrocketed to 322 deals, with a total of $3.6 billion invested. For all healthcare IT companies, venture capital funding during first nine months of 2017 alone passed the total for 2016, which was

Fast-Paced Innovation in Health Care

Today, AI works best through perception and cognition using voice and image recognition and ML — learning without humans explicitly programming them to perform that process. AI in health care uses algorithms (a process for problem-solving) to analyze medical data, especially prevention or treatments that could impact patient outcomes. AI programs are working most effectively in fields like personalized medicine/genetics; drug discovery and development; and disease identification and management.

“Putting real-time data in the hands of providers helps them better help patients,” says Deborah Muro, CIO for El Camino Hospital in California, like by developing an algorithm to analyze patients at high risk of falls. Gathering certain types of information, such as how frequently patients leave their beds or use their call lights, can be used to alert nurses to check on patients in order to prevent potential falls, she says.

AI Solutions for Health Care: Now and Later

Both now and on the horizon, AI innovations in health care are more exciting than ever. Consider these technologies:

• Chatbots can take “patient inquiries via phone, e-mail or live chat.”

• Virtual assistants “enable conversational dialogues and pre-built capabilities that automate clinical workflows.” Some can to even detect depression through subtle clues in speech or gesture.

• Robot "doctors" are conversational robots that explain lab results.

• Surgery consultants support workflow and build predictive modeling.

• AI prosthetics refers to when a “bionic hand is fitted with a camera which instantaneously takes a picture of the object in front of it, assesses its shape and size and triggers a series of movements in the hand” in response.

• Disease detectors can “identify tuberculosis on chest X-rays,” and some can highlight “areas that might indicate the potential presence of cerebral bleeds.”

By virtue of design, AI and ML solutions for health care will keep getting better. You can expect these technologies to enhance diagnosis and prevention of diseases, help researchers get more out of the data they collect and even empower labs to produce drugs tailored to a person’s DNA. For AI in health care, the future certainly looks bright.