AI-driven healthcare is seeing a boom in investment
Healthcare is becoming one of the most fast-growth areas for the application of artificial intelligence (AI).
The volume of medical data in our grasp is both overwhelming and hugely valuable. For the overstretched healthcare industry, combing through this data manually takes resource which all too often is non-existent.
Employing AI programmed to discern patterns and trends, however, can effectively make a nigh-on impossible task for humans and execute it in mere minutes or seconds. In essence, machines are able to use historical data to find the figurative ‘needle in the haystack’, which could be anything from a diagnosis, a suggested cure, or a statistical survival rate. The impact of AI on healthcare has potential to revolutionize the industry.
Since 2013, healthcare AI startups have raised $US 4.5 billion, putting them ahead of any other industry. In Q2 this year, funding hit an all-time high, with nearly 70 equity deals amounting to close to $US 600 million in investment (CB Insights).
It’s difficult to point to areas of healthcare that won’t benefit from the integration of AI, and that’s evidenced in the variety of applications already in trial. A partnership between Google’s DeepMind and Moorfields eye hospital, for example, saw 3D image recognition technology accurately diagnose 50 sight-threatening eye diseases.
In the long-term, this would help doctors quickly determine patients most in need of urgent treatment, which could ultimately save sight, and it’s easy to imagine how the same or similar technology could be used in other areas.
Earlier this year, the FDA (Food and Drug Administration) approved AI software that screened patients for diabetic retinopathy, negating the need for a second expert opinion, while in the world of big pharma, deep-learning has been employed to ‘design’ new drugs.
But while the implications of this ground-breaking research are huge, as is always the case, there are significant challenges that could hamper adoption.
Some of these can be said of any industry faced with the prospect of digital transformation, in that it will be a hard task to overcome the ‘inertia’ of current processes which are now redundant in order to experiment with new tech.
Others, however, are more nuanced to healthcare; as CB Insights points out, for example, there is no standard format or central repository for patient data in the States. In addition, many patient files contain handwritten notes or images, which poses a challenge for interpretation by AI systems.
These barriers, though, provide both up-and-coming and established tech companies with fuel for disruption.
Apple is one such firm; it’s building a “clinical research ecosystem” around the iPhone and Apple Watch, providing medical researchers with consistently-formatted and interoperable health data that had so far been more or less unattainable.
Another startup, meanwhile, allows users to conduct a urinalysis with their smartphone. Its product employs computer vision algorithms to analyze test strips under different lighting conditions.
Ground is being made at a significant pace with AI in healthcare, and despite the challenges that lay ahead, this year’s landmark in funding is a sign that innovative companies are just getting started in the development and integration of what will literally be life-saving technology.