How AI is Revolutionizing Healthcare
The real impact of AI in healthcare
Artificial intelligence (AI) is already bringing machine learning into big data management, customer relations, and many other areas across a multitude of industries. Expect it to play a huge role in healthcare in the not-too-distant future.
For instance, we may soon be looking back nostalgically at 1:1 contact in patient care. Why? Because face-to-face interactions are time-consuming, expensive, and not always necessary.
According to experts at Accenture, AI will also be a major factor in performing surgeries, developing new products, and conducting preventive interventions. Machines and technology will replace humans in some surgical settings. Phones will be used for self-care, as programs like Molly employ voice technology to help patients in their daily management of chronic illness.
Venture capital is pouring in, expected to reach $6.6 billion by 2021.
Predicting and diagnosing disease
As machines scan hundreds of thousands of medical records and treatment histories, it’s possible to predict who may be at risk for disease as well as make a diagnosis.
For example, the Moorfields Eye Hospital and University College of London tested AI’s ability to diagnose a certain eye disease. They used the program DeepMind to examine 14,000+ retinal scans of existing patents. The AI program accurately diagnosed the eye disease in 94% of cases—in minutes.
Physicians can crowdsource medical knowledge with the Human DX app, which compiles global data into a report containing the most likely diagnosis.
A question of reliability
On the clinical side, issues with AI adoption relate to trust and reliability, especially in the realm of predictive analytics. More testing of and experience with machine learning are needed. So, don’t expect clinicians to pivot right away. AI will be embraced when it is proven to enhance and/or accelerate a positive outcome for patients.
Breaking the “iron triangle”
The excitement around AI solutions includes a prediction from Accenture of nearly $150 billion in healthcare cost savings by 2026. These savings look to be especially strong in medical operations, as well as sales and marketing. Automation and machine learning will increase accuracy while improving customization in direct outreach. AI is also expected to reduce insurance fraud and streamline waste in hospital spending.
Indeed, it may finally be the way to break through the “iron triangle” in healthcare: access, affordability and effectiveness. To date, when one of these is improved, another area is compromised. But AI shows promise toward changing that equation while revolutionizing healthcare as we know it.
Keeping it real. With real results.
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