An Artificial Intelligence (AI) revolution is coming. By 2026, Accenture predicts that AI will achieve a market value of $150 billion. This will change the way that every conceivable sector functions, especially healthcare.
This healthcare revolution can’t come soon enough. As the COVID-19 pandemic spreads, healthcare systems are coming under increasing strain. But with new solutions, we can turn the tide against the virus to ensure that healthcare is prepared for future pandemics.
Here are a few of the ways that Artificial Intelligence is helping to transform diagnosis and treatment.
Improving Surgery with Surgical Robots
Most people tend to think of robots when they think of AI, be it WALL-E, R2-D2 or even RoboCop.
But what many people don’t think of are robot surgeons. Today, hospitals are starting to use robots to perform complex surgical procedures with precision. In doing so, these robots enhance human capabilities and enable new, safe treatments.
Equipped with cameras and mechanical arms, surgical robots come in all shapes and sizes. Some focus on improving accuracy using 6D motion-sensing technology. Others focus on enhancing specialised surgeries like heart therapy. But regardless of how the robots differ, they all have a common trait. They help reduce surgery-related complications.
Strengthening the Patient Experience
Even before the coronavirus pandemic, healthcare systems were under constant strain. Many patients don’t get to see their doctor or experience a poor service because there are too many patients. In the US, 96% of complaints are about a lack of customer service, paperwork confusion and negative experiences with admin staff.
AI is changing that. It is helping the healthcare sector to process more data faster and more efficiently. This is enabling hospitals and surgeries to see more patients while giving them the time and care each patient requires. Also, AI is helping to manage patient flow by empowering doctors and nurses to see patients remotely. Apps like Babylon feature personalisation, an AI-powered chatbot and functionality for video-call appointments with doctors.
AI is helping to alleviate pressure on hospitals, clinics and surgeries while ensuring that patients get the health advice they need. With advances like these, we should see improvements to patient experience throughout the healthcare sector.
Embracing AI by Digitising Data
Elsewhere, and most importantly given the current situation, AI and Machine Learning algorithms are helping to predict how new diseases spread. The world’s authorities and public health bodies are using this information in the fight against new viruses.
The technology works by taking vast quantities of data, gathered from previous epidemics as well as other data sources like the movement of people and goods, to estimate how diseases spread. The insights ensure that governments can deploy resources where they’re most needed. It also shows both what actions to take and when to take them, such as cancelling flights and enforcing lockdown measures.
Likewise, AI is helping to reduce risks. One company, KenSci, has combined AI with big data – like who will get sick – to predict clinical, financial and operational risks. This allows for better resource planning, and showcases the everyday application and benefit of a technology like epidemic prediction.
Predicting Epidemiological Spread
All these advances are impressive, but we won’t achieve any of them and roll them out to healthcare systems everywhere without data.
Data is the lifeblood of AI. It needs data to both function and improve, so now is the time for health bodies to take digital transformation more seriously. Fortunately, there are some positive signs that healthcare is moving in the right direction. For example, the NHS’s digital arm, NHSX, is planning for AI and testing a variety of tools to bring safe, data-driven innovation to healthcare.
However, we’ll only achieve AI’s full potential in healthcare when real efforts are made to digitise and consolidate data. Ethical issues like how that sensitive data is collected, stored and used must be answered. But the possibilities for improving healthcare mean we must make those decisions and start implementing the right infrastructure now.