AI is bettering diagnostics, clinical infrastructure, and preventative care. The authorities and medical profession are already changing attitudes, regulations, and the underlying technology. The Chinese company Lenovo is changing and using everything from hospital administration to algorithm development to improve hospital systems.
While not yet replacing doctors but improving efficiency, massive changes and early advances are occurring using smarter machines and virtual assistants. Over the next few years, technology will use voice recognition with the likes of a virtual assistant on your smartphone. It will record what it learns about your habits and past behavior and use these in diagnostics.
If you go to the hospital for a scan, say, an algorithm will scan and interpret your data and highlight any irregularity. This will assist the physicians in drawing attention to certain issues and irregularities. This, in turn, helps the medical staff ensure that nothing is missed in any diagnosis, speeding up the procedure.
Enhanced resolution and analysis will allow remote scanning and diagnosis, even of small and subtle symptoms. Doctors must be careful not to be overwhelmed by all the tracking data, as they do not want clinics to be inundated with phone ‘pings.’
What is known as telemedicine, which involves consulting a doctor from the comfort of your home, was happening during the pandemic, but an electronic physician could radically reduce costs. Even if a real person steps in to review and approve, an AI-led interview and data assessment would undoubtedly increase efficiency. They will be a useful diagnostic supplement available upon request.
There will undoubtedly be a growing demand for everything to be available at your fingertips through a website or app. It will reshape low-risk patient care. More AI may lead to chatbot-style physician care, where a series of targeted questions combined with biometrics will help people find the proper care.
Gradually, misconceptions about AI will erode, and the successful distribution of assisted technology should increase the general public’s trust in living by the algorithm’s diktat. Much of the AI information recording happens in the background, and the data collected will gradually improve the public’s trust, even in the highly regulated world of medicine.
Genomic sequencing is a revolution. Mapping a genome opens a window into inherited conditions, susceptibility to disease, potential responses to treatment, and countless other insights. But the process takes time, and to do this, high-performance computers are needed.
What we must imagine is this kind of scenario: a patient anywhere in the world could share a blood sample and deep biometrics, and then the AI at the local level steps in for the initial analysis, finding patterns, diagnosing the patient, and recommending the next steps. Then, as necessary, the case escalates worldwide to the right expert, who now has all that information at their fingertips.
In addition, the possibility of assisting and treating with augmented reality tools and both efficiency and quality soar while costs plummet. Trials already ongoing make us optimistic that this will rapidly become a reality.
Consider that AI algorithms are only as powerful as the data available. The essential data upon which machine learning thrives will push big data analytics in healthcare to nearly $70 billion by 2025. Who can predict how this will empower patients and providers in 20 years?
The ability to access real-time data will let research medics monitor any biological changes in inpatients while gathering data and identifying the patients’ responses to various treatments. Indeed, the possibilities are endless.
