The potential benefits of AI for healthcare are tremendous; the sector's growing market value is estimated to reach $36.1 billion by the end of 2025.
AI's role in healthcare revolves around making better decisions, freeing up time for doctors and nurses, and bringing precision to processes. The core strengths of AI here are pattern recognition and workflow automation. AI will not only cut costs and help diagnose life-threatening diseases like cancer faster, but will also mean a more patient-centric approach to healthcare. This will lead to increased patient satisfaction, patient-doctor communication, and more accurate healthcare records.
Here are 8 major use cases for AI in healthcare.
1. Speeding Up Administrative Tasks
Medical staff waste a great deal of their time filling in various documents needed for patient tracking, financial and insurance purposes. Automating such admin tasks means significant time savings as well as increased transparency.
AI could be of great value here, especially through its natural language processing capability. It can recognize voice and text to let doctors and nurses use their hands as they dictate to the software. Another way AI developers say this technology could help the healthcare sector is by looking through old medical records and organizing them.
2. Automating Routine Tasks
A great deal of physicians’ daily work includes repetitive, low-level tasks which could be quickly taken on by AI. Examining medical images, including CT scans and X-rays, as well as interpreting lab tests is a full day’s job. Yet these tasks could one day be outsourced to AI in most cases. Human specialists would only have to examine those cases which are out of the ordinary, something that the machine is not able to classify.
Of course, much work will be needed to ensure the accuracy of such practices, but early studies show that a well-trained system can beat humans. LYNA, a system designed to detect breast cancer, shows correct results in 99% of cases.
3. AI Nurses
Nurses perform a lot of low-level routine tasks, which make a difference to a patient’s wellbeing but don’t require highly specialized skills. For example, reminding patients to take their medicine on time can have a significant impact on the treatment efficiency, and this is something that can be easily handled by AI on the patient’s smartphone or on a companion robot.
4. Digital Diagnosis
Since AI is excellent at identifying patterns, it makes sense to use this technology for diagnostic purposes. After all, it is precisely what doctors do: they look at symptoms, evaluate the patient’s history and try to make a conclusion based on the most reasonable classification.
People are already self-diagnosing themselves using questionable and anxiety-provoking search results, but using AI would be a more scientific approach based on medical evidence instead of subjective opinions from dubious sources. Such an AI-based app that’s already in use in the UK is Babylon, although this remains in its early stages and has had a skeptical reception in some medical journals.
5. Treatment Design & Precision Medicine
On the other end of the healthcare spectrum from general diagnosis, AI can help create personalized treatment plans. By looking into a patient’s medical records, conducting lab tests, even by using gene analysis, an AI system can identify potential threats for this patient and suggest a treatment plan.
Personalized, precision medicine is a new way of providing care. Instead of identifying general solutions and making a patient fit a profile, this takes a reverse approach. It looks at a patient’s problems first and tries to find the right solution. The Jackson Laboratory has secured millions in grants for research programs with these personalized aims.
6. Drug Selection
Most of the time, creating new drugs can take years and cost billions. Training a neural network with the results of past attempts can guide the process of finding new treatments and speed up the drug selection process. This can also rule out the need to test every combination. A real-life use of this was a program trying to find new therapies for Ebola through drug repurposing conducted by University of Toronto startup Atomwise.
7. Robotic Surgery
Surgeons are unlikely to lose their jobs to robots any time soon. Yet, having a trustworthy assistant – such as surgical robot Modus V, which detects sensitive areas like nerves and blood vessels – can increase the safety of procedures and speed up a patient’s recovery.
This technology has been around a while; one example, already 12 years old, is the inch-long Heartlander robot, which offers stabilization, sensing, and enhanced access with minimal discomfort during surgery.
A more recent use of AI in burn surgery estimates the affected area with great precision and helps doctors plan the intervention in detail instead of relying on rules of thumb.
8. Healthcare Supervision
When it comes to health, prevention is the best defense. AI linked to wearables such as fitness bracelets, smartwatches or other devices can help people monitor their health and stay on top of problems such as diabetes, heart disease, and more. A simple SMS from an app can prevent a crisis and keep the person safe. It can also motivate patients by showing progress when they are following a diet or an exercise routine.
We should never underestimate the ability of AI tools to help us preserve our health instead of treating a disease. It is safe to assume that the future will be more about prevention and less about intervention – all through using innovative AI-centered technologies.