AI refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions. The term may also be applied to any machine that exhibits traits associated with a human mind such as learning and problem-solving.
We can divide AI in medicine into three categories: Patient-Oriented AI, Clinician-Oriented AI and Administrative-and-Operational-Oriented AI. And by combining these three categories, we can achieve our goals as healthcare team.
How is AI used today in healthcare?
There are various capacities where AI is emerging as a game-changer for healthcare industry. Below are a few examples in use today:
Radiology – AI solutions are being developed to automate image analysis and diagnosis. This can help highlight areas of interest on a scan to a radiologist, to drive efficiency and reduce human error. There is also opportunity for fully automated solutions – to automatically read and interpret a scan without human oversight – which could help enable instant interpretation in under-served geographies or after hours.
Surgery – Robots can analyze data from pre-op medical records to guide a surgeon’s instrument during surgery, which can lead to a 21% reduction in a patient’s hospital stay. Robot-assisted surgery is considered « minimally invasive » so patients won’t need to heal from large incisions. Via artificial intelligence, robots can use data from past operations to inform new surgical techniques. The positive results are indeed promising. One study that involved 379 orthopedic patients found that AI-assisted robotic procedure resulted in five times fewer complications compared to surgeons operating alone. A robot was used on an eye surgery for the first time, and the most advanced surgical robot, the Da Vinci allows doctors to perform complex procedures with greater control than conventional approaches.
What is the Future of AI in Medicine?
The Future is Almost Here! With tech giants investing heavily in healthcare innovation, AI has received a massive boost in recent years. Google’s DeepMind Health project promises to speed up clinical procedures by processing an enormous amount of medical information in a matter of minutes. IBM’s Watson system helps in early diagnosis of heart failure through patient data collected during their hospital visits. The latter system has found its way into many hospital wards, and has been far more effective than traditional methods.