Artificial intelligence is no longer a science fiction concept and has found its unique purpose while stirring controversies in numerous fields – in the entertainment industries, director and producer Paul Epstein voices against it, while in the financial services sector, Dr. Patrice Latinne welcomes it with open arms.
As healthcare becomes increasingly complex and data-driven, it is not unexpected that multiple tech firms and entrepreneurs acknowledge AI’s tremendous potential This article outlined four ways in which AI can transform healthcare.
Despite facing push backs from some other industries, for example, Emmy-nominated Paul Epstein has been vocal about the potential thread of AI to the film and TV industry, AI can be game-changing in sectors such as healthcare. A critical advantage of AI in healthcare is its ability to reduce the likelihood of individuals requiring intensive care by effectively preventing illness.
Despite being one of the most effective measures in the healthcare system, the power of illness prevention is often limited by medical workers’ capacity. Therefore, AI technology can revolutionise healthcare by relieving overworked healthcare workers of illness prevention responsibilities.
Via data analysis and deep learning, AI-powered healthcare applications can function as personal health consultants to their users. These applications can put together highly individualised and comprehensive health and lifestyle plans for each user. Based on the individual plans, they can then promote healthier behaviour and assist with proactive lifestyle management
Thanks to pattern recognition, AI-powered applications can also identify patients at risk of developing a life-threatening condition faster and more reliably than most humans, regardless of whether the health risk is environmental, genetic, or caused by other factors.
Decision-making is another one of the major categories of AI applications in healthcare. It involves both assisting in disease diagnoses and making recommendations on treatment methods.
The healthcare industry has already recognised AI technology’s ability to accurately detect severe diseases like cancer and heart disease at their earliest stages when they are more treatable. Additionally, AI enables doctors and caregivers to diagnose complicated conditions confidently using worldwide medical care databases.
IBM’s digital healthcare tool, Watson, for example, can review and store far more medical information than humans can, including every journal, symptom, and case study, creating a global database.
Furthermore, by leveraging cognitive technology and machine learning, healthcare workers can take advantage of the vast power of big data analytics, which results in better decision-making based on evidence. Big data analytics can improve healthcare outcomes by helping professionals make appropriate, timely treatment decisions and analysis-based predictions. By creating suitable administrative checklists, this technology can also help healthcare staff complete tasks on time.
Applying robotic and automatic technologies in surgeries is another key usage of AI in healthcare.
Nowadays, most advanced medical facilities employ AI-driven assistant robots that perform basic surgical tasks for surgeons, such as positioning surgical instruments. Using these robots reduces the possibility of human errors caused by fatigue and generally enhances surgeons’ performances during interventions, resulting in superior treatment outcomes. Furthermore, robots can also use reinforcement learning to perform and record subtasks such as tube insertion and soft tissue manipulation, for which precise analytical models are challenging to create otherwise.
The appearance of merging techniques in AI continues to push the limits of how we can apply AI in healthcare. For example, a recently developed robot model completed a complicated medical operation on its own, raising the question of whether human surgeons are irreplaceable. As artificial intelligence technologies bloom in surgery, we can only imagine what the future holds.
Training and Research
Professional training and research are some of the more recent applications of AI in healthcare. AI technology can further transform healthcare by equipping researchers and learners with additional cutting-edge instruments.
AI-driven programs can simulate naturalistic medical scenarios that better depict real-life circumstances than conventional algorithms and models while still providing measurable data and variables. AI-based training programmes can also optimise training efficiency by learning from trainees’ previous behaviour. By compiling previous training responses and identifying repeated patterns, programmes can automatically modify their training process constantly.
On the other hand, researchers can use realistic medical simulation technology as a more ethical, time-efficient, and affordable alternative for pre-clinical and clinical trials. For example, drug researchers can utilise AI simulations to examine how new drugs influence the human body in the laboratory. Consequently, not only can they run the simulation indefinitely without demanding living test objects, but they can also access valuable data more quickly. Both elements accelerate the authorisation procedure for new drugs.