AI in Healthcare
Last updated
Last updated
AI is revolutionizing healthcare by improving diagnostics, personalizing treatments, and streamlining clinical workflows. It allows for faster and more accurate analysis of medical data, leading to better patient outcomes.
One of the most promising applications of AI in healthcare is in medical imaging. IBM’s Watson Health, along with other AI-driven diagnostic tools, is used to analyze radiology images to detect early signs of cancer, such as breast cancer, with greater accuracy. In 2020, Google Health developed an AI system capable of identifying breast cancer in mammograms more effectively than human radiologists. By applying deep learning models, AI systems can analyze thousands of medical images, reducing human error and improving early detection rates.
AI analyzes a person's electrocardiogram (ECG), evaluating not only the shape of the ECG waves, their duration and amplitude, but also the frequency of the signal oscillation at each point of the recording. This kind of analysis notices minor changes in the electrical activity of the heart that a person is unable to notice, and determines dysfunction of the heart muscle even before the onset of severe irreversible changes. This also provides unlimited opportunities for remote diagnostics and monitoring of cardiovascular diseases using gadgets without visiting a medical institution.
AI automatically analyzes images obtained using magnetic resonance imaging (MRI), computed tomography (CT) and X-rays for pathological changes, increasing the safety of the method, detecting subtle pathologies and dramatically reducing image interpretation time - from weeks to seconds.
AI is also being used to predict the progression of diseases. For instance, Google’s DeepMind developed an AI model called AlphaFold, which predicts the 3D structure of proteins. Understanding protein folding is key to many diseases, including Alzheimer’s and Parkinson’s. By accurately predicting how proteins fold, AlphaFold provides crucial insights into disease mechanisms, opening the door to new drug discoveries.
AI-powered virtual assistants are increasingly used in healthcare to provide patients with personalized advice and reminders. Babylon Health, for example, offers an AI-driven platform where users can chat with a virtual doctor to assess symptoms and receive recommendations for treatment. This reduces the burden on healthcare providers and improves access to care, particularly in underserved areas.
