5 ways to use generative AI in healthcare

 

Facilitating medical training and simulations

Generative AI in healthcare can come up with realistic simulations replicating a large variety of health conditions, allowing medical students and professionals to practice in a risk-free, controlled environment. AI can generate patient models with different diseases or help simulate a surgery or another medical procedure.

Assisting in clinical diagnosis

Generating high-quality medical images. Hospitals can employ generative AI tools to enhance the traditional AI’s diagnostic abilities. This technology can convert poor-quality scans into high-resolution medical images with great details, apply anomaly detection AI algorithms, and present the results to radiologists.

Real-life examples

A team of researchers experimented with Generative Adversarial Network (GAN) models to extract and enhance features in low-quality medical scans, transforming them into high-resolution images. This approach was tested on brain MRI scans, dermoscopy, retinal fundoscopy, and cardiac ultrasound images, displaying a superior accuracy rate in anomaly detection after image enhancement.

Contributing to drug development

Designing and generating new molecules with desired properties that researchers can later evaluate in lab settings. Predicting properties of novel drug candidates and proteins. Generating virtual compounds with high binding affinity to the target that can be tested in computer simulations to reduce costs. Forecasting side effects of novel drugs by analyzing their molecular structure.

AI in Healthcare

Automating administrative tasks

Extract data from patients’ medical records and populate the corresponding health registries. Microsoft is planning to integrate generative AI into Epic’s EHR. This tool will perform various administrative tasks, such as replying to patient messages.