The Potential of AI in Healthcare

The good news is that most large healthcare organizations are beginning to make use of some form of AI. However, we’re still early in the journey of learning how we can apply artificial intelligence to make healthcare better.

One of the primary use cases is using machine learning and AI to make predictions. Organizations are using AI to predict everything from emergency department volumes (to get a better handle on staffing and triage) to predicting which treatments might be most effective for women who develop breast cancer.

Healthcare teams are also using natural language processing to improve the interpretation of patient scans by augmenting the work of human radiologists.

When a radiologist looks at a scan, they’re typically looking for one thing, which is the reason you have that image done. But many times in the background, there's something else that can be seen. So as radiologists are dictating, natural language processes are being used to call out these secondary issues for follow-up, where previously those things might go unnoticed…so it's a preventive way of trying to get out ahead of a future health problem.

The biggest promise of AI in healthcare comes from changing clinical workflows. AI can add value by either automating or augmenting the work of clinicians and staff. Many repetitive tasks will become fully automated, and we can also use AI as a tool to help health professionals perform better at their jobs and improve outcomes for patients.

The healthcare organizations that will be the most successful are the ones that will be able to fundamentally rethink and reimagine their workflows and processes and use machine learning and AI to create a truly intelligent health system.