Artificial intelligence is all around us. We often interact with it every day – whether it’s talking to Siri on an Apple device, using an Alexa smart speaker or interacting with the digital answering service at your utility company. Health care has greatly benefitted from the use of artificial intelligence, coupled with advancements in modern technology. For example, the past decade has born witness to the rise of robotic surgery: from 2012 to 2018, the use of robots for all general surgery procedures has increased from 1.8% to 15.1%, according to a recent analysis. Digitizing processes and care operations, as well as the adoption of electronic medical records systems, have provided huge opportunities for collaboration and continuity of care between hospitals and providers. The next wave of technological innovations in health care is going beyond robots and electronic records to analyze data and provide predictive insights. For example, artificial intelligence (AI) can predict health conditions and provide advisories for treatment and determine the impacts of certain drug interactions. It can also accelerate the development of vaccines, as was the case with some of the first vaccines for COVID-19. Now, AI is increasingly being explored for use in health care settings by providers, health insurance payers and life sciences companies.
What is AI?
Simply put, AI is computer-generated intelligence based on knowledge and information provided as inputs by humans to simulate the way humans think and act. You may encounter AI when using computer speech recognition on your phone or voice-enabled electronics including home speakers or digital assistants like Siri or Alexa; during phone calls in which a digital customer service system mimics a human when navigating a menu of options, or when chatting with virtual agents on a website. Here are some of the simple ways AI is being used in the medical field already:
- Online appointment scheduling and check-ins for appointments
- Appointment and immunization reminder calls, emails and texts
- Drug dosage and drug interaction algorithms
- Clinical decision support for providers
- Analysis of images including CT scans, X-rays and MRIs
Radiology is one of the major areas in medicine that has seen an increase in the use of AI to assist radiologists in analyzing images, including the use of computer-assisted diagnostics in mammography screenings for breast cancer.
What are the possibilities for AI in health care?
Larger-scale applications of AI to aid in detecting diseases and diagnosing them are part of what many believe is the future of medicine. Health care systems generate an enormous amount of data on patients, which creates an opportunity to apply AI to process and generate actionable insights for medical professionals. Systems can be taught to recognize patterns in datasets to aid in identifying a particular group of symptoms or anomalies in an image. Machines can be trained for a specific scenario using machine learning (ML) and store the knowledge and machine models, commonly referred to as algorithms. Algorithms analyzing a data set can deliver a probability that a patient would be at risk for developing a blood clot, for example, based on their heart rate and blood pressure. They could also predict if a patient would need knee surgery, as another example, based on symptoms and other factors. This type use of AI holds tremendous opportunities for more personalized health care in the future as providers would be able to better recommend preventive steps and treatment options – and ultimately, improve personalized care accessibility and drive better health outcomes for all. More from MIBluesPerspectives:
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