How AI and Machine Learning Impact Cloud-Managed Networking: HEALTHCARE Edition

In our recent blog posts, we’ve been looking at the roles AI and Machine Learning play in different industries, and how this technology is making an impact for network managers, business managers, partners, and customers. We’ve covered hospitality, education, and retail in previous blogs. This week, we will be looking at the role of AI and Machine Learning in healthcare.

In retail, the use of AI and Machine Learning is about driving sales and ROI. In education, it’s about student engagement and learning. In hospitality, it’s about guest services. In healthcare, it’s about saving lives. In 2015, medical error and misdiagnosis accounted for 10 percent of all deaths in the United States. By leveraging AI and Machine Learning, we can save lives and conserve resources at the same time.

Lowering Hospital Re-Admittance Rates

Virtual nursing assistants could reduce unnecessary patient hospital visits and lower the burden on the medical staff. For routine monitoring of levels, dosages, and checkups, the use of AI can monitor patients after they leave the hospital and lower re-admittance rates.

Avoid Missing a Diagnosis

Back in 2017, Apple and Stanford unveiled a heart study program using the Apple Watch’s heart rate sensor to collect data on irregular heart rhythms and notify users who may be experiencing atrial fibrillation (AFib). AFib, the leading cause of stroke, is responsible for approximately 130,000 deaths and 750,000 hospitalizations in the US every year. Many people don’t experience symptoms, so AFib diagnosis is often missed. As we live in a more connected world, by putting Machine Learning to work on mass amounts of anonymized medical information, doctors and researchers can learn about new diseases, new trends, and build new medications.

Aid in Detecting Disease

Using AI to diagnose patients is undoubtedly in its early stages, but there have been some interesting use cases. A Stanford University study used an AI project to detect skin cancer against dermatologists, and it performed at the same level as humans. As more information is collected, it’s likely that AI diagnosis will become even more accurate over time.

The Future

Using AI and Machine Learning is going to allow us to learn more and more about how diseases respond to medicine, how diseases form, and what we can do to prevent. Plain and simple: lives will be saved in the future because of AI and Machine Learning in healthcare.

All Posts in this Series

  1. Key Industry Use Case Edition: Introduction to AI and Machine Learning for Cloud-Managed Networking
  2. How AI and Machine Learning Impact Cloud-Managed Networking: RETAIL Edition
  3. How AI and Machine Learning Impact Cloud-Managed Networking: HOSPITALITY Edition
  4. How AI and Machine Learning Impact Cloud-Managed Networking: EDUCATION Edition
  5. How AI and Machine Learning Impact Cloud-Managed Networking: HEALTHCARE Edition
  6. How AI and Machine Learning Impact Cloud-Managed Networking: MANUFACTURING Edition
  7. How AI and Machine Learning Impact Cloud-Managed Networking: TRANSPORTATION Edition
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Aerohive simplifies and secures your network using a cloud-managed solution with machine learning and artificial intelligence capabilities. AI-driven innovation enables customers to discover untapped business insights, allowing them to implement informed decisions based on these predictive analytics, while providing unrivalled flexibility in deployment, management and licensing of cloud-managed wireless, switching, routing and security solutions.

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