Summary
The AI revolution isn’t just one of many challenges healthcare organizations must face to keep their competitive edge. It’s an opportunity to empower your employees to discover better ways to offer healthcare services. This module discussed many scenarios in which AI can be a powerful assistant in all stages of the healthcare journey: from research, drug development, and supply chain to doctors’ consultations. You’ve read real success stories from leading companies in the sector that prove AI generates value in healthcare.
To achieve these goals, Microsoft offers a wide range of services. Microsoft Cloud for Healthcare incorporates Azure, Microsoft Dynamics 365, and Microsoft 365. These products are customized for healthcare professionals and include embedded AI. There are also specific products for the industry, such as Azure Health Data Services. To implement AI potential at its best, Azure OpenAI Services delivers state-of-the-art generative AI models.
Now that you reviewed this module, you should be able to:
- Describe goals and challenges in life sciences, pharmacology, and healthcare
- Identify opportunities for AI in life sciences, pharmacology, and healthcare
- Describe common use cases in life sciences, pharmacology, and healthcare
- Explore how Microsoft AI technologies can help health providers
Use these resources to discover more
- To learn more about what Microsoft can do for your healthcare organization, visit our Microsoft Cloud for Healthcare website.
- To learn more about all the features covered in Azure Health Data Services, visit our Azure Health Data Services website.
- Stay up to date with Microsoft AI, visit our AI website.
- To learn more about Microsoft commitment to responsible AI, visit our Responsible AI website.
- To learn more about the models delivered by Azure OpenAI Service, read our technical documentation on Azure OpenAI Service.
- To learn more about privacy and security in Azure OpenAI Service, read our legal documentation on Azure OpenAI Service.
- To learn more about our intelligent business applications, visit our Dynamics 365 AI homepage.
- To learn more about our low-code tools in Power Platform, visit our Power Platform website AI Builder homepage.
- To learn more about all the prebuilt AI models available at Azure AI Services, read our technical documentation on AI Services.
References
- Bhasker, Shashank; Bruce, Damien; Lamb, Jessica, & Stein, George, “Tackling healthcare’s biggest burdens with generative AI,” McKinsey & Company, July 10 2023.
- Richens, Jonathan G.; Lee, Ciarán M., and Johri, Saurabh, “Improving the accuracy of medical diagnosis with causal machine learning,” Nature, 2023.
- World Health Organization, "Health workforce," 2023.
- U.S. Department of Health and Human Services, "Addressing Health Worker Burnout: The U.S. Surgeon General’s Advisory on Building a Thriving Health Workforce," 2022.
- D Magazine, "Healthcare Financial Trends for 2022," 2022.