Ep 71: AI in Business - Healthcare Use Cases

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How is AI taking form when it comes to helping businesses in healthcare? Dr. Nadia Boutaoui, Founder of NanoNares Inc,  joins us and shares valuable insights and use cases, discussing how AI can improve operations, enhance patient care, and revolutionize personalized medicine.

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Timestamps:
[00:00:18] Daily AI news

[00:05:55] How AI improves healthcare

[00:07:30] AI's role in caring for aging people

[00:11:17] Mistrust of AI in healthcare and hallucinations

[00:17:14] How AI helps with chronic diseases, cancer, and new drugs

[00:19:41] AI's role in healthcare customer service and burnout

[00:21:58] Fragmented US health system

Topics Covered in This Episode:
- Caring for aging individuals in their homes
    - Growing issue with the aging baby boomer population in the US.
    - Anticipation of integrating AI technologies for remote healthcare support.
- Future of personalized healthcare
    - Data monitoring and chatbots trained on personal data for treatment.
- Concerns about mistrust of AI and hallucinations
    - Inaccurate information provided by language models.
    - Need to address concerns as a society.
- Using chatbots to answer FAQs and provide personalized responses
    - Segmentation of patient population for targeted communication.
- AI to identify bottlenecks and improve staff utilization
    - Burnout as a significant problem in healthcare.
- Supercomputers for personalized treatments in cancer
    - DeepMind and IBM Watson using large data sets.
    - Collaboration between Regeneron Pharmaceuticals and Geisinger Health System for new drug development.
- Human oversight in advanced data analytics and AI
    - Human validation of recommendations.
- Concerns about data safety and third-party access
    - Importance of complying with HIPAA regulations

Keywords:
technology, healthcare, regulations, burnout, complexity, cost, training, workflows, safety, compliance, HIPAA, adoption, AI, electronic health records, intervention medicine, prevention, asthma, scheduling, specialists, patient care, aging individuals, diabetes, heart disease, centralized data centers, state laws, federal funding, user feedback, personalization, mistrust, hallucinations, chatbots, genomics, electronic medical records, drug development.

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