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1
intro
2
preamble
3
anomaly detection
4
the challenges we set out to solve
5
anomaly detection at a glance
6
ml algorithm development process
7
why data annotation?
8
data annotation...
9
a comprehensive ai impl journey
10
anomaly identification framework
11
machine learning model framework - continuous training for optimized performance
12
llm + guardrails
13
challenges in bert models
14
generative ai and prompt engineering
15
gen ai - llm's approach
16
thank you
Description:
Explore the application of generative AI and transformers in healthcare through this conference talk from Conf42 Python 2024. Delve into anomaly detection techniques, challenges in healthcare AI implementation, and the importance of data annotation. Learn about comprehensive AI implementation journeys, anomaly identification frameworks, and continuous training for optimized machine learning model performance. Discover the integration of Large Language Models (LLMs) with guardrails, challenges in BERT models, and the approach of generative AI in healthcare applications. Gain insights into prompt engineering and the potential of AI to revolutionize healthcare practices.

Leveraging Generative AI and Transformers in Healthcare - Anomaly Detection and Implementation

Conf42
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