AWS Machine Learning Blog

MARCH 18, 2025

Extraction of relevant data points for electronic health records (EHRs) and clinical trial databases. Data integration and reporting The extracted insights and recommendations are integrated into the relevant clinical trial management systems, EHRs, and reporting mechanisms.

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LLM NLP Data Integration AI 83

Heartbeat

OCTOBER 23, 2023

The Role of Data Scientists and ML Engineers in Health Informatics At the heart of the Age of Health Informatics are data scientists and ML engineers who play a critical role in harnessing the power of data and developing intelligent algorithms.

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Data Scientist Machine Learning Big Data Algorithm 52

The MLOps Blog

JUNE 27, 2023

An integrated model factory to develop, deploy, and monitor models in one place using your preferred tools and languages. Databricks Databricks is a cloud-native platform for big data processing, machine learning, and analytics built using the Data Lakehouse architecture. Robust security functionality.

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Machine Learning Metadata Data Scientist Data Quality 134

AWS Machine Learning Blog

JUNE 3, 2024

Perform an analysis on the transformed data Now that transformations have been done on the data, you may want to perform analyses to make sure they haven’t affected data integrity. About the Authors Rushabh Lokhande is a Senior Data & ML Engineer with AWS Professional Services Analytics Practice.

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Generative AI Categorization Auto-complete Auto-classification 118

AWS Machine Learning Blog

OCTOBER 2, 2024

However, scaling up generative AI and making adoption easier for different lines of businesses (LOBs) comes with challenges around making sure data privacy and security, legal, compliance, and operational complexities are governed on an organizational level. Tanvi Singhal is a Data Scientist within AWS Professional Services.

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Generative AI Data Ingestion AI AI 123

Pickl AI

JUNE 6, 2024

Machine Learning (ML) Machine Learning algorithms are like powerful engines, but they rely on clean fuel – clean data – to function effectively. Inaccurate data can lead to biased and unreliable models. But how can you personalize experiences and target marketing campaigns effectively if your customer data is a mess?

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Machine Learning Algorithm Business Intelligence Data Quality 40