Machine Learning for Everyone: Simplifying Healthcare Analytics with BigQuery ML

<p>Machine learning (ML) transforms healthcare by enabling predictive analytics, personalized treatments and improved patient outcomes. However, traditional ML workflows often require specialized skills, infrastructure and resources, limiting accessibility for many healthcare professionals. This paper explores how BigQuery ML Cloud service helps healthcare researchers and data analysts to build and deploy models using SQL, without need for advanced ML knowledge.</p>

Authors

Publication Details

Journal
Journal of Artificial Intelligence Machine Learning and Data Science
Published
2025-03-05
DOI
https://doi.org/10.51219/jaimld/salari-ma/520
Citations
1
Primary Topic
Machine Learning in Healthcare
Type
article
Field-Weighted Citation Impact
2.48
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article

Machine Learning for Everyone: Simplifying Healthcare Analytics with BigQuery ML

Behrouz Rahmani, Mohammad Amir Salari
1 citations
Journal of Artificial Intelligence Machine Learning and Data Science
Machine Learning in Healthcare
2.48
article

Machine Learning for Everyone: Simplifying Healthcare Analytics with BigQuery ML

Behrouz Rahmani, Mohammad Amir Salari
article en
1 citations

Abstract

<p>Machine learning (ML) transforms healthcare by enabling predictive analytics, personalized treatments and improved patient outcomes. However, traditional ML workflows often require specialized skills, infrastructure and resources, limiting accessibility for many healthcare professionals. This paper explores how BigQuery ML Cloud service helps healthcare researchers and data analysts to build and deploy models using SQL, without need for advanced ML knowledge.</p>

Journal of Artificial Intelligence Machine Learning and Data ScienceVol. 3(1)
Openalex Percentile: Top 11%
Machine Learning in Healthcare
2.48
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Machine Learning for Everyone: Simplifying Healthcare Analytics with BigQuery ML — Behrouz Rahmani, Mohammad Amir Salari · Journal of Artificial Intelligence Machine Learning and Data Science (2025) | TGRS Research Map | TGRS