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Data Science for Healthcare
By Nitin Singh
0 - Default Title
Description
In this book, you will learn how healthcare data is captured and structured, how to clean and prepare it, and how to build predictive models for problems like sepsis risk and length of stay. The book covers natural language processing for clinical notes, computer vision for imaging, and generative AI for tasks such as question answering and denial review. It also shows how to evaluate models, monitor them in production, and design workflows that people will actually use.
By the end of this book, you will know how to move from an idea to a working healthcare AI solution. You will be able to frame the use case, choose the correct data, build and evaluate a model, explain its output, and position it in a clinical or business workflow.
WHAT YOU WILL LEARN¿ Understand how healthcare data is captured, structured, and governed.¿ Build predictive models for sepsis risk, readmission, and length of stay.¿ Apply NLP to clinical notes for extraction, summarization, and question answering.¿ Use computer vision techniques to analyze scans and imaging data.¿ Leverage generative AI and RAG for clinician-facing decision support.¿ Design evaluation, monitoring, and explainability for production healthcare models.¿ Integrate AI outputs into real clinical and operational workflows.
WHO THIS BOOK IS FORThis book is for anyone working at the intersection of data and healthcare, including data scientists, analysts, machine learning engineers, clinical informatics teams, and digital health leaders. It is designed for readers who want practical, working examples of AI in patient risk prediction, documentation support, and workflow automation.
Product details
Binding:
Paperback
Number of Pages:
244
Release Date:
2025-12-01
Publication Date:
2025-12-01
Publisher:
BPB Publications
Languages:
Original:
English
ISBN10:
9365897920
ISBN13:
9789365897920
Minimum Reading Age:
18
Maximum Reading Age:
18
Weight:
360 g
Height:
152 cm
Width:
229 cm
Thickness:
13 cm
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