Introduction
Precision Medicine: Improving Healthcare with Data Science and Machine Learning explores the shift toward personalised healthcare, where treatments are tailored to individual patient characteristics. Driven by advances in data science and machine learning, precision medicine enables more accurate diagnoses, better predictions, and targeted therapies.
This book provides a comprehensive overview of how data-driven technologies are transforming modern healthcare. It covers key areas such as clinical decision support systems, predictive modelling, genomic analysis, and biomarker discovery. Through a combination of foundational concepts and real-world applications, the book highlights the growing role of big data and intelligent algorithms in improving patient outcomes and healthcare efficiency.
It also addresses important challenges, including data privacy, ethical considerations, and regulatory issues, while offering insights into the future of data-driven healthcare.
Key Features
- - Integration of precision medicine with data science and machine learning.
- - Case studies on genomic analysis, biomarker discovery, and personalised treatments.
- - Coverage of clinical decision support and predictive modelling techniques.
- - Discussion of ethical, privacy, and regulatory challenges.
- - Practical insights for implementing machine learning in healthcare.
- - Future perspectives on data-driven and personalised medicine.
Target Readership :
Researchers, professionals, and postgraduate students in healthcare informatics, computational biology, and medicine.