Healing with Data: Machine Learning in Healthcare
Language: English
Published by Independently published, 2024
- Softcover
- New

Seller: California Books, Miami, FL, U.S.A.California Books
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Condition: New
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- Title
- Healing with Data: Machine Learning in Healthcare
- Author
- Singh, Mehakpreet; Sharma, Priya
- Publisher
- Independently published
- Publication year
- 2024
- Condition
- New
- Binding
- Soft cover
- Language
- English
- ISBN 13
- 9798325631306
Healing with Data: Machine Learning in Healthcare
Overview:
- Explore the intersection of cutting-edge technology and compassionate healthcare in "Healing with Data: Machine Learning in Healthcare."
- This comprehensive guide offers insights into the transformative potential of Deep Learning and Machine Learning in revolutionizing medical practice, research, and patient care.
Key Features:
- Understanding Machine Learning in Healthcare: Gain a foundational understanding of machine learning principles and their applications in healthcare settings.
- Practical Applications: Discover real-world examples and case studies showcasing how machine learning is enhancing diagnostic accuracy, optimizing treatment decisions, and improving patient outcomes.
- Medical Imaging and Diagnosis: Explore the role of machine learning in medical imaging, image classification, and computer-aided diagnosis (CAD), revolutionizing the field of radiology and imaging diagnostics.
- Precision Medicine and Predictive Analytics: Learn how AI-driven predictive analytics and precision medicine initiatives are ushering in a new era of personalized healthcare, tailored to individual patient characteristics and genetic profiles.
- Clinical Decision Support Systems (CDSS): Understand the importance of clinical decision support systems (CDSS) powered by machine learning algorithms in augmenting clinical decision-making processes and improving patient safety.
- Ethical Considerations and Regulatory Compliance: Navigate the ethical and regulatory considerations surrounding the use of ML in healthcare, ensuring patient privacy, fairness, and accountability.
Who Should Read This Book?
- Healthcare professionals seeking to leverage machine learning technologies to enhance clinical practice and patient care.
- Researchers and academics interested in exploring the latest advancements in healthcare informatics and medical AI.
- Students and educators in the fields of healthcare administration, data science, and biomedical engineering.
- Technology enthusiasts curious about the transformative potential of ML in revolutionizing the healthcare industry.
Why Choose "Healing with Data"?
- Accessible and comprehensive guide suitable for both technical and non-technical readers.
- Written by experts in the fields of machine learning, healthcare informatics, and medical imaging.
- Packed with practical insights, case studies, and real-world examples to illustrate key concepts.
- Offers a balanced exploration of the opportunities and challenges of integrating Algorithms into healthcare practice.
- Provides actionable takeaways and best practices for implementing machine learning solutions in healthcare settings.
Embark on a journey into the future of healthcare with "Healing with Data: Machine Learning in Healthcare" and discover how ML is reshaping the landscape of medicine, one algorithm at a time.
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