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/https://libri-media.knygos-static.lt/6a338cfd-a10c-41e0-8559-b17ef5150ade/1)
- Autorius: Praveen Kumar M
- Leidėjas: Elsevier Science
- Metai: 2026
- Puslapiai: 180
- ISBN-10: 0443219192
- ISBN-13: 9780443219191
- Kalba: Anglų
Application of Python in the Healthcare Technology (el. knyga) (skaityta knyga) | knygos.lt
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Aprašymas
Application of Python in Healthcare Technology: Medical Data Analysis and Developing ML/AI Models provides comprehensive coverage of the Python programming language from a medical-based perspective. With a strong focus on utility-based learning rather than technical-based learning of Python, this title clarifies how the application of Python in the healthcare technology industry has a meaningful impact on patient care through the development of deep learning models for early prediction of diseases and the development of Clinical Decision Support System (CDS). In 13 chapters, an extensive range of topics pertaining to the intersection of Python and medical sciences is covered. Coverage defines how to set up an environment to work with python, describes Python class, methods, and functions, explains both basic and advanced statistical analysis in Python, and provides a tool to assist in the development of deep learning models such as API, Git, Github, NumPy, Pandas, and SciPy.
- Autorius: Praveen Kumar M
- Leidėjas: Elsevier Science
- Metai: 2026
- Puslapiai: 180
- ISBN-10: 0443219192
- ISBN-13: 9780443219191
- Kalba: Anglų
Application of Python in Healthcare Technology: Medical Data Analysis and Developing ML/AI Models provides comprehensive coverage of the Python programming language from a medical-based perspective. With a strong focus on utility-based learning rather than technical-based learning of Python, this title clarifies how the application of Python in the healthcare technology industry has a meaningful impact on patient care through the development of deep learning models for early prediction of diseases and the development of Clinical Decision Support System (CDS). In 13 chapters, an extensive range of topics pertaining to the intersection of Python and medical sciences is covered. Coverage defines how to set up an environment to work with python, describes Python class, methods, and functions, explains both basic and advanced statistical analysis in Python, and provides a tool to assist in the development of deep learning models such as API, Git, Github, NumPy, Pandas, and SciPy.
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