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Kirjailija

Yassine Bouchareb

Kirjat ja teokset yhdessä paikassa: 2 kirjaa, julkaisuja vuodelta 2026, suosituimpiin kuuluu Data Science in Healthcare. Vertaile teosten hintoja ja tarkista saatavuus suomalaisista kirjakaupoista.

2 kirjaa

Data Science in Healthcare

Data Science in Healthcare

Gayathri Delanerolle; Yassine Bouchareb; Konstantinos V. Katsikopoulos; Peter Phiri

TAYLOR FRANCIS LTD
2026
sidottu
This book brings together everything you need to know about data science within healthcare systems, with a primary focus on showing how to advance automated and non-automated analytical methods for extracting valuable insights from healthcare data. It draws upon a range of interconnected disciplines, including machine learning, big data analytics, statistics, pattern recognition, computer vision, and Semantic Web Technologies. The book emphasizes the practical application of these disciplines in the healthcare domain inclusive of quality assurance, governance and regulatory overview. It includes instructional chapters on data science in healthcare as a foundation, then progresses to showcase real world, successful examples of data science and AI applications in healthcare, highlighting their range of usefulness and potential. Intended primarily for healthcare professionals, including clinical academics, academics and trainees working in the healthcare or medical sectors, this book offers crucial insights into cutting-edge data science technologies, essential for driving innovation in both healthcare businesses and patient care.
Data Science in Healthcare

Data Science in Healthcare

Gayathri Delanerolle; Yassine Bouchareb; Konstantinos V. Katsikopoulos; Peter Phiri

TAYLOR FRANCIS LTD
2026
nidottu
This book brings together everything you need to know about data science within healthcare systems, with a primary focus on showing how to advance automated and non-automated analytical methods for extracting valuable insights from healthcare data. It draws upon a range of interconnected disciplines, including machine learning, big data analytics, statistics, pattern recognition, computer vision, and Semantic Web Technologies. The book emphasizes the practical application of these disciplines in the healthcare domain inclusive of quality assurance, governance and regulatory overview. It includes instructional chapters on data science in healthcare as a foundation, then progresses to showcase real world, successful examples of data science and AI applications in healthcare, highlighting their range of usefulness and potential. Intended primarily for healthcare professionals, including clinical academics, academics and trainees working in the healthcare or medical sectors, this book offers crucial insights into cutting-edge data science technologies, essential for driving innovation in both healthcare businesses and patient care.