Data science has the potential to influence and improve fundamental services such as the healthcare sector. This book recognizes this fact by analyzing the potential uses of data science in healthcare. Every human body produces 2 TB of data each day. This information covers brain activity, stress level, heart rate, blood sugar level, and many other things. More sophisticated technology, such as data science, allows clinicians and researchers to handle such a massive volume of data to track the health of patients. The book focuses on the potential and the tools of data science to identify the signs of illness at an extremely early stage.…mehr
Data science has the potential to influence and improve fundamental services such as the healthcare sector. This book recognizes this fact by analyzing the potential uses of data science in healthcare. Every human body produces 2 TB of data each day. This information covers brain activity, stress level, heart rate, blood sugar level, and many other things. More sophisticated technology, such as data science, allows clinicians and researchers to handle such a massive volume of data to track the health of patients. The book focuses on the potential and the tools of data science to identify the signs of illness at an extremely early stage.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Prof. Seifedine Kadry's research focuses on data science, education using technology, system prognostics, stochastic systems, and applied mathematics. He is an ABET (Accreditation Board for Engineering and Technology) Program Evaluator for computing and engineering technology. He is a Fellow of IET, IETE, and IACSIT. He is a distinguished speaker for the IEEE Computer Society.
Inhaltsangabe
1. PPH 4.0: a privacy-preserving health 4.0 framework with machine learning and cellular automata 2. An automatic detection and severity levels of COVID-19 using convolutional neural network models 3. Biosensors and disease diagnostics in medical field 4. Brain tumor recognition and classification techniques 5. Identifying the features and attributes of various artificial intelligence-based healthcare models 6. Classification algorithms and optimization techniques in healthcare systems representation of dataset in medical applications 7. A knowledge discovery framework for COVID-19 disease from PubMed abstract using association rule hypergraph 8. Predictive analysis in healthcare using data science: leveraging big data for improved patient care 9. Data science in medical field: advantages, challenges, and opportunities 10. Decentralizing healthcare through parallel blockchain architecture: transmitting internet of medical things data through smart contracts in telecare medical information systems 11. Machine learning in heart disease prediction 12. U-Net-based approaches for brain tumor segmentation 13. Explainable image recognition models for aiding radiologists in clinical decision making 14. Prediction of heart failure disease using classification algorithms along with performance parameters 15. Cancer survival prediction using artificial intelligence: current status and future prospects 16. Heart disease prediction in pregnant women with diabetes using machine learning 17. Healthcare using image recognition technology 18. Integration of deep learning and blockchain technology for a smart healthcare record management system 19. Internet of things based smart health and attendance monitoring system in an institution for COVID-19 20. Medical diagnosis using image processing techniques 21. Harnessing the potential of predictive analytics and machine learning in healthcare: empowering clinical research and patient care 22. Predictive analysis in healthcare using data science 23. Recommender systems in healthcare-an emerging technology 24. Robotics: challenges and opportunities in healthcare 25. A new era of the healthcare industry using Internet of Medical Things 26. Single cell genomics unleashed: exploring the landscape of endometriosis with machine learning, gene expression profiling, and therapeutic target discovery 27. Analyzing the success of the thriving machine prediction model for Parkinson’s disease prognosis: a comprehensive review
1. PPH 4.0: a privacy-preserving health 4.0 framework with machine learning and cellular automata 2. An automatic detection and severity levels of COVID-19 using convolutional neural network models 3. Biosensors and disease diagnostics in medical field 4. Brain tumor recognition and classification techniques 5. Identifying the features and attributes of various artificial intelligence-based healthcare models 6. Classification algorithms and optimization techniques in healthcare systems representation of dataset in medical applications 7. A knowledge discovery framework for COVID-19 disease from PubMed abstract using association rule hypergraph 8. Predictive analysis in healthcare using data science: leveraging big data for improved patient care 9. Data science in medical field: advantages, challenges, and opportunities 10. Decentralizing healthcare through parallel blockchain architecture: transmitting internet of medical things data through smart contracts in telecare medical information systems 11. Machine learning in heart disease prediction 12. U-Net-based approaches for brain tumor segmentation 13. Explainable image recognition models for aiding radiologists in clinical decision making 14. Prediction of heart failure disease using classification algorithms along with performance parameters 15. Cancer survival prediction using artificial intelligence: current status and future prospects 16. Heart disease prediction in pregnant women with diabetes using machine learning 17. Healthcare using image recognition technology 18. Integration of deep learning and blockchain technology for a smart healthcare record management system 19. Internet of things based smart health and attendance monitoring system in an institution for COVID-19 20. Medical diagnosis using image processing techniques 21. Harnessing the potential of predictive analytics and machine learning in healthcare: empowering clinical research and patient care 22. Predictive analysis in healthcare using data science 23. Recommender systems in healthcare-an emerging technology 24. Robotics: challenges and opportunities in healthcare 25. A new era of the healthcare industry using Internet of Medical Things 26. Single cell genomics unleashed: exploring the landscape of endometriosis with machine learning, gene expression profiling, and therapeutic target discovery 27. Analyzing the success of the thriving machine prediction model for Parkinson’s disease prognosis: a comprehensive review
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