Artificial Intelligence for Disease Diagnosis and Prognosis in Smart Healthcare
Herausgeber: Kouadri Mostefaoui, Ghita; Tariq, Faisal; Islam, S M Riazul
Artificial Intelligence for Disease Diagnosis and Prognosis in Smart Healthcare
Herausgeber: Kouadri Mostefaoui, Ghita; Tariq, Faisal; Islam, S M Riazul
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Artificial Intelligence (AI) in general and machine learning (ML) and deep learning (DL) in particular and related digital technologies are a couple of fledging paradigms that the next generation healthcare services are sprouting towards.
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Artificial Intelligence (AI) in general and machine learning (ML) and deep learning (DL) in particular and related digital technologies are a couple of fledging paradigms that the next generation healthcare services are sprouting towards.
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Produktdetails
- Produktdetails
- Verlag: Taylor & Francis Ltd
- Seitenzahl: 314
- Erscheinungstermin: 30. März 2023
- Englisch
- Abmessung: 254mm x 178mm x 19mm
- Gewicht: 740g
- ISBN-13: 9781032168302
- ISBN-10: 1032168307
- Artikelnr.: 66269908
- Herstellerkennzeichnung
- Libri GmbH
- Europaallee 1
- 36244 Bad Hersfeld
- 06621 890
- Verlag: Taylor & Francis Ltd
- Seitenzahl: 314
- Erscheinungstermin: 30. März 2023
- Englisch
- Abmessung: 254mm x 178mm x 19mm
- Gewicht: 740g
- ISBN-13: 9781032168302
- ISBN-10: 1032168307
- Artikelnr.: 66269908
- Herstellerkennzeichnung
- Libri GmbH
- Europaallee 1
- 36244 Bad Hersfeld
- 06621 890
Ghita Kouadri Mostefaoui is currently an Associate Professor at the Department of Computer Science, University College London. Her current teaching includes programming, computer architecture, and software engineering. She received her PhD in computer science from both the University of Fribourg, Switzerland and Université Pierre et Marie Curie (Paris 6). Ghita is a Fellow of the Higher Education Academy. S. M. Riazul Islam is currently a Senior Lecturer in Computer Science at the University of Huddersfield, United Kingdom. Before moving to the UK, he was an Assistant Professor at the Department of Computer Science and Engineering, Sejong University, South Korea, from 2017 to 2022. Dr. Islam's prior affiliations were at Inha University as a Postdoctoral Fellow, at Samsung R&D Institute as a Senior Engineer, and at the University of Dhaka as an Assistant Professor in EEE. He received his Ph.D. in Information and Communication Engineering from Inha University, South Korea, in 2012. Dr. Islam's research interests include applied AI, machine learning, data science, and IoT. Faisal Tariq is currently a Senior Lecturer at the James Watt School of Engineering, University of Glasgow, United Kingdom. He received his PhD degree from The Open University, UK. His research interests include applications of Artificial Intelligence (AI) and Machine Learning (ML) in various domains including smart wireless communications, healthcare technology, cyber security and intelligent internet of Things (IIoT). He is a senior member of IEEE and fellow of the Higher Education Academy.
1. Introduction. 2. Machine Learning for Disease Assessment. 3. Precision
Medicine and Future Healthcare. 4. AI-driven Drug Response Prediction for
Personalised Cancer Medicine. 5. Skin Disease Recognition and
Classification Using Machine Learning and Deep Learning in Python. 6.
COVID-19 Diagnosis Based Deep Learning Approaches for COVIDX Dataset: A
Preliminary Survey. 7. Automatic Grading of Invasive Breast Cancer Patients
for the Decision of Therapeutic Plan. 8. Prognostic Role of CALD1 in Brain
Cancer: A Data-driven Review. 9. Artificial Intelligence for Parkinson's
Disease Diagnosis: A Review. 10: Breast Cancer Detection: A Survey. 11.
Review of Artifact Detection Methods for Automated Analysis and Diagnosis
in Digital Pathology. 12. Machine Learning Enabled Detection and Management
of Diabetes Mellitus. 13. IoT and Deep Learning-based Smart Healthcare with
an Integrated Security System to Detect Various Skin Lesions. 14. Real-Time
Facemask Detection Using Deep Convolutional Neural Network-based Transfer
Learning. 15. Security Challenges in Wireless Body Area Networks for Smart
Healthcare. 16. Machine Learning Based Security and Privacy Protection
Approach to Handle the Physiological Data. 17. Conclusion: Future
Challenges in Artificial Intelligence for Smart Healthcare.
Medicine and Future Healthcare. 4. AI-driven Drug Response Prediction for
Personalised Cancer Medicine. 5. Skin Disease Recognition and
Classification Using Machine Learning and Deep Learning in Python. 6.
COVID-19 Diagnosis Based Deep Learning Approaches for COVIDX Dataset: A
Preliminary Survey. 7. Automatic Grading of Invasive Breast Cancer Patients
for the Decision of Therapeutic Plan. 8. Prognostic Role of CALD1 in Brain
Cancer: A Data-driven Review. 9. Artificial Intelligence for Parkinson's
Disease Diagnosis: A Review. 10: Breast Cancer Detection: A Survey. 11.
Review of Artifact Detection Methods for Automated Analysis and Diagnosis
in Digital Pathology. 12. Machine Learning Enabled Detection and Management
of Diabetes Mellitus. 13. IoT and Deep Learning-based Smart Healthcare with
an Integrated Security System to Detect Various Skin Lesions. 14. Real-Time
Facemask Detection Using Deep Convolutional Neural Network-based Transfer
Learning. 15. Security Challenges in Wireless Body Area Networks for Smart
Healthcare. 16. Machine Learning Based Security and Privacy Protection
Approach to Handle the Physiological Data. 17. Conclusion: Future
Challenges in Artificial Intelligence for Smart Healthcare.
1. Introduction. 2. Machine Learning for Disease Assessment. 3. Precision
Medicine and Future Healthcare. 4. AI-driven Drug Response Prediction for
Personalised Cancer Medicine. 5. Skin Disease Recognition and
Classification Using Machine Learning and Deep Learning in Python. 6.
COVID-19 Diagnosis Based Deep Learning Approaches for COVIDX Dataset: A
Preliminary Survey. 7. Automatic Grading of Invasive Breast Cancer Patients
for the Decision of Therapeutic Plan. 8. Prognostic Role of CALD1 in Brain
Cancer: A Data-driven Review. 9. Artificial Intelligence for Parkinson's
Disease Diagnosis: A Review. 10: Breast Cancer Detection: A Survey. 11.
Review of Artifact Detection Methods for Automated Analysis and Diagnosis
in Digital Pathology. 12. Machine Learning Enabled Detection and Management
of Diabetes Mellitus. 13. IoT and Deep Learning-based Smart Healthcare with
an Integrated Security System to Detect Various Skin Lesions. 14. Real-Time
Facemask Detection Using Deep Convolutional Neural Network-based Transfer
Learning. 15. Security Challenges in Wireless Body Area Networks for Smart
Healthcare. 16. Machine Learning Based Security and Privacy Protection
Approach to Handle the Physiological Data. 17. Conclusion: Future
Challenges in Artificial Intelligence for Smart Healthcare.
Medicine and Future Healthcare. 4. AI-driven Drug Response Prediction for
Personalised Cancer Medicine. 5. Skin Disease Recognition and
Classification Using Machine Learning and Deep Learning in Python. 6.
COVID-19 Diagnosis Based Deep Learning Approaches for COVIDX Dataset: A
Preliminary Survey. 7. Automatic Grading of Invasive Breast Cancer Patients
for the Decision of Therapeutic Plan. 8. Prognostic Role of CALD1 in Brain
Cancer: A Data-driven Review. 9. Artificial Intelligence for Parkinson's
Disease Diagnosis: A Review. 10: Breast Cancer Detection: A Survey. 11.
Review of Artifact Detection Methods for Automated Analysis and Diagnosis
in Digital Pathology. 12. Machine Learning Enabled Detection and Management
of Diabetes Mellitus. 13. IoT and Deep Learning-based Smart Healthcare with
an Integrated Security System to Detect Various Skin Lesions. 14. Real-Time
Facemask Detection Using Deep Convolutional Neural Network-based Transfer
Learning. 15. Security Challenges in Wireless Body Area Networks for Smart
Healthcare. 16. Machine Learning Based Security and Privacy Protection
Approach to Handle the Physiological Data. 17. Conclusion: Future
Challenges in Artificial Intelligence for Smart Healthcare.