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4th International Conference on Artificial Intelligence and Applied Mathematics in Engineering : ICAIAME 2022 / / edited by D. Jude Hemanth, Tuncay Yigit, Utku Kose, Ugur Guvenc
| 4th International Conference on Artificial Intelligence and Applied Mathematics in Engineering : ICAIAME 2022 / / edited by D. Jude Hemanth, Tuncay Yigit, Utku Kose, Ugur Guvenc |
| Autore | Hemanth D. Jude |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (779 pages) |
| Disciplina | 006.3 |
| Altri autori (Persone) |
YigitTuncay
KoseUtku GuvencUgur |
| Collana | Engineering Cyber-Physical Systems and Critical Infrastructures |
| Soggetto topico |
Computational intelligence
Artificial intelligence Engineering - Data processing Computational Intelligence Artificial Intelligence Data Engineering |
| ISBN |
9783031319563
3031319567 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Sentiment Analysis in Turkish using Transformer-based Deep Learning Models -- Mathematical Modeling of an Antenna Device Based on a T-shaped Waveguide of the Microwave Range -- Higher-order and stable numerical scheme for nonlinear diffusion system via compact finite difference and adaptive step-size Runge-Kutta methods -- Explainable Artificial Intelligence (XAI) for Deep Learning Based Intrusion Detection Systems -- A Color Channel Based Analysis on Image Tessellation -- Modeling of Shear Strength of Basalt Fiber Reinforced Clay (BFRC) Soil Using Artificial Neural Network (ANN) -- Change of the Internet with Blockchain and Metaverse Technologies -- A Language-Free Hate Speech Identification on Code-Mixed Conversational Tweets -- Decision Trees in Causal Inference -- The Resilience of Unmanned Aerial Vehicles to Cyberattacks and Assessment of Potential Threats. |
| Record Nr. | UNINA-9910728392403321 |
Hemanth D. Jude
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| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Artificial Intelligence and Applied Mathematics in Engineering Problems : Proceedings of the International Conference on Artificial Intelligence and Applied Mathematics in Engineering (ICAIAME 2019) / / edited by D. Jude Hemanth, Utku Kose
| Artificial Intelligence and Applied Mathematics in Engineering Problems : Proceedings of the International Conference on Artificial Intelligence and Applied Mathematics in Engineering (ICAIAME 2019) / / edited by D. Jude Hemanth, Utku Kose |
| Edizione | [1st ed. 2020.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 |
| Descrizione fisica | 1 online resource (1,105 pages) |
| Disciplina |
620.00151
620.0028563 |
| Collana | Lecture Notes on Data Engineering and Communications Technologies |
| Soggetto topico |
Computational intelligence
Artificial intelligence Computational Intelligence Artificial Intelligence |
| ISBN | 3-030-36178-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | State and Trends of Machine Learning Approaches in Business: An Empirical Review -- Piecewise Demodulation based on Combined Artificial Neural Network for Quadrate Frequency Shift Keying Communication Signals -- A New Variable Ordering Method for the K2 Algorithm -- A Benefit Optimization Approach to the Evaluation of Classification Algorithms -- Financial Fraud Detection through Artificial Intelligence -- Deep Learning-based Software Energy Consumption Profiling -- Prediction of Potential Bank Customers: Application on Data Mining -- The Model Selection Methods for Sparse Biological Networks -- A Hybrid Approach for the Sentiment Analysis of Turkish Twitter Data -- Text Mining and Statistical Learning for the Analysis of the Voice of the Customer -- Effect the Number of Reservations on Implementation of Operating Room Scheduling with Genetic Algorithm -- Statistical Learning Applied to Malware Detection -- Improved Social Spider Algorithm via Differential Evolution -- On the Prediction of Possibly Forgotten Shopping Basket items -- Selection and Training of School Administrators in Different Countries -- A Walking and Balance Analysis Based on Pedobarography -- On the Notion of Structure Species in the Bourbaki's Sense. |
| Record Nr. | UNINA-9910483954903321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Artificial Intelligence and Digital Twin Technology : 1st International Conference, IconAIDTT 2023, Sivakasi, India, April 26-28, 2023, Proceedings
| Artificial Intelligence and Digital Twin Technology : 1st International Conference, IconAIDTT 2023, Sivakasi, India, April 26-28, 2023, Proceedings |
| Autore | K Valarmathi |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Cham : , : Springer, , 2025 |
| Descrizione fisica | 1 online resource (173 pages) |
| Altri autori (Persone) |
ARamathilagam
SeeniSankarganesh KoseUtku HungBui Thanh KottursamyKottilingam |
| Collana | Communications in Computer and Information Science Series |
| ISBN |
9783031777998
3031777999 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910918590803321 |
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K Valarmathi
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| Cham : , : Springer, , 2025 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Deep learning for cancer diagnosis / / Utku Kose; Jafar Alzubi
| Deep learning for cancer diagnosis / / Utku Kose; Jafar Alzubi |
| Edizione | [1st ed. 2021.] |
| Pubbl/distr/stampa | Singapore : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (XIX, 300 p. 118 illus., 87 illus. in color.) |
| Disciplina | 006.31 |
| Collana | Studies in Computational Intelligence |
| Soggetto topico |
Cancer - Diagnosis - Data processing
Machine learning |
| ISBN | 981-15-6321-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Deep Learning for Enhancing Cancer Diagnosis -- Improved Deep Learning Techniques for Better Cancer Diagnosis -- Deep Learning for Diagnosing Rare Cancer Types -- Deep Learning for Histopathological Diagnosis -- Effective Use of Deep Learning and Image Processing for Cancer Diagnosis. |
| Record Nr. | UNINA-9910483238803321 |
| Singapore : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Deep Sciences for Computing and Communications [[electronic resource] ] : First International Conference, IconDeepCom 2022, Chennai, India, March 17–18, 2022, Revised Selected Papers / / edited by Kottilingam Kottursamy, Ali Kashif Bashir, Utku Kose, Annie Uthra
| Deep Sciences for Computing and Communications [[electronic resource] ] : First International Conference, IconDeepCom 2022, Chennai, India, March 17–18, 2022, Revised Selected Papers / / edited by Kottilingam Kottursamy, Ali Kashif Bashir, Utku Kose, Annie Uthra |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (XIII, 368 p. 223 illus., 161 illus. in color.) |
| Disciplina | 006.3 |
| Collana | Communications in Computer and Information Science |
| Soggetto topico |
Artificial intelligence
Education—Data processing Social sciences—Data processing Image processing—Digital techniques Computer vision Computer networks Artificial Intelligence Computers and Education Computer Application in Social and Behavioral Sciences Computer Imaging, Vision, Pattern Recognition and Graphics Computer Communication Networks |
| ISBN | 3-031-27622-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Classification and Regression Problems for Communication Paradigms -- Deep Learning and Vision Computing -- Deep- Recurrent Neural network (RNN) for Industrial informatics -- Extended AI for heterogeneous Edge. |
| Record Nr. | UNISA-996547971703316 |
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Deep Sciences for Computing and Communications : First International Conference, IconDeepCom 2022, Chennai, India, March 17–18, 2022, Revised Selected Papers / / edited by Kottilingam Kottursamy, Ali Kashif Bashir, Utku Kose, Annie Uthra
| Deep Sciences for Computing and Communications : First International Conference, IconDeepCom 2022, Chennai, India, March 17–18, 2022, Revised Selected Papers / / edited by Kottilingam Kottursamy, Ali Kashif Bashir, Utku Kose, Annie Uthra |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (XIII, 368 p. 223 illus., 161 illus. in color.) |
| Disciplina | 006.3 |
| Collana | Communications in Computer and Information Science |
| Soggetto topico |
Artificial intelligence
Education - Data processing Social sciences - Data processing Image processing - Digital techniques Computer vision Computer networks Artificial Intelligence Computers and Education Computer Application in Social and Behavioral Sciences Computer Imaging, Vision, Pattern Recognition and Graphics Computer Communication Networks Aprenentatge automàtic Sistemes de telecomunicació |
| Soggetto genere / forma |
Congressos
Llibres electrònics |
| ISBN |
9783031276224
3031276221 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Classification and Regression Problems for Communication Paradigms -- Deep Learning and Vision Computing -- Deep- Recurrent Neural network (RNN) for Industrial informatics -- Extended AI for heterogeneous Edge. |
| Record Nr. | UNINA-9910682560403321 |
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Futuristic Computational Systems and Advanced Engineering for the Society : Proceedings of the 6th International Conference on Artificial Intelligence and Applied Mathematics in Engineering ICAIAME 2024, Volume 2 / / edited by Jude Hemanth, Utku Kose, Nabi Ibadov, Ismail Serkan Uncu, Hamit Armagan
| Futuristic Computational Systems and Advanced Engineering for the Society : Proceedings of the 6th International Conference on Artificial Intelligence and Applied Mathematics in Engineering ICAIAME 2024, Volume 2 / / edited by Jude Hemanth, Utku Kose, Nabi Ibadov, Ismail Serkan Uncu, Hamit Armagan |
| Edizione | [1st ed. 2025.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 |
| Descrizione fisica | 1 online resource (XXII, 207 p. 60 illus., 45 illus. in color.) |
| Disciplina | 006.3 |
| Collana | Engineering Cyber-Physical Systems and Critical Infrastructures |
| Soggetto topico |
Computational intelligence
Artificial intelligence Engineering - Data processing Computational Intelligence Artificial Intelligence Data Engineering |
| ISBN | 3-031-94600-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Optimization of Language Models for Product Feed Enrichment: LM-PFE -- Deep Learning Algorithms for Automatic Text Summarization in Academic Studies -- Multichannel Convolutional Networks for Classification and Localization of Construction and Demolition Waste -- Optimizing Hybrid CNN-RNN-Transformer Models for Multiclass Classification Tasks -- Artificial Neural Networks for Predicting Asphalt Fatigue Life: Investigating Material and Loading Parameters with a Comprehensive Dataset and Addressing Model Intricacies -- Cyber Security and Artificial Intelligence in Military Aviation: Threats and Advancements -- Keyword Extractıon from Turkish Text Using Natural Language Processing Techniques -- Semi-Structured Data Streaming and Anomaly Detection in a Big Data Environment with Spark -- Integration Deep Learning Models into Personalized Search -- Examining the audience comments of the BBC Learning English channel videos with LDA Topic Analysis -- Albanian Crossword Generation with Artificial Intelligence -- A Deep Learning-Based Reinforcement Algorithm for the Diagnosis of Glioma -- Cryptography with Artificial Intelligence: An Overview -- IoT Sensors Based Association Analysis Between the Number of Detections and the Progress of Construction Works -- A Question Answering System Using Deep Learning Techniques in The Education Domain. |
| Record Nr. | UNINA-9911021146403321 |
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Futuristic Computational Systems and Advanced Engineering for the Society : Proceedings of the 6th International Conference on Artificial Intelligence and Applied Mathematics in Engineering ICAIAME 2024, Volume 1 / / edited by D. Jude Hemanth, Utku Kose, Nabi Ibadov, Ismail Serkan Uncu, Hamit Armagan
| Futuristic Computational Systems and Advanced Engineering for the Society : Proceedings of the 6th International Conference on Artificial Intelligence and Applied Mathematics in Engineering ICAIAME 2024, Volume 1 / / edited by D. Jude Hemanth, Utku Kose, Nabi Ibadov, Ismail Serkan Uncu, Hamit Armagan |
| Edizione | [1st ed. 2025.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 |
| Descrizione fisica | 1 online resource (XXII, 209 p. 72 illus., 64 illus. in color.) |
| Disciplina | 006.3 |
| Collana | Engineering Cyber-Physical Systems and Critical Infrastructures |
| Soggetto topico |
Computational intelligence
Artificial intelligence Engineering - Data processing Computational Intelligence Artificial Intelligence Data Engineering |
| ISBN | 3-031-92552-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | The Effect of Feature Selection on Stock Market Index Prediction -- Controversy Detection on Twitter with Dynamics and Content-Based Features -- Detection of Alzheimer's Disease with an Ensemble Deep Learning Model Using Diffusion Tensor Imaging -- Reliability Challenges in Crowdsourced Bounding-Box Data for Computer Vision -- Glaucoma Classification Using Transfer Learning Based Convolutional Neural Networks -- A study on enhancing low-resource Turkish-English neural machine translation using part of speech tags -- Detection of Malware and Benign Samples in AWSCTD Dataset with Kolmogorov-Arnold Networks -- Stance Intensity Detection on Social Media -- Stance in Translation: English-to-Turkish Cross-Lingual Stance Detection -- Evaluation of Distance Metrics for the Success of Machine Learning-Based Authentication Systems Using Photoplethysmography (PPG)Signals -- Optimization of Agent-based Queuing System Model: A Case Study through Inventory Systems -- Support Vector Machine and Neural Network Approaches for Stiffness Modulus Prediction of Bituminous Mixtures Under Four-Point Bending Tests -- Application of Machine Learning Method in Predicting the Swelling Pressure of Clayey Soils -- Virtual Consultant: An Automated SAP Advisor -- Comparative Study of Machine Learning Techniques for Remaining Useful Life Estimation in Simulated Mini Factory Environment. |
| Record Nr. | UNINA-9911007363103321 |
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Healthcare Monitoring and Data Analysis Using IoT : Technologies and Applications
| Healthcare Monitoring and Data Analysis Using IoT : Technologies and Applications |
| Autore | Jain Vishal |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Stevenage : , : Institution of Engineering & Technology, , 2022 |
| Descrizione fisica | 1 online resource (427 pages) |
| Disciplina | 616.028 |
| Altri autori (Persone) |
ChatterjeeJyotir Moy
KumarPradeep KoseUtku |
| Collana | Healthcare Technologies |
| Soggetto topico | Patient monitoring - Technological innovations |
| ISBN |
1-83724-472-3
1-5231-4666-4 1-83953-438-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Contents -- About the editors -- Preface -- Acknowledgments -- 1. COVID-19 pandemic analysis using application of AI | Pawan Whig, Rahul Reddy Nadikattu and Arun Velu -- 1.1 Introduction -- 1.2 Literature survey -- 1.3 Dataset used for analysis -- 1.4 Various machine learning libraries -- 1.5 Training and testing -- 1.6 Bias and variance -- 1.7 Result -- 1.8 Conclusion -- References -- 2. M-health: a revolution due to technology in healthcare sector | Mayuri Diwakar Kulkarni, Ashish Suresh Awate and Jyotir Moy Chatterje -- 2.1 Introduction -- 2.2 Discussion -- 2.3 Conclusion and future work -- References -- 3. Analysis of Big Data in electroencephalography (EEG) | Sagar Motdhare, Garima Mathur and Ravi Kant -- 3.1 Introduction -- 3.2 Methodology -- 3.3 EEG signal recording -- 3.4 Activity/action of EEG -- 3.5 EEG applications -- 3.6 Mathematical model -- 3.7 Across the boundaries of small sample sizes -- 3.8 EEG signal analytics and seizure analysis -- 3.9 EEG digital video -- 3.10 EEG data storage and its management -- 3.11 Big Data in epileptic EEG analysis -- 3.12 Conclusion -- 3.13 Future scope -- References -- 4. An analytical study of COVID-19 outbreak | Shipra Gupta, Vijay Kumar, P. Patil and Lajwanti Kishnani -- 4.1 Introduction -- 4.2 Review of literature -- 4.3 Method -- 4.4 Results -- 4.5 Discussions -- 4.6 Precautions -- 4.7 Conclusions and future scope -- Acknowledgment -- References -- 5. IoT-based smart healthcare monitoring system | Hakan Yuksel -- 5.1 Introduction -- 5.2 Related work -- 5.3 Proposed method -- 5.4 Result and discussion -- 5.5 Conclusion and future scope -- References -- 6. Development of a secured IoMT device with prioritized medical information for tracking and monitoring COVID patients in rural areas | P.K. Jawahar, K. Indragandhi, G. Kannan and Yiu-Wing Leung -- 6.1 Introduction.
6.2 Security threats in IoMT -- 6.3 Introduction to COVID-19 -- 6.4 Proposed system architecture -- 6.5 Conclusion and future scope -- References -- 7. An IoT-based system for a volumetric estimation of human brain morphological features from magnetic resonance images | S.N. Kumar, A. Lenin Fred, L.R. Jonisha Miriam, H. Ajay Kumar, I. Christina Jane, Parasuraman Padmanabhan and Balazs Gulyas -- 7.1 Introduction -- 7.2 Materials and methods -- 7.3 Results and discussion -- 7.4 Conclusion and future scope -- Acknowledgments -- References -- 8. Healthcare monitoring through IoT: security challenges and privacy issues | S.O. Owoeye, A.S. Akinade, K.I. Adenuga and F.O. Durodola -- 8.1 Introduction -- 8.2 IoT applications in personalized healthcare -- 8.3 Challenges of IoT in personalized healthcare -- 8.4 Security of IoT in personalized healthcare -- 8.5 Privacy -- 8.6 Conclusion and future scope -- References -- 9. E-health natural language processing | Saman Hina, Raheela Asif and Pardeep Kumar -- 9.1 Unstructured datasets for E-health NLP research -- 9.2 Annotation challenges dealing with health-care corpora -- 9.3 NLP methods that can be adopted to tackle semantics for medical text analysis -- 9.4 E-health and Internet of Things (IoT) -- 9.5 Contributions required from NLP researchers in health-care applications -- 9.6 Conclusion and future work -- References -- 10. Blockchain of things for healthcare asset management | Sajid Nazir, Mohammad Kaleem, Hassan Hamdoun, Jafar Alzubi and Hua Tianfield -- 10.1 Introduction -- 10.2 Healthcare asset management -- 10.3 Challenges and opportunities in healthcare -- 10.4 Blockchain: concepts and frameworks -- 10.5 Blockchain of things architecture for healthcare asset management -- 10.6 Major healthcare application areas -- 10.7 Conclusion and future work -- References. 11. Artificial intelligence: practical primer for clinical research in cardiovascular disease | Shivendra Dubey, Chetan Gupta and Kalpana Rai -- 11.1 Artificial intelligence -- 11.2 Traditional statistics versus AI -- 11.3 Representative algorithms of AI -- 11.4 Machine power along with big data -- 11.5 Challenges to implementation -- 11.6 Conclusion and future work -- References -- 12. Deep data analysis for COVID-19 outbreak | S.O. Owoeye, O.J. Odeyemi, F.O. Durodola and K.I. Adenuga -- 12.1 Introduction to deep data analysis -- 12.2 Deep data analysis for COVID-19 -- 12.3 CNN architectures -- 12.4 Building the neural network -- 12.5 Neural network architecture -- 12.6 Other parameters used to configure the neural network -- 12.7 Model summary -- 12.8 Metrics used for evaluation -- 12.9 Results and evaluation -- 12.10 Conclusion and future scope -- References -- 13. Healthcare system using deep learning | J.B. Shajilin Loret and P.C. Sherimon -- 13.1 Introduction -- 13.2 History of healthcare deep learning -- 13.3 Deep learning benefits -- 13.4 Components of deep learning -- 13.5 The role of deep learning in healthcare in the future -- 13.6 Deep learning applications in healthcare -- 13.7 Conclusion and future work -- References -- 14. Intelligent classification of ECG signals using machine learning techniques | Kuldeep Singh Kaswan, Anupam Baliyan, Jagjit Singh Dhatterwal, Vishal Jain and Jyotir Moy Chatterjee -- 14.1 Introduction -- 14.2 Heart-generated ECG signal -- 14.3 Filtering parameters least-mean-square algorithm -- 14.4 Retrieve and classify ECG signals utilizing ML-based techniques -- 14.5 Artificial neural network (ANN)-based ECG signals -- 14.6 Classification of ECG signals based fuzzy logic (FL) -- 14.7 Fourier transform wavelet transforms -- 14.8 Combination of machine learning and statistical algorithms. 14.9 Conclusion and future work -- References -- 15. A survey and taxonomy on mutual interference mitigation techniques in wireless body area networks | Neethu Suman and P.C. Neelakantan -- 15.1 Introduction -- 15.2 Interference issues in WBAN -- 15.3 Mutual interference mitigation schemes -- 15.4 Conclusion and future scope -- References -- 16. Predicting COVID cases using machine learning, android, and firebase cloud storage | Ritesh Kumar Sinha, Sukant Kishoro Bisoy, Saurabh Kumar, Sai Prasad Sarangi and Utku Kose -- 16.1 Introduction -- 16.2 Literature survey -- 16.3 Implementation and methodology -- 16.4 Machine learning models -- 16.5 Introduction to android app -- 16.6 Result analysis -- 16.7 Conclusion and future work -- References -- 17. Technological advancement with artificial intelligence in healthcare | Manas Kumar Yogi, Jyotsna Garikipati and Jyotir Moy Chatterjee -- 17.1 Introduction -- 17.2 Literature review -- 17.3 Disease identification and diagnosis -- 17.4 Drug discovery and manufacturing -- 17.5 Electronic health records -- 17.6 Disease prediction using machine learning -- 17.7 Fairness -- 17.8 Data analytics role in healthcare -- 17.9 Deep learning applications in healthcare -- 17.10 Conclusion and future scope -- References -- 18. Changing dynamics on the Internet of Medical Things: challenges and opportunities | Imtiaz Ali Brohi, Najma Imtiaz Ali and Pardeep Kumar -- 18.1 Introduction -- 18.2 The applications of Internet of Things -- 18.3 Healthcare and Internet of Things -- 18.4 Security in Internet of Medical Things -- 18.5 Privacy in Internet of Medical Things -- 18.6 Perception of trust and risk in IoMT -- 18.7 Conclusion and future scope -- References -- 19. Internet of Drones (IOD) in medical transport application | G. Prasad, J. Kavya and J. Sahana -- 19.1 Introduction to unmanned aerial vehicle. 19.2 Internet of Things in Industry 5.0 -- 19.3 Applications in medical transport -- 19.4 Methodology and approach -- 19.5 Conclusion and future -- Acknowledgment -- References -- 20. Blockchain-based Internet of Things (IoT) for healthcare systems: COVID-19 perspective | Anand Sharma, S.R. Biradar, H.K.D. Sarma and N.P. Rana -- 20.1 Introduction -- 20.2 IoT in healthcare system -- 20.3 COVID-19 outbreak -- 20.4 Blockchain -- 20.5 Blockchain-based IoT for healthcare systems -- 20.6 Advantages of proposed system -- 20.7 Conclusion and future scope -- References -- 21. Artificial intelligence-based diseases detection and diagnosis in healthcare | Said El Kafhali and Iman El Mir -- 21.1 Introduction -- 21.2 Overview of diseases detection and diagnosis techniques -- 21.3 Supervised learning models -- 21.4 Unsupervised learning models -- 21.5 Reinforcement learning models -- 21.6 Summary of some applications for disease diagnosis in healthcare -- 21.7 Some open research problems -- 21.8 Conclusions -- References -- Index. |
| Record Nr. | UNINA-9911006840803321 |
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Jain Vishal
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| Stevenage : , : Institution of Engineering & Technology, , 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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