Titlebook: Smart Healthcare and Machine Learning; Mousmi Ajay Chaurasia,Prasanalakshmi Balaji,Alejan Book 2024 The Editor(s) (if applicable) and The

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Deep Q-Learning-Based Neural Network for Secure Data Transmission in Internet of Things (IoT) Healtd efficiency must be balanced because the network’s sensors are energy-constrained devices. Consequently, this study developed a unique framework, the deep Q-learning-based neural network, for secure data transmission in the IoT healthcare sector with shorter encryption and decryption times to prote

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Reliable and Efficient Healthcare System Using Artificial Intelligence,matically identify issues and threats to patient safety, such as patterns of suboptimal care or outbreaks of hospital-acquired infections, with high accuracy and speed, providing valuable insights. Some present-day research on AI applications for healthcare indicates a future where more cohesive and

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IoT Paradigm for Healthcare System to Secure the Patients Real-Time Data,orage, has the potential to significantly enhance the effectiveness, convenience, and cost-effectiveness of health care, as opposed to solely relying on hospital-based assistance. This study report has examined the use of supplementary information gathering methods for the purpose of obtaining perti

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Application of the Internet of Things in the Healthcare Field,logies. The integration of IoT in health care involves the deployment of interconnected devices, ranging from wearable sensors to smart medical equipment and remote monitoring systems. The paper delves into the ways in which these devices facilitate real-time data collection, enabling continuous mon

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A Predictive Diagnostic Model for Diabetes Using Machine Learning Technique,r (KNN), decision tree (DT), and logistic regression were employed on the PIMA Indian Diabetes Dataset (PIDD) to predict diabetes in patients. The evaluation of the performance of all the classification methods employed was done with various measurement methods such as accuracy, precision, and F1-sc