Authentication Framework for Healthcare Devices Through Internet of Things and Machine Learning

Kute, Shruti; Madhav, A. V. Shreyas; Tyagi, Amit Kumar; Deshmukh, Atharva

doi:10.1007/978-981-16-9605-3_27

Evolutionary Computing and Mobile Sustainable Networks

2022

DOI: 10.1007/978-981-16-9605-3_27

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Authentication Framework for Healthcare Devices Through Internet of Things and Machine Learning

Shruti Kute

A. V. Shreyas Madhav

Amit Kumar Tyagi

et al.

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Digital Health Communication With Artificial Intelligence-Based Cyber Security

Tyagi,

Hemamalini,

Soni

2023

Advances in Medical Technologies and Clinical Practice

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Digital health communication (DHC) has become an increasingly popular domain of the healthcare industry, enabling effective and efficient communication between healthcare providers, patients, and other stakeholders. However, the growing importance of digital platforms and the exchange of sensitive health information also present cybersecurity challenges. This chapter explains the utilization of AI-based cybersecurity in DHC to enhance security and protect patient privacy. Artificial intelligence (AI) plays an important role in cybersecurity by enabling advanced threat detection, rapid response, and intelligent risk management. AI algorithms can analyze large amounts of data, identify patterns, and detect potential security breaches or malicious activities in real-time. By adding AI-based cybersecurity solutions, DHC platforms can enhance their security measures and protect sensitive patient data. In DHC, AI-based cybersecurity can be utilized to ensure secure data transmission and storage.

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Digital Health Communication With Artificial Intelligence-Based Cyber Security

Tyagi,

Hemamalini,

Soni

2023

Advances in Medical Technologies and Clinical Practice

View full text Add to dashboard Cite

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Emerging Technologies in Drug Discovery for Providing Efficient Services to Patients

Hemamalini,

Jeyaselvi,

Savitha

et al. 2024

Converging Pharmacy Science and Engineering in Computational Drug Discovery

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This chapter examines the current landscape and future prospects of emerging technologies in drug discovery, focusing on their potential to provide efficient and innovative services to patients. The integration of technologies such as artificial intelligence (AI), machine learning, high-throughput screening, and advanced analytics is reshaping the drug discovery process, promising accelerated development timelines and improved therapeutic outcomes. AI and machine learning algorithms play a pivotal role in data analysis, aiding in the identification of potential drug candidates, target validation, and predictive modeling. High-throughput screening technologies enable the rapid testing of large compound libraries, expediting the identification of lead compounds and optimizing drug development pipelines. Additionally, advanced analytics facilitate the interpretation of complex biological data, enhancing our understanding of disease mechanisms and drug interactions. The convergence of these technologies holds immense promise for personalized medicine.

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Authentication Framework for Healthcare Devices Through Internet of Things and Machine Learning

Cited by 2 publications

References 20 publications

Digital Health Communication With Artificial Intelligence-Based Cyber Security

Digital Health Communication With Artificial Intelligence-Based Cyber Security

Emerging Technologies in Drug Discovery for Providing Efficient Services to Patients

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