Secure and Smart Healthcare System using IoT and Deep Learning Models

Rana, Ajay; Reddy, A. Rajashekar; Shrivastava, Anurag; Verma, Devvret; Ansari, Md. Sakil; Singh, Devender

doi:10.1109/ictacs56270.2022.9988676

Cited by 14 publications

(7 citation statements)

References 40 publications

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“…The use of artificial intelligence (AI) in education has enabled personalized learning, revolutionizing the way students learn (Rana et al, 2022). Personalized learning is a teaching method that tailors learning experiences to each student's individual needs, strengths, weaknesses, and interests .…”

Section: Personalized Learningmentioning

confidence: 99%

Role of AI in Education

Harry

2023

Injurity

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Artificial intelligence (AI) has the potential to revolutionize the way we learn and teach, making it more personalized, engaging, and efficient. AI in education refers to the use of artificial intelligence technologies, such as machine learning and natural language processing, to enhance the learning experience. It involves the use of algorithms that analyze data, identify patterns, and make predictions, enabling educators to personalize learning for each student. The potential benefits of using AI in education are significant. Personalized learning, one of the most significant advantages of AI in education, can lead to better student outcomes, as students can learn at their own pace and in a way that suits their learning style. Intelligent tutoring systems, chatbots, and automated grading and assessment can increase efficiency, save teachers' time, and provide more accurate and consistent feedback. However, there are also challenges associated with using AI in education. Privacy and security concerns, lack of trust, cost, and potential bias are some of the challenges that need to be addressed. Ethical considerations such as ensuring accessibility, transparency, and fairness in AI-based education systems also need to be taken into account. Despite these challenges, the potential of AI in education is immense. AI can provide better data analysis, enabling educators to make data-driven decisions. In this review we described role of AI in management, promotion of education which describe the effect of AI in education sector

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Section: Personalized Learningmentioning

confidence: 99%

Role of AI in Education

Harry

2023

Injurity

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“…AI is also being used to accelerate drug discovery by analyzing large datasets and identifying potential drug candidates that may have been overlooked by traditional methods (Rana et al, 2022)(M. Galety et al, 2021). For example, in 2020, researchers at the University of California, San Francisco (UCSF) used AI to discover a new drug candidate for treating Alzheimer's disease (Samudrala et al, 2022).…”

Section: Drug Discoverymentioning

confidence: 99%

Artificial Intelligence in Health Sector of USA

Pendy¹

2023

JISS

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The article describes how AI has already made a significant impact in the health sector in the US, with many promising future applications. In medical imaging, for example, AI algorithms have been developed that can detect and classify anomalies with high accuracy rates, potentially reducing the need for unnecessary biopsies or surgeries. Personalized medicine is another area where AI is being used to analyze large amounts of patient data and provide tailored treatments. AI is also being used to improve the accuracy and efficiency of electronic health records (EHRs) by automatically detecting errors and inconsistencies. In drug discovery, AI algorithms can analyze large data sets and predict which compounds are likely to be effective in treating a particular disease, potentially reducing the time and cost of drug development. In the future, AI is expected to play an even greater role in precision medicine, enabling clinicians to develop customized treatment plans based on a patient's individual genetic and medical history. AI is also being developed for use in virtual assistants, which can provide patients with personalized health advice and reminders. Clinical decision support systems are another area where AI is expected to have a significant impact, helping clinicians to make more informed decisions by analyzing patient data and providing recommendations based on the latest research and best practices. Overall, the article suggests that AI has the potential to transform healthcare by improving patient outcomes, reducing costs, and increasing access to care. However, the article also acknowledges that there are challenges to be addressed, such as ensuring the accuracy and fairness of AI algorithms and addressing privacy concerns.

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“…The medical data about the patient is gathered using IoT-aided 45 implemented AD-LSTM-AN model for verification of the user. If the person is authorized, then the AD-LSTM-AN gives output as an authorized user who can further access the blockchain network for storing and retrieving the medical data.…”

Section: First Level Of Authenticated User Verificationmentioning

confidence: 99%

“…indicates the arbitrary hyperplane. The vector for the cruise is given as provided in Equation (45).…”

Section: Cruisementioning

confidence: 99%

See 1 more Smart Citation

HECC‐ABE: A novel blockchain‐based IoT healthcare data storage using hybrid cryptography schemes with key optimization by hybrid meta‐heuristic algorithm

Dubey,

Ramanjaneyulu,

Saraswat

et al. 2023

Trans Emerging Tel Tech

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The most contemporary development in information technology is the Internet of Things (IoT), which integrates the digital world with the real world. It makes it possible for things and people to communicate via the Internet. Blockchain is one of the popular topics of interest right now, and it can be used in most IoT applications. The blockchain's salient characteristics, like decentralization, data integrity, confidentiality, protection, and openness, are the main reasons for implementing it in healthcare services. Hence, this paper introduces an effective approach for storing IoT‐based healthcare data storage in the blockchain. The procedures in this suggested paradigm are as follows: user authentication, user trust verification, and optimal key storage in the blockchain. Wearable sensors are inserted in or adhered to a patient's body and used by IoT networks to gather healthcare data. These details are supplied into the verification structure constructed by adaptive dilated long short term memory with attention network (AD‐LSTM‐AN). Once the user's authentication is confirmed, then the user's trust level is computed. The same AD‐LSTM‐AN‐based verification structure is used to verify the historical data that has been stored and retrieved by the user, together with their previous transactions, in this phase. The healthcare data are then sent to the hybrid elliptic curve cryptography with attribute‐based encryption (HECC‐ABE) cryptography schemes for data encryption once the authentication of the person who attempts to store the data is confirmed. An adaptive final position‐based golden eagle‐Harris hawks optimization (AFP‐GEHHO) algorithm is used for optimizing the keys of the encrypted data. The blockchain platform stores the encrypted data of the authorized user with a high level of trust. The same process is done in reverse order whenever a user needs to recover information that is saved in the blockchain to retrieve the initially stored healthcare data. The effectiveness of secure data storage in blockchain is tested through experimental simulations. Throughout the analysis, the designed model achieves 96% in terms of accuracy. Thus, the developed model shows more secure and effective, has less error and reduces the time and memory requirements compared to existing approaches.

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Secure and Smart Healthcare System using IoT and Deep Learning Models

Cited by 14 publications

References 40 publications

Role of AI in Education

Role of AI in Education

Artificial Intelligence in Health Sector of USA

HECC‐ABE: A novel blockchain‐based IoT healthcare data storage using hybrid cryptography schemes with key optimization by hybrid meta‐heuristic algorithm

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