A survey on COVID-19 impact in the healthcare domain: worldwide market implementation, applications, security and privacy issues, challenges and future prospects

Complex & Intelligent Systems, Journal Year: 2022, Volume and Issue: 9(1), P. 1027 - 1058

Published: May 31, 2022

Extensive research has been conducted on healthcare technology and service advancements during the last decade. The Internet of Medical Things (IoMT) demonstrated ability to connect various medical apparatus, sensors, specialists ensure best treatment in a distant location. Patient safety improved, prices have decreased dramatically, services become more approachable, operational efficiency industry increased. This paper offers recent review current future applications, security, market trends, IoMT-based implementation. analyses advancement IoMT implementation addressing concerns from perspectives enabling technologies, services. potential obstacles issues system are also discussed. Finally, survey includes comprehensive overview different disciplines empower researchers who eager work make advances field obtain better understanding domain.

Language: Английский

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TSA-CNN-AOA: Twitter sentiment analysis using CNN optimized via arithmetic optimization algorithm

Neural Computing and Applications, Journal Year: 2023, Volume and Issue: 35(14), P. 10311 - 10328

Published: Jan. 20, 2023

Language: Английский

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A comprehensive survey on impact of applying various technologies on the internet of medical things

Artificial Intelligence Review, Journal Year: 2025, Volume and Issue: 58(3)

Published: Jan. 8, 2025

Abstract This paper explores the transformative impact of Internet Medical Things (IoMT) on healthcare. By integrating medical equipment and sensors with internet, IoMT enables real-time monitoring patient health, remote care, individualized treatment plans. significantly improves several healthcare domains, including managing chronic diseases, safety, drug adherence, resulting in better outcomes reduced expenses. Technologies like blockchain, Artificial Intelligence (AI), cloud computing further boost IoMT’s capabilities Blockchain enhances data security interoperability, AI analyzes massive volumes health to find patterns make predictions, offers scalable cost-effective processing storage. Therefore, this provides a comprehensive review (IoT) IoMT-based edge-intelligent smart healthcare, focusing publications published between 2018 2024. The addresses numerous studies IoT, IoMT, AI, edge computing, security, Deep Learning, blockchain. obstacles facing are also covered paper, interoperability issues, regulatory compliance, privacy concerns. Finally, recommendations for provided.

Language: Английский

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The Deep Learning ResNet101 and Ensemble XGBoost Algorithm with Hyperparameters Optimization Accurately Predict the Lung Cancer

Applied Artificial Intelligence, Journal Year: 2023, Volume and Issue: 37(1)

Published: June 3, 2023

Lung cancer is the most common and second leading cause of with lowest survival rate due to lack efficient diagnostic tools. Currently, researchers are devising artificial intelligence based tools improve capabilities. The machine learning (ML) requires hand-crafted features train algorithms. To extract relevant still a challenging task in field image processing. We first extracted texture gray level co-occurrence matrix features. fed these traditional ML algorithms such as k-nearest neighbor (KNN) support vector (SVM). SVM yielded an accuracy 83.0%, whereas KNN produced 97.0%. then optimized employed ensemble extreme boosting (XGBoost) algorithm, which improved detection performance precision, recall, 100%. also deep ResNet101 distinguish small cell from non-small lung obtained 100% evaluation measures. results revealed that proposed approach more robust than Based on results, methodology can be very helpful early treatment for better diagnosis system.

Language: Английский

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Differentiating Chat Generative Pretrained Transformer from Humans: Detecting ChatGPT-Generated Text and Human Text Using Machine Learning

Mathematics, Journal Year: 2023, Volume and Issue: 11(15), P. 3400 - 3400

Published: Aug. 3, 2023

Recently, the identification of human text and ChatGPT-generated has become a hot research topic. The current study presents Tunicate Swarm Algorithm with Long Short-Term Memory Recurrent Neural Network (TSA-LSTMRNN) model to detect both as well text. purpose proposed TSA-LSTMRNN method is investigate model’s decision presence any particular pattern. In addition this, technique focuses on designing Term Frequency–Inverse Document Frequency (TF-IDF), word embedding, count vectorizers for feature extraction process. For detection classification processes, LSTMRNN used. Finally, TSA employed selecting parameters approach, which enables improved performance. simulation performance was investigated benchmark databases, outcome demonstrated advantage system over other recent methods maximum accuracy 93.17% 93.83% human- datasets, respectively.

Language: Английский

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Sentiment Analysis in the Age of COVID-19: A Bibliometric Perspective

Information, Journal Year: 2023, Volume and Issue: 14(12), P. 659 - 659

Published: Dec. 13, 2023

The global impact of the COVID-19 pandemic has been profound, placing significant challenges upon healthcare systems and world economy. pervasive presence illness, uncertainty, fear markedly diminished overall life satisfaction. Consequently, sentiment analysis gained substantial traction among scholars seeking to unravel emotional attitudinal dimensions this crisis. This research endeavors provide a bibliometric perspective, shedding light on principal contributors emerging field. It seeks spotlight academic institutions associated with domain, along identifying most influential publications in terms both paper volume h-index metrics. To end, we have meticulously curated dataset comprising 646 papers sourced from ISI Web Science database, all centering theme during pandemic. Our findings underscore burgeoning interest exhibited by community particular evident an astonishing annual growth rate 153.49%. Furthermore, our elucidates key keywords collaborative networks within authorship, offering valuable insights into proliferation thematic pursuit. In addition this, encompasses n-gram investigation across keywords, abstracts, titles, keyword plus, complemented examination frequently cited works. results gleaned these offer crucial perspectives, contribute identification pertinent issues, guidance for informed decision-making.

Language: Английский

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Machine learning based model for detecting depression during Covid-19 crisis

Scientific African, Journal Year: 2023, Volume and Issue: 20, P. e01716 - e01716

Published: May 15, 2023

Covid-19 has impacted negatively on people all over the world. Some of ways that it affected include such as Health, Employment, Mental Education, Social isolation, Economic Inequality and Access to healthcare essential services. Apart from physical symptoms, caused considerable damage mental health individuals. Among all, depression is identified one common illnesses which leads early death. People suffering are at a higher risk developing other conditions, heart disease stroke, also suicide. The importance detection intervention cannot be overstated. Identifying treating can prevent illness becoming more severe development conditions. Early suicide, leading cause death among with depression. Millions have this disease. To proceed study individuals we conducted survey 21 questions based Hamilton tool advise psychiatrist. With use Python's scientific programming principles machine learning methods like Decision Tree, KNN, Naive Bayes, results were analysed. Further comparison these techniques done. Study concludes KNN given better than accuracy decision tree in terms latency detect person. At conclusion, learning-based model suggested replace conventional method detecting sadness by asking encouraging getting regular feedback them.

Language: Английский

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Investigating Influential COVID-19 Perspectives: A Multifaceted Analysis of Twitter Discourse

Lecture notes in computer science, Journal Year: 2025, Volume and Issue: unknown, P. 3 - 22

Published: Jan. 1, 2025

Language: Английский

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BERT-Based Deep Learning Models for Analyzing Sentiments of COVID-19-Related Social Media Tweets

Advances in computational intelligence and robotics book series, Journal Year: 2025, Volume and Issue: unknown, P. 21 - 36

Published: Feb. 28, 2025

Social media data has become an important tool for understanding public attitudes. All over the world, COVID-19 pandemic impacted people's lives in various ways. People worldwide utilize social to express their thoughts and feelings about pandemic. Because of diversity Twitter posts, researchers analyze sentiment examine public's numerous sentiments concerning COVID-19. In meantime, people have shared immunization protection efficacy on sites such as Twitter. Studies demonstrated that it may strengthen ideas impact general opinion. This study focuses analyzing connected using bidirectional encoder representations from transformers (BERT) with random forest (RF), convolutional neural networks (CNN), recurrent CNN (RCNN) classifiers.

Language: Английский

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Social Media Text Sentiment Analysis: Exploration Of Machine Learning Methods

Published: Jan. 8, 2024

With the increasing number of social media and online platforms, sentiment analysis has become an important research object in new fields. This study aims to explore improve text methods ability extract understand information data. A public data set called "Sentiment book review on Amazon Kindle" is used, which contains product analyses Kindle store category, with a total 982,619 records. Through effective preprocessing, including cleaning, tokenization, removal stop words lemmatization, we are ready for subsequent development models. uses natural language processing technology classify reviews into positive negative categories, RNN logistic regression machine learning algorithms comparison. Finally, basic web application prototype based FLASK, HTML, CSS Python was designed, integrating AI models provide results visualization real time.

Language: Английский

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