COVID-19
The TripAdvisor online airline review dataset, spanning from 2016 to 2023, provides a comprehensive collection of passenger feedback on airline services during the COVID-19 pandemic. This dataset includes user-generated reviews that capture sentiments, preferences, and concerns, allowing for an in-depth analysis of shifting customer priorities in response to pandemic-related disruptions. By examining these reviews, the dataset facilitates the study of evolving passenger expectations, changes in service perceptions, and the airline industry's adaptive strategies.
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100 Views
This dataset includes long-term symptom prevalence data for 27 physical and mental health symptoms associated with Long COVID, extracted from 136 studies spanning up to three years. Key symptoms include fatigue, joint pain, myalgia, respiratory issues (dyspnea, cough), sensory impairments (anosmia, ageusia), neurological symptoms (brain fog), and mental health challenges (anxiety, depression, insomnia).
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144 Views
Please cite the following paper when using this dataset:
Vanessa Su and Nirmalya Thakur, “COVID-19 on YouTube: A Data-Driven Analysis of Sentiment, Toxicity, and Content Recommendations”, Proceedings of the IEEE 15th Annual Computing and Communication Workshop and Conference 2025, Las Vegas, USA, Jan 06-08, 2025 (Paper accepted for publication, Preprint: https://arxiv.org/abs/2412.17180).
Abstract:
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120 Views
To download this dataset without purchasing an IEEE Dataport subscription, please visit: https://zenodo.org/records/13896353
Please cite the following paper when using this dataset:
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886 Views
To download the dataset without purchasing an IEEE Dataport subscription, please visit: https://zenodo.org/records/13738598
Please cite the following paper when using this dataset:
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1143 Views
Persistent viruses like influenza, HIV, Coronavirus exemplify the challenge of viral escape, significantly hindering the development of long-lasting vaccines and effective treatments. This study leverages a Long Short-Term Memory (LSTM) based deep learning architecture to analyze an extensive dataset of over 3.1 million unique viral spike protein sequences, with SARS-CoV-2 serving as the primary example. Our model, Escape Elite Network(EEN) outperforms existing methods in detecting escape mutations across diverse datasets.
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155 Views
This dataset named "Chest X-ray images for Multiple diseases" is a medium sized dataset we collected and produced in 2024 from various sources to predict various Chest-X-ray diseases using Deep learning techniques, primarily from Radiopaedia.org, coronacases.org, Kaggle contains 1000 images for each of the disease namely TB,pneumonia,Covid-19,Normal. This dataset is designed to support the evaluation and development of algorithms to predict various chest x-ray diseases.
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1302 Views
To access this dataset without purchasing an IEEE Dataport subscription, please visit: https://zenodo.org/doi/10.5281/zenodo.11711229
Please cite the following paper when using this dataset:
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936 Views
This research utilized data from the Oxford University Our World in Data Covid 19 Dataset. This dataset contains data points collected on an ongoing basis from Johns Hopkins University, Center for Systems Science and Engineering COVID-19 data, European Centre for Disease Control, and OXFORD COVID-19 Government Response Tracker, from January 2020 to the present.
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306 Views
This dataset contains measured data from five sensor modules designed for monitoring the oxygen concentration in the air in a hospital environment, especially in rooms where oxygen therapy can potentially occurs. This data is crucial from a safety point of view, as a higher oxygen concentration can increase the risk of fire development.
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570 Views