The second part (COVID-CTset.zip) contains the whole dataset for each patient. Each patient has three folders (SR_2, SR_3, SR_4), which each folder show one sequence of the lung HRCT scan images of that patient (One time the patient's lung opens and closes). Each of these folders...
We built a large lung CT scan dataset for COVID-19 by curating data from 7 public datasets listed in the acknowledgements. These datasets have been publicly used in COVID-19 diagnosis literature and proven their efficiency in deep learning applications. Therefore, the merged dataset is expected ...
COVID-19 is a severe global problem, and AI can play a significant role in preventing losses by monitoring and detecting infected persons in early-stage. This paper aims to propose a high-speed and accurate fully-automated method to detect COVID-19 from the patient's CT scan images. We ...
COVIDx CT-3: A Large-scale, Multinational,Open-Source Benchmark Dataset for Computer-aidedCOVID-19 Screening from Chest CT ImagesHayden Gunraj 1,2 , Tia Tuinstra 1,2 , Alexander Wong 1,2,3,41 Vision and Image Processing Lab, University of Waterloo2 Department of Systems Design Engineering...
The early and highly accurate prediction of COVID-19 based on medical images can speed up the diagnostic process and thereby mitigate disease spread; therefore, developing AI-based models is an inevitable endeavor. The presented work, to our knowledge, i
Fast temporal query on large EHR-derived data sources presents an emerging big data challenge, as this query modality is intractable using conventional strategies that have not focused on addressing Covid-19-related research needs at scale. We introduce a novel approach called Event-level Inverted ...
Project Page|Paper|GitHub|Dataset|Leaderboard We are very proud to launch Video-MME, the first-ever comprehensive evaluation benchmark of MLLMs in Video Analysis! 🌟 It includes short- (< 2min), medium- (4min~15min), and long-term (30min~60min) videos, ranging from11 seconds to 1 ho...
f, PANDA can detect early-stage PDACs and metastatic cancer that was initially misdetected by the radiologists on chest non-contrast CT (COVID-19 prevention CT). Full size image Without tuning on any chest CT scans, PANDA achieved an AUC of 0.979 (95% CI 0.962–0.993), a sensitivity of...
This paper presents COV19Tweets Dataset (Lamsal 2020a ), a large-scale Twitter dataset with more than 310 million COVID-19 specific English language tweets and their sentiment scores. The dataset's geo version, the GeoCOV19Tweets Dataset (Lamsal 2020b ), is also presented. The paper ...
The data set was collected from four different sources and consisted of 594 COVID-19, 1345 viral pneumonia, and 1341 normal X-ray images. Models are built using Tensorflow and Keras Libraries with Python programming language. Preprocessing was performed on the dataset by applying resizing, ...