COVID-19 Diagnosis
82 papers with code • 7 benchmarks • 11 datasets
Covid-19 Diagnosis is the task of diagnosing the presence of COVID-19 in an individual with machine learning.
Benchmarks
These leaderboards are used to track progress in COVID-19 Diagnosis
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Libraries
Use these libraries to find COVID-19 Diagnosis models and implementationsDatasets
COVIDx
COVID-19 Image Data Collection
BrixIA
BIMCV COVID-19
Large COVID-19 CT scan slice dataset
Synthetic COVID-19 CXR Dataset
Novel COVID-19 Chestxray Repository
Latest papers
COVID-19 Detection Using Slices Processing Techniques and a Modified Xception Classifier from Computed Tomography Images
This paper extends our previous method for COVID-19 diagnosis, proposing an enhanced solution for detecting COVID-19 from computed tomography (CT) images.
CT-xCOV: a CT-scan based Explainable Framework for COVid-19 diagnosis
Lastly, the results of the comparison of XAI techniques show that Grad-Cam gives the best explanations compared to LIME and IG, by achieving a Dice coefficient of 55%, on COVID-19 positive scans, compared to 29% and 24% obtained by IG and LIME respectively.
C2C: Cough to COVID-19 Detection in BHI 2023 Data Challenge
woo-jin-chung/bhi_2023_challenge_audio_alchemists
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This report describes our submission to BHI 2023 Data Competition: Sensor challenge.
COVID-19 detection using ViT transformer-based approach from Computed Tomography Images
This method involves evaluating all CT slices for a given patient and assigning the patient the diagnosis that relates to the thresholding for the CT scan.
Virtual imaging trials improved the transparency and reliability of AI systems in COVID-19 imaging
In this study, COVID-19 serves as a case example to unveil the intrinsic and extrinsic factors influencing AI performance.
On the Impact of Voice Anonymization on Speech-Based COVID-19 Detection
zhu00121/anonymized-speech-diagnostics
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With advances seen in deep learning, voice-based applications are burgeoning, ranging from personal assistants, affective computing, to remote disease diagnostics.
Enhancing COVID-19 Severity Analysis through Ensemble Methods
aanandt/enhancing-covid-19-severity-analysis-through-ensemble-methods
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Computed Tomography (CT) scans provide a detailed image of the lungs, allowing clinicians to observe the extent of damage caused by COVID-19.
CECT: Controllable Ensemble CNN and Transformer for COVID-19 Image Classification
nus-tim/cect
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With remarkable feature capture ability and generalization ability, we believe CECT can be extended to other medical scenarios as a powerful diagnosis tool.
DeltaNet:Conditional Medical Report Generation for COVID-19 Diagnosis
To reduce the workload of radiologists, we propose DeltaNet to generate medical reports automatically.
CoV-TI-Net: Transferred Initialization with Modified End Layer for COVID-19 Diagnosis
In this research, the PyTorch pre-trained models (VGG19\_bn and WideResNet -101) are applied in the MNIST dataset for the first time as initialization and with modified fully connected layers.
