severity prediction

22 papers with code • 1 benchmarks • 2 datasets

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Most implemented papers

CVEfixes: Automated Collection of Vulnerabilities and Their Fixes from Open-Source Software

secureIT-project/CVEfixes 19 Jul 2021

Data-driven research on the automated discovery and repair of security vulnerabilities in source code requires comprehensive datasets of real-life vulnerable code and their fixes.

AbuseAnalyzer: Abuse Detection, Severity and Target Prediction for Gab Posts

mohit3011/AbuseAnalyzer COLING 2020

While extensive popularity of online social media platforms has made information dissemination faster, it has also resulted in widespread online abuse of different types like hate speech, offensive language, sexist and racist opinions, etc.

Interpretable Machine Learning for COVID-19: An Empirical Study on Severity Prediction Task

wuhanstudio/interpretable-ml-covid-19 30 Sep 2020

The black-box nature of machine learning models hinders the deployment of some high-accuracy models in medical diagnosis.

Uncertainty-Aware Multi-Modal Ensembling for Severity Prediction of Alzheimer's Dementia

wazeerzulfikar/alzheimers-dementia 3 Oct 2020

Reliability in Neural Networks (NNs) is crucial in safety-critical applications like healthcare, and uncertainty estimation is a widely researched method to highlight the confidence of NNs in deployment.

COVIDX: Computer-aided diagnosis of Covid-19 and its severity prediction with raw digital chest X-ray images

wajidarshad/covidx 25 Dec 2020

In the absence of specific drugs or vaccines for the treatment of COVID-19 and the limitation of prevailing diagnostic techniques, there is a requirement for some alternate automatic screening systems that can be used by the physicians to quickly identify and isolate the infected patients.

An integrated autoencoder-based hybrid CNN-LSTM model for COVID-19 severity prediction from lung ultrasound

ankangd/HybridCovidLUS 1 May 2021

The proposed convolutional neural network (CNN) architecture implements an autoencoder network and separable convolutional branches fused with a modified DenseNet-201 network to build a vigorous, noise-free classification model.

Global and Local Interpretation of black-box Machine Learning models to determine prognostic factors from early COVID-19 data

ananyajana/interpretable_covid19 10 Sep 2021

We explore one of the most recent techniques called symbolic metamodeling to find the mathematical expression of the machine learning models for COVID-19.

Attention to Fires: Multi-Channel Deep Learning Models for Wildfire Severity Prediction

dbdmg/rescue Applied Sciences 2021

In this context, we analyze the burned area severity estimation problem by exploiting a state-of-the-art deep learning framework.