22 papers with code • 1 benchmarks • 2 datasets
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.
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.
The black-box nature of machine learning models hinders the deployment of some high-accuracy models in medical diagnosis.
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
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
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
We explore one of the most recent techniques called symbolic metamodeling to find the mathematical expression of the machine learning models for COVID-19.
In this context, we analyze the burned area severity estimation problem by exploiting a state-of-the-art deep learning framework.
The Severity Prediction of The Binary And Multi-Class Cardiovascular Disease -- A Machine Learning-Based Fusion Approach
To improve the performance of classification, a weighted score fusion approach was taken.