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Benchmarking study of feature extraction methods for cancer diagnosis using blood-based biomarkers. Feature extraction methods are compared both in terms of their performance and robustness
Machine learning research project: Bayesian Network Structure Learning using Genetic Algorithms.
Biomarker signature identification for Cystic Fibrosis Related Diabetes from miRNAs in ExtraCellular Vesicles
COVID-19 Time-Series Forcasting
Following repository demonstrates machine learning architectures that can correctly classify lesions between LM and AMH. Overall, our methods showcase the potential for computer-aided diagnosis in dermatology, which, in conjunction with remote acquisition can expand the range of diagnostic tools in the community. This code is implemented using Keras and Tensorflow frameworks.
Drug Similarity information
Benchmarking on Feature selection and classification methods for blood-based biomarker discovery
shiny app for FIND network visualization
To accurately predict the regional spread of COVID-19 infection, this study proposes a novel hybrid model which combines a Long short-term memory (LSTM) artificial recurrent neural network with dynamic behavioral models. Several factors and control strategies affect the virus spread, and the uncertainty arisen from confounding variables underlying the spread of the COVID-19 infection is substantial. The proposed model considers the effect of multiple factors to enhance the accuracy in predicting the number of cases and deaths across the top ten most-affected countries and Australia. The results show that the proposed model closely replicates test data. It not only provides accurate predictions but also estimates the daily behavior of the system under uncertainty. The hybrid model outperforms the LSTM model accounting for data limitation. The parameters of the hybrid models were optimized using a genetic algorithm for each country to improve the prediction power while considering regional properties. Since the proposed model can accurately predict COVID-19 spread under consideration of containment policies, is capable of being used for policy assessment, planning and decision-making.
A data-driven, knowledge-based approach to biomarker discovery
Multi-objective, network-based microRNA biomarker discovery of complex disease phenotypes
We present a novel pre-processing method (scPSD) inspired by power spectral density analysis to extract important information from large-scale single-cell omics data and enhance the separation of cellular phenotypes.
Power Spectral Density (psd) preprocessing method in R
Single-cell Annotation and Fusion with Adversarial Open-Set Domain Adaptation Reliable for Data Integration
sample size estimation for ICI responder from microbial data
Survival analysis study for predicting HCC recurrence one year after surgical resection
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.