BMJ

Machine learning algorithms reveal unique gene expression profiles in muscle biopsies from patients with different types of myositis

Objectives Myositis is a heterogeneous family of diseases that includes dermatomyositis (DM), antisynthetase syndrome (AS), immune-mediated necrotising myopathy (IMNM), inclusion body myositis (IBM), ...
GitHub

tiskw/random-fourier-features

RFF can be applicable to many other machine learning algorithms than the above. The author will provide implementations of the other algorithms soon. This module supports training/inference on GPU.
GitHub

High accuracy captcha solver for SJTU Jaccount login page using SVM and ResNet.

This work includes two high performance recognizers. The SVM based recognizer has an accuracy of 90%. It first applies projection-based algorithm to the input image, then use a pre-trained SVM model ...
Nature

Repurposing FDA approved drugs for psoriasis indications through integrated molecular docking, one-SVM algorithm, and molecular dynamics simulation approaches

The exact cause of psoriasis is still unclear and there is no treatment available for its permanent reemission. The available biologics for disease treatment, are stated to be associated with a high ...
Design News

How to Build an Arduino-Based Solar Power Prediction System Using Python & Machine Learning, Part 2

In this tutorial, we’ll build on the foundation laid in the “Arduino-Based Solar Power System Using Python & Machine Learning, Part 1” project by exploring how to intelligently select and use machine ...
IEEE

Development of a Conditional Generative Adversarial Network Model for Television Spectrum Radio Environment Mapping

Abstract: To efficiently use the finite wireless communication resource (radio spectrum), a Radio Environment Map (REM) is needed to monitor, analyse and provide rich awareness of spectrum activities ...
IEEE

Buried Magnetic Material Detection System: An SVM Algorithm Application

Abstract: In recent times, studies about remote-sensing methods have focused on improving variables like sensing distance, sensitivity, and power consumption of available remote-sensing methods. The ...
snmjournals.org

Exploring the impact of feature selection methods and classification algorithms on the predictive performance of PET radiomic ML models in lung cancer

Introduction: The high-dimensional data from the radiomics technique can lead to overfitting and poor performance in predicting lung cancer mutation status. Thus, finding the best combination of ...
Nature

Construction of power network security risk assessment model based on LSA-SVM algorithm in the background of smart grid

Due to theintricate and interdependent nature of the smart grid, it has encountered an increasing number of security threats in recent years. Currently, conventional security measures such as ...
InfoWorld

14 popular AI algorithms and their uses

Large language models have captured the news cycle, but there are many other kinds of machine learning and deep learning with many different use cases. Amid all the hype and hysteria about ChatGPT, ...
Scientific Research Publishing

Pedregosa, F., Varoquaux, G., Gramfort, A., et al. (2011) Scikit-Learn: Machine Learning in Python. Journal of Machine Learning Research, 12, 2825-2830.

ABSTRACT: The manuscript presents an augmented Lagrangian—fast projected gradient method (ALFPGM) with an improved scheme of working set selection, pWSS, a decomposition based algorithm for training ...