Tech Xplore

AI model predicts robberies across US cities with 86.3% accuracy

Researchers have developed an artificial intelligence model that predicts crime more accurately than several existing ...
Medical Xpress

Review on glioma organoid models proposes new classification framework for brain cancer research

Researchers from the Terasaki Institute for Biomedical Innovation, together with key pioneers in glioma biology, neuro-oncology and stem cell biology, have published a comprehensive review in Society ...
News Medical

AI-driven model predicts type 1 diabetes risk with greater accuracy

Study: Genetic association and machine learning improve the prediction of type 1 diabetes risk. Image credit: sasirin pamai/Shutterstock.com Researchers performed genetic association analysis and ...
LinkedIn

Logistic Regression: Understanding the Concepts Behind a Fundamental Classification Algorithm

Machine learning models are often introduced as tools for making predictions, but the real value of a model lies in understanding how it represents relationships in data. Logistic Regression is one of ...
IEEE

Power Quality Disturbance Classification Assessment Using Logistic Regression Algorithm

Abstract: Voltage sag, swell, harmonics, and transients are power quality (PQ) disturbances that damage modern electrical apparatus. This paper presents an effective classification approach using ...
LinkedIn

Email Spam Classification Using Logistic Regression and TF-IDF Vectorization: A Natural Language Processing Approach for Message Filtering

I am pleased to present my latest work in natural language processing and applied machine learning: a binary text classification system designed to discriminate between legitimate (ham) and ...
Scientific Research Publishing

Efficiency of Classification Algorithms in Monitoring Land Use through Remote Sensing in Sissili Province of Burkina Faso ()

Monitoring of natural resources is a major challenge that remote sensing tools help to facilitate. The Sissili province in Burkina Faso is a territory that includes significant areas dedicated for the ...
IEEE

Fuzzy LASSO Logistic Regression: A Regularized Framework for Interpretable Binary Classification Under Uncertainty

Abstract: Fuzzy classification models are important for handling uncertainty and heterogeneity in high-dimensional data. Although recent fuzzy logistic regression approaches have demonstrated ...
Frontiers

A TPS-based numerical method for simulating the non-linear diffusion logistic population model

The Fisher–Kolmogorov–Petrovsky–Piskunov equation is a diffusive logistic model for the population density of an invasive species. This paper presents a one-level numerical simulation of the ...
Scientific Research Publishing

Shipe, M.E., Deppen, S.A., Farjah, F. and Grogan, E.L. (2019) Developing Prediction Models for Clinical Use Using Logistic Regression: An Overview. Journal of Thoracic Disease ...

ABSTRACT: Bipolar disorder is a multifaceted psychiatric illness characterized by unpredictable mood episodes and highly variable treatment responses across individuals. Predicting response to ...
Nature

Enhancing anomaly detection in IoT-driven factories using Logistic Boosting, Random Forest, and SVM: A comparative machine learning approach

Three machine learning algorithms—Logistic Boosting, Random Forest, and Support Vector Machines (SVM)—were evaluated for anomaly detection in IoT-driven industrial environments. A real-world dataset ...
Nature

An automatic classification of breast cancer using fuzzy scoring based ResNet CNN model

The expansion rate of medical data during the past ten years has rapidly expanded due to the vast fields. The automated disease diagnosis system is proposed using a deep learning (DL) algorithm, which ...