Logo Lanfrica
  • Accueil
  • Atlas
  • Analyses
  • Documentation
  • Sign in

© 2026 Lanfrica. Tous droits réservés. Tous les droits d'auteur des ressources affichées sur le site Web Lanfrica appartiennent aux détenteurs de droits d'auteur d'origine, sauf indication contraire explicite.

Prediction of Tuberculosis on HIV Patients Based on Gene Expression Data Using Grey Wolf Optimization-Support Vector Machine

Type de record:

paper
Créateur:
HanHasIsm
Éditeur:
IEEE
Hôte:

Visit

doi.org

Licenses

https://doi.org/10.15223/policy-029https://doi.org/10.15223/policy-037

Similaires

Student Academic Performance Prediction Using Support Vector MachineSocial Unrest Prediction Through Sentiment Analysis on Twitter Using Support Vector Machine: Experimental Study on Nigeria’s #EndSARSTraffic Accidents Severity Prediction using Support Vector Machine ModelsPATH LOSS PREDICTION BASED ON MACHINE LEARNING TECHNIQUES: SUPPORT VECTOR MACHINE, ARTIFICIAL NEURAL NETWORK, AND MULTILINEAR REGRESSION MODELGene expression prediction: A machine learning approachPoster on Deep Learning-Based Prediction of High-Yield Wheat Transcriptomes Using Network Biology and Gene Expression Analysis

Student Academic Performance Prediction Using Support Vector Machine

This paper investigates the relationship between students' preadmission academic profile and final a

Social Unrest Prediction Through Sentiment Analysis on Twitter Using Support Vector Machine: Experimental Study on Nigeria’s #EndSARS

Abstract Social unrest is a powerful mode of expression and organized form of behav

Traffic Accidents Severity Prediction using Support Vector Machine Models

International audience In recent years, road traffic accidents (RTA) have become one

PATH LOSS PREDICTION BASED ON MACHINE LEARNING TECHNIQUES: SUPPORT VECTOR MACHINE, ARTIFICIAL NEURAL NETWORK, AND MULTILINEAR REGRESSION MODEL

The rapid progress in fairness, transparency, and reliability is inextricably linked to Nigeria's ri

Gene expression prediction: A machine learning approach

Tremendous progress in understanding and unravelling genetic predictors of complex traits have been

Poster on Deep Learning-Based Prediction of High-Yield Wheat Transcriptomes Using Network Biology and Gene Expression Analysis

This study integrates transcriptomic analysis, network biology, and deep learning to identify key ge