AHA/ASA Journals

Contrastive Machine Learning to Quantify Hypertensive Multiorgan Damage and Identify New Disease Phenotypes: A Multinational Multimodal Study

BACKGROUND: Hypertension induces structural and functional damage in multiple organs. Evidence of subclinical damage ...
Scientific Research Publishing

Deep Reinforcement Learning for Phishing Detection with Transformer-Based Semantic Features ()

Phishing is a form of cybercrime in which people are deceived into exposing their personal information which can result in ...
Visual Studio Magazine

AdaBoost.R2 Regression Using C#

AdaBoost.R2 regression is a machine learning technique used to predict a single numeric value. AdaBoost.R2 builds a sequence of decision tree regressors where each accepted tree improves prediction ...
GitHub

Supervised Learning: Regression & Classification

Predict appliance energy consumption (Wh) from indoor sensor readings and outdoor weather data. Estimate the number of occupants in a room (0–3 people) from multi-modal IoT sensor streams. Implements ...
IEEE

Hyperdimensional Computing Regression: Foundations, Algorithms, and Comparative Review

Abstract: This article offers a targeted survey and comparative analysis of regression techniques based on hyperdimensional computing (HDC), and investigates how they compare with traditional ...
GitHub

CheeseThuong/Predicting-water-levels-using-Linear-Regression

This project addresses the problem of predicting water levels in fish ponds - a critical factor in aquaculture management. Using Machine Learning, we can: Predict water levels based on environmental ...
IEEE

Comparative Analysis of Supervised Machine Learning Algorithms

Abstract: Data mining can be described as a procedure that extracts valuable and informative data from huge amounts of data and then describes the procedure to discover the patterns and meanings ...
Live Science

'Quantum AI' algorithms already outpace the fastest supercomputers, study says

It's quick and easy to access Live Science Plus, simply enter your email below. We'll send you a confirmation and sign you up for our daily newsletter, keeping you up to date with the latest science ...
Scientific Research Publishing

Xie, Z., Jin, J., Liu, D.S., et al. (2024) Construction of a Predictive Model for the Death Risk of Patients with Septic Shock Based on Supervised Machine Learning Algorithms ...

ABSTRACT: Objective: To develop and validate a machine learning-based risk prediction model for postoperative nausea and vomiting (PONV) following gynecological day hysteroscopy, providing ...