EurekAlert!

An interpretable machine learning model for predicting 5‐year survival in breast cancer based on integration of proteomics and clinical data

Breast cancer is a highly heterogeneous malignancy among women worldwide. Traditional prognostic models relying solely on ...
Scientific Research Publishing

Halder, R.K., et al. (2024) Enhancing K-Nearest Neighbor Algorithm: A Com-prehensive Review and Performance Analysis of Modifications. Journal of Big Data, 11, Article No. 113.

ABSTRACT: The objective of this work is to determine the true owner of a land—public or private—in the region of Kumasi (Ghana). For this purpose, we applied different machine learning methods to the ...
Frontiers

SHAP combined with machine learning to predict mortality risk in maintenance hemodialysis patients: a retrospective study

Background: Patients undergoing maintenance hemodialysis face a high mortality rate, yet effective tools for predicting mortality risk in this population are lacking. This study aims to develop an ...
GitHub

FPGA-Based Hardware Accelerator for K-Nearest Neighbors (KNN)

This repository contains the implementation of a hardware-accelerated K-Nearest Neighbors (KNN) algorithm using Verilog on an FPGA. The project includes performance and timing analysis using Quartus, ...
IEEE

Concise Prediction of Early Floods in Variable Weather Forecasts using K Nearest Neighbor

Abstract: Aim: In light of unpredictable weather forecasts, the goal of this research is to develop and assess a sophisticated K nearest Neighbor (KNN) based systematic prediction system for early ...
Scientific Research Publishing

Tang, Y., Chang, Y. and Li, K. (2023) Applications of K-Nearest Neighbor Algorithm in Intelligent Diagnosis of Wind Turbine Blades Damage. Renewable Energy, 212, 855-864.

ABSTRACT: To ensure the efficient operation and timely maintenance of wind turbines, thereby enhancing energy security, it is critical to monitor the operational status of wind turbines and promptly ...
GitHub

knearest-neighbor-algorithm

This project demonstrates how to implement the K-Nearest Neighbors (KNN) algorithm for classification on a customer dataset. The program iterates through different values of k (number of neighbors) ...