One of the key issues faced by financial institutions is the prediction of loan default. Two machine learning methods, Random Forest and K-Nearest Neighbors (KNN), are tested in this study, using an ...

The workflow encompasses patient datacollection and screening, univariate regression analysis for initial variable selection, systematic comparison of 91 machine learning models,selection and ...

Researchers analyzed clinical data and RNA expression from the peripheral blood of 174 patients with gout and hyperuricemia that had been collected at week 48 of their participation in the STOP Gout ...

1 School of Information Engineering, Anhui University of Chinese Medicine, Hefei, China 2 School of Pharmaceutical Economics and Management, Anhui University of Chinese Medicine, Hefei, China ...

This project implements a pairs trading strategy integrated with machine learning using the K-Nearest Neighbors (KNN) algorithm. Developed as part of an internship at Deepscope, the strategy aims to ...

Recently, many machine learning techniques have been presented to detect brain lesions or determine brain lesion types using microwave data. However, there are limited studies analyzing the location ...

Background: Maternal and child health remains a global public health issue, particularly in low- and middle-income countries where maternal and child mortality are extremely high. The World Health ...

Abstract: The K-nearest neighbors (kNNs) algorithm, a cornerstone of supervised learning, relies on similarity measures constrained by real-number-based distance metrics. A critical limitation of ...

Organizations often face challenges in efficiently assigning volunteers to suitable tasks, especially when dealing with large pools of volunteers with varied skill sets, availabilities, and interests.

Forbes contributors publish independent expert analyses and insights. Writes about the future of finance and technology, follow for more. We live in a world where machines can understand speech, ...