Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...

A signal-processing–based framework converts DNA sequences into numerical signals to identify protein-coding regions. By integrating spectral analysis and SVM classification, the approach improves ...

A deep learning framework combines convolutional and bidirectional recurrent networks to improve protein function prediction from genomic ...

Background: Alterations in brain structure have been suggested to be associated with bulimia nervosa (BN). This study aimed to employ machine learning (ML) methods based on diffusion tensor imaging ...

If you just want to test the emulator without installing a RISC-V compiler, you will find pre-built binaries in prebuilt/. The emulator provides a Python API that allows users to control execution, ...

Abstract: The Support Vector Machine (SVM) is a popular classification algorithm and is known for its generalization properties in machine learning. In this paper, we propose parallel implementation ...

The stroke deprives person's brain of oxygen and nutrients, which can cause brain cells to die. Numerous works have been carried out for predicting various diseases by comparing the performance of ...

Software defect prediction and cost estimation are critical challenges in software engineering, directly influencing software quality and project management efficiency. This study presents a ...

Abstract: Sentiment AI leverages artificial intelligence to analyze human emotions across various fields. This research focuses on understanding patient experiences with healthcare facilities by using ...

In the era of big data and artificial intelligence, machine learning is one of the hot issues in the field of credit rating. On the basis of combing the literature on credit rating methods at home and ...