Abstract: Most of the content on various social media platforms has enormous textual data. Before being used in machine learning models, this textual data must be transformed into numerical formats ...

ABSTRACT: From the perspective of student consumption behavior, a data-driven framework for screening student loan eligibility was developed using K-means clustering analysis and decision tree models.

Deep learning methods such as multilayer perceptrons (MLPs) and convolutional neural networks (CNNs) have been applied to predict the complex traits in animal and plant breeding. However, it remains ...

Deep learning methods such as multilayer perceptrons and convolutional neural networks have been applied to predict the complex traits in animal and plant breeding. However, it remains challenging to ...

The director, at the height of his powers, delivers a startling, present-day American epic, with Leonardo DiCaprio as a washed-up radical and doting dad. By Manohla Dargis When you purchase a ticket ...

Introduction: Accurately predicting the on-target activity of sgRNAs remains a challenge in CRISPR-Cas9 applications, due to the limited generalization of existing models across datasets, small-sample ...

1 Hunan Provincial Key Laboratory of Finance and Economics Big Data Science and Technology, Hunan University of Finance and Economics, Changsha, China 2 College of Information Science and Engineering, ...

The robots mimic the movements and body temperature of real rabbits, a favored prey of pythons. The project is funded by the South Florida Water Management District and builds upon previous research ...

My dataset consists of 2089 patients and each patient has a sequence of time/code pairs of varying length. The time is numeric value relative to a reference date, with values from 0 back to -800 ...

In today’s world dominated by artificial intelligence, terms like transformers, LLMs (large language models), and embeddings are everywhere. While many are familiar with models like ChatGPT, few truly ...

ABSTRACT: Evaluating drug safety during pregnancy remains an ongoing clinical and pharmacological challenge due to ethical, practical, and regulatory barriers, resulting in scarce human clinical trial ...