A binary classification problem is a type of supervised learning task in machine learning where the goal is to predict to which of two classes (categories) a particular instance belongs to [Bishop, ...

ABSTRACT: The research examines how different key parameters affect the SEIRD epidemic model through MATLAB Simulink simulations. The simulation model includes three scenarios which consist of a ...

In this study, the authors developed a novel radiotherapy sensitivity score (NPC-RSS) for nasopharyngeal carcinoma patients using machine learning algorithms. They identified 18 key genes associated ...

Revised: This Reviewed Preprint has been revised by the authors in response to the previous round of peer review; the eLife assessment and the public reviews have been updated where necessary by the ...

Abstract: In the mobile CDN environment, the information spread within the coverage of any edge server may contain sensitive information, so the sensitive information needs to be protected during the ...

Objective: Develop a predicting model that can help stratify patients with epithelial ovarian cancer (EOC) before platinum-based chemotherapy. Methods: 148 patients with pathologically confirmed EOC ...

% This code fits a SIR model for LA county data on COVID-19 - https://github.com/datadesk/california-coronavirus-data and http://publichealth.lacounty.gov/media ...

Introduction: The SIR (Susceptible-Infected-Recovered) model is one of the simplest and most widely used frameworks for understanding epidemic outbreaks. Methods: A second-order dynamical system for ...

This repository contains codes developed in 2022 to simulate the proposed Mobile Human Ad Hoc Network model to simulate the infectious disease spread based on airborne transmission.

A powerful new video-generating AI model became widely available today — but there’s a catch: The model appears to be censoring topics deemed too politically sensitive by the government in its country ...