To our knowledge, this study is the first to apply deep learning models that can, beyond diagnosis, identify molecular subtypes and predict outcomes in a single brain tumour entity (meningioma) using ...

Robust hypothesis testing in statistical classification addresses the challenge of deciding which of several categories best explains observed data when models are uncertain, incomplete or ...

ABSTRACT: Credit risk assessment is a fundamental component of banking operations, directly influencing lending decisions, capital allocation, pricing strategies, and regulatory compliance.

Abstract: Classification of brain tumor is the heart of the computer-aided diagnosis (CAD) system designed to aid the radiologist in the diagnosis of such tumors using Magnetic Resonance Image (MRI).

Implement Neural Network in Python from Scratch ! In this video, we will implement MultClass Classification with Softmax by making a Neural Network in Python from Scratch. We will not use any build in ...

ABSTRACT: Introduction: A large number of studies indicated that ionizing radiation exposure is a risk factor for some cancers and non-cancer diseases. However, hypothesis supported by the literature ...

Kentaro Matsuura (2023). Bayesian Statistical Modeling with Stan, R, and Python. Singapore: Springer. URL: https://link.springer.com/book/10.1007/978-981-19-4755-1 ...

The research fills a gap in standardized guidance for lipidomics/metabolomics data analysis, focusing on transparency and reproducibility using R and Python. The approach offers modular, interoperable ...

A global team led by Michal Holčapek, professor of analytical chemistry at the Faculty of Chemical Technology, UPCE, Pardubice (Czech Republic), and Jakub Idkowiak, a research associate from KU Leuven ...

This repository contains comprehensive implementations and solutions for statistical analysis, data science methodologies, and computational mathematics assignments. Each assignment demonstrates ...