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 ...

When an LLM produces a categorical decision (apply / consider / reject; pass / fail / needs-review; high / medium / low), do not let it emit the verdict directly. Have it emit the underlying evidence ...

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.

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 ...

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 ...

In the wake of Charlie Kirk’s killing, the Republican policy apparatus went immediately to work. The Heritage Foundation, which published Project 2025, and its spinoff, the Oversight Project, issued a ...

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