Data Quality Assessment of HIV EHRs for Trustworthy AI (Zambia): analysis code

D4.3 Code security and quality assessment

Nikolaos Nikolaidis, Dimosthenis Natsos

This document represents a key technical contribution to the RAISE project, specifically focusing on the quality and security of the distributed code in the infrastructure. To ensure the highest standard of scientific rigor and to facilitate the wide dissemination of project resu…Read more

Data and Code Supporting "Enhancing Urban Flood Risk Assessment: A PCA-Integrated Deep Learning Surrogate for Hazard and Damage Prediction"

Hyeon‐Tae Moon, G. Kim

This record provides the processed data and Version 1.0 of the analysis code supporting the study “Enhancing Urban Flood Risk Assessment: A PCA-Integrated Deep Learning Surrogate for Hazard and Damage Prediction.” The archive includes the synthetic rainfall–inundation–damage data…Read more

Data and Code to reproduce results in paper "A Systematic Literature Review on Graph-Based Models in Credit Risk Assessment"

Lennart John Baals, Yiting Liu, Joerg Osterrieder, Branka Hadji Misheva

Data and Code to reproduce results in paper "A Systematic Literature Review on Graph-Based Models in Credit Risk Assessment" This repository contains the necessary codes to reproduce results in the paper: Baals, L. J., Liu, Y., Osterrieder, J., & Hadji-Misheva, B. (2025). A Syste…Read more

Also available via: European Organization for Nuclear Research

Integrating ToF-SIMS and machine learning reveals a mammary tumor-associated multi-ion signature — analysis code

Auraya Manaprasertsak, Wei Tang, Caroline Lööf, Laila Azemovic, Sofie Mohlin, Catharina Hagerling, et al.

Analysis code, result tables, and figures for a time-of-flight secondary ion mass spectrometry (ToF-SIMS) machine-learning study of a mammary tumor-associated multi-ion signature and its detectability across biological samples in the MMTV-PyMT mouse model of breast cancer. Accomp…Read more

A Scalable Distributed and Fault-Tolerant Architecture for Cloud-Based Machine Learning and Data Analysis

Grace Dooshima GBOR, Emmanuel Ogala, Donald Douglas Atsa’am, Iorshashe Agaji

Abstract The rapid growth of data-intensive applications has necessitated the development of scalable and efficient architectures for cloud-based machine learning and data analysis. This study proposes a scalable, distributed, and fault-tolerant architecture designed to address t…Read more

Deciphering the Host-Range Grammar of Orthoflaviviruses Using Foundation Model Embeddings: A Leakage-Aware Evaluation Framework — Data and Code

Brhanu F. Znabu, Qiuming Yao, Nicole R. Sexton

Data and code for a leakage-aware evaluation of machine-learning predictors of orthoflavivirus host range. Contains the full analysis pipeline, DNABERT-2 embeddings, window-level sequence data, results, and figure-generation scripts to reproduce every figure and result. verify_re…Read more