AP25794129 Cardio Project

About

Research project on cardiac image preprocessing and downstream evaluation for radiology/cardiology workflows.

This repository contains two versions of the project:

ap25794129-cardio-preprocessing — main project version.
for_editor_blinded_review/cardiac-preprocessing-benchmark — an anonymized clone for editor/reviewer download (blinded review package).

Submitted to Radiology Advances (Manuscript ID: RADADV-2026-179) — decision received 2026-07-31: not accepted. The editors' feedback centered on journal fit (the work suits an engineering/data-science readership better than Radiology Advances' primarily clinical audience); no methodological concerns were raised.
A revised submission to Computerized Medical Imaging and Graphics (Elsevier) is in preparation.

The values in ap25794129-cardio-preprocessing/docs/final_results_radiology_ai.md and related CSV tables are transcribed from the Radiology Advances submission tables.
These result tables were added for transparency and reproducibility of that submitted version.
No post-hoc model retraining or parameter tuning was performed to match these reported values.

Maxat Kabdullin — PhD candidate in Information Systems, Department of Information Systems, Satbayev University, Almaty, Kazakhstan. Research interests include deep learning, medical image analysis, cardiovascular imaging workflows, and translational evaluation of artificial intelligence systems in radiology and cardiology. He is also the project lead.
Azat Kabdullin — PhD candidate in Information Systems, Department of Information Systems, Satbayev University, Almaty, Kazakhstan. Research interests include information systems, applied artificial intelligence, and biomedical data analysis.
Lyazat Naizabayeva — Doctor of Technical Sciences, Professor-Researcher, Department of Information Systems, International Information Technology University (IITU), Almaty, Kazakhstan. Research interests include information systems and data analytics.