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ZENODO
Software . 2025
Data sources: ZENODO
ZENODO
Software . 2025
Data sources: Datacite
ZENODO
Software . 2025
Data sources: Datacite
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CardioAtlas

Authors: Usai, Luigi;
Abstract

Title: CardioAtlas: A Scalable Desktop Application for Personal Cardiology Knowledge Management Description: CardioAtlas is a specialized desktop application developed in Python for creating, managing, and consulting a personal, comprehensive encyclopedia of cardiological diseases. This tool is designed for students, researchers, healthcare professionals, and enthusiasts who need a structured and efficient way to organize and access medical information. The core of CardioAtlas is its innovative Scalable File-System-based Data Library (SFDL) architecture. Unlike monolithic database files, this model uses a structured directory of individual JSON files, each representing a single pathology, orchestrated by a lightweight central index file (index.json). This design ensures: Scalability: The application's performance remains optimal, with near-instantaneous startup times, regardless of the number of entries in the database (from tens to thousands). Performance: Data is loaded on-demand ("lazy loading"), meaning that the full details of a pathology are only read from disk when selected by the user, minimizing memory consumption. Portability and Simplicity: The entire database is contained within a self-contained folder, making the application fully portable. The data remains human-readable and can be managed协同 with simple text editors. Key Features: Intuitive GUI: A clean and functional graphical user interface built with Python's Tkinter library (ttk themed widgets). Structured Data Display: Pathologies are presented with clear, distinct sections for description, symptoms, causes, and treatments. On-Demand Data Loading: Ensures a fast and responsive user experience. Category-based Navigation: Browse diseases through major cardiological categories (e.g., Ischemic Heart Diseases, Arrhythmias, Valvular Diseases, Rare Diseases). Keyword Search: A powerful search function that queries metadata in the index for quick and efficient retrieval of information. Extensible Database: Comes with a companion Python script (distribuisci_files.py) that automatically populates the file-system database from a master JSON file, allowing for easy, non-destructive, and incremental updates. Disclaimer:This software is intended as an educational, research, and personal knowledge management tool. The information contained within is not a substitute for professional medical advice, diagnosis, or treatment. Always seek the advice of a qualified health provider with any questions you may have regarding a medical condition. Versione Italiana Titolo: CardioAtlas: Un'Applicazione Desktop Scalabile per la Gestione della Conoscenza Cardiologica Personale Descrizione: CardioAtlas è un'applicazione desktop specializzata, sviluppata in Python, per la creazione, gestione e consultazione di un'enciclopedia personale e completa delle patologie cardiologiche. Questo strumento è progettato per studenti, ricercatori, professionisti sanitari e appassionati che necessitano di un metodo strutturato ed efficiente per organizzare e accedere a informazioni mediche. Il cuore di CardioAtlas è la sua innovativa architettura "Libreria di Dati Scalabile su File System" (SFDL). A differenza di file di database monolitici, questo modello utilizza una directory strutturata di singoli file JSON, ognuno dei quali rappresenta una singola patologia, orchestrati da un file indice centrale e leggero (index.json). Questo design garantisce: Scalabilità: Le performance dell'applicazione rimangono ottimali, con tempi di avvio quasi istantanei, indipendentemente dal numero di voci nel database (da decine a migliaia). Performance: I dati vengono caricati on-demand ("lazy loading"), il che significa che i dettagli completi di una patologia sono letti dal disco solo quando vengono selezionati dall'utente, minimizzando il consumo di memoria. Portabilità e Semplicità: L'intero database è contenuto in una cartella auto-consistente, rendendo l'applicazione pienamente portabile. I dati rimangono leggibili dall'uomo e gestibili con semplici editor di testo. Funzionalità Chiave: GUI Intuitiva: Un'interfaccia grafica pulita e funzionale, costruita con la libreria Tkinter di Python (widget tematici ttk). Visualizzazione Dati Strutturata: Le patologie sono presentate con sezioni chiare e distinte per descrizione, sintomi, cause e trattamenti. Caricamento Dati On-Demand: Assicura un'esperienza utente veloce e reattiva. Navigazione per Categorie: Permette di esplorare le malattie attraverso le principali categorie cardiologiche (es. Cardiopatie Ischemiche, Aritmie, Malattie delle Valvole, Malattie Rare). Ricerca per Parole Chiave: Una potente funzione di ricerca che interroga i metadati nell'indice per un recupero rapido ed efficiente delle informazioni. Database Estensibile: Fornito con uno script Python di supporto (distribuisci_files.py) che popola automaticamente il database su file system a partire da un file JSON master, consentendo aggiornamenti facili, non distruttivi e incrementali. Disclaimer:Questo software è inteso come strumento educativo, di ricerca e di gestione della conoscenza personale. Le informazioni contenute non sostituiscono in alcun modo il parere, la diagnosi o il trattamento di un medico qualificato. Consultare sempre un professionista sanitario per qualsiasi domanda relativa a una condizione medica.

Keywords

python, malattie cardiologiche, Cardiology, Luigi Usai, patologie cardiache, Usai Luigi, Software, Atlante Cardiologico, Cardiologia

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average