Intelligent Decision Support System Based on Heart Failure
DOI:
https://doi.org/10.3991/ijoe.v21i11.56089Keywords:
Machine Learning, healthcare, Artificial Intelligence, Big Data, Prediction, Logistic RegressionAbstract
In the ever-changing realm of healthcare, the integration of advanced technologies and the wealth of medical data presents exciting opportunities to enhance diagnostic processes. This study presents the Intelligent Diagnostic Decision Support System (IDDSS), employing data analysis and AI to aid doctors in making informed diagnostic decisions. The IDDSS harnesses a wealth of patient data, encompassing medical records, test findings, and demographic details. By employing advanced data analysis techniques, it reveals valuable insights, identifies patterns, and establishes correlations within the data. Furthermore, to elevate diagnostic precision, the IDDSS integrates state-of-the-art AI algorithms and machine learning models. These models, trained on extensive datasets, excel in recognizing intricate patterns, categorizing illnesses, and predicting outcomes. Continuously adapting to incorporate the latest medical advancements, the IDDSS remains at the forefront of enhancing healthcare efficacy and patient care. This system has significant potential to advance healthcare diagnostics, ultimately serving as a valuable decision support tool enabling physicians to provide exceptional care and improve patient outcomes.
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Copyright (c) 2025 GHLANA AMARA, Abderrahmane Ez-Zahout, Soumia ZITI

This work is licensed under a Creative Commons Attribution 4.0 International License.

