THE ROLE OF ARTIFICIAL INTELLIGENCE IN INVESTIGATING QUALITY OF LIFE OUTCOMES IN PATIENTS WITH ARRHYTHMIAS UNDERGOING BREAST CANCER SURGERY

O.S Mehreliyev

doi:10.28942/acj.v26i2y2024.114

Abstract

This study explores the application of artificial intelligence (AI) in assessing quality of life outcomes in patients with arrhythmias who underwent breast cancer surgery. The research focuses on 115 patients with breast cancer, including 45 at the preoperative stage exhibiting signs of metastatic damage to regional lymph nodes. The primary objective is to investigate the impact of arrhythmias on patients' well-being and overall quality of life post-surgery.

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MATERIALS AND METHODS:
A comprehensive and minimally invasive diagnostic approach was employed, involving a range of instrumental examinations. The diagnostic methods included Holter ECG monitoring, conducted in both main and control groups of breast cancer patients. The criteria for initiating Holter ECG monitoring were based on the American Heart Association guidelines (Mond H.G., 2017), with indications being the presence of patient complaints related to cardiac arrhythmias. Daily complaints were recorded through diary entries to establish a comprehensive understanding of the patients' experiences.

RESULTS:
The study revealed critical insights into the prevalence and impact of arrhythmias in breast cancer patients, especially those with metastatic lymph node involvement. AI algorithms were employed to analyze the extensive data gathered from Holter monitoring and other instrumental examinations. These analyses aimed to identify patterns, correlations, and potential predictors of quality of life outcomes in this specific patient population.

CONCLUSION:
Artificial intelligence plays a pivotal role in investigating and understanding the quality of life outcomes in breast cancer patients with arrhythmias. The integration of AI with traditional diagnostic methods enhances the precision and efficiency of data analysis, providing valuable insights that can inform personalized treatment strategies. This research contributes to the growing body of knowledge on the intersection of AI and healthcare, showcasing its potential to improve patient care and outcomes in complex medical scenarios.