Publications by authors named "Luiza Camelia Nechita"
Article Synopsis
- This review analyzes how artificial intelligence (AI) is transforming the prediction and prevention of sports injuries through machine learning (ML) and deep learning (DL) techniques, highlighting its capability to analyze complex data and improve injury prevention strategies for athletes.
- It emphasizes the use of various AI models, such as random forests and convolutional neural networks, to create tailored injury risk assessments based on real-time data and individual athlete profiles.
- The review also discusses challenges like data quality, ethical concerns, and the complexities of integrating data in team sports, while showcasing AI's potential to shift injury management from reactive to proactive methods, enhancing athlete safety and performance.
The application of artificial intelligence (AI) in electrocardiography is revolutionizing cardiology and providing essential insights into the consequences of the COVID-19 pandemic. This comprehensive review explores AI-enhanced ECG (AI-ECG) applications in risk prediction and diagnosis of heart diseases, with a dedicated chapter on COVID-19-related complications. Introductory concepts on AI and machine learning (ML) are explained to provide a foundational understanding for those seeking knowledge, supported by examples from the literature and current practices.
View Article and Find Full Text PDF: The objective of the study is to analyze the impact of cardiovascular history on mortality in COVID-19 patients, hospitalized in the intensive care unit with indications for continuous positive airway pressure (CPAP) and subsequently mechanical ventilation, without oncological disease. : A retrospective observational study was carried out on a group of 108 critical COVID-19 patients. We compared demographic data, paraclinical and clinical parameters, days of hospitalization, and mortality rate between two groups of patients, one group with a history of cardiovascular disease (81 patients) and a group without a history of cardiovascular disease (27 patients).
View Article and Find Full Text PDFBackground: Heart failure is a global major healthcare problem with millions of hospitalizations annually and with a very high mortality. There is an increased interest in finding new and reliable biomarkers for the diagnostic, prognostic and therapeutic guidance of patients hospitalized for acute heart failure; Our review aims to summarize in an easy-to-follow flow recent relevant research evaluating the possible use and the clinical value of measuring CA 125 serum levels in acute HF.
Methods: A thorough search in the main international databases identified a relevant pool of 170 articles, providing recently published data for this narrative review that used PRISMA guidelines.
Heart failure is one of the main morbidity and mortality factors in the general population and especially in elderly patients. Thus, at the European level, the prevalence of heart failure is 1% in people under 55 years of age but increases to over 10% in people over 70 years of age. The particularities of the elderly patient, which make the management of heart failure difficult, are the presence of comorbidities, frailty, cognitive impairment and polypharmacy.
View Article and Find Full Text PDF