ABSTRACT
Cardiovascular diseases (CVDs) are the leading cause of premature death and disability globally, leading to significant increases in healthcare costs and economic strains. Artificial intelligence (AI) is emerging as a crucial technology in this context, promising to have a significant impact on the management of CVDs. A wide range of methods can be used to develop effective models for medical applications, encompassing everything from predicting and diagnosing diseases to determining the most suitable treatment for individual patients. This literature review synthesizes findings from multiple studies that apply AI technologies such as machine learning algorithms and neural networks to electrocardiograms, echocardiography, coronary angiography, computed tomography, and cardiac magnetic resonance imaging. A narrative review of 127 articles identified 31 papers that were directly relevant to the research, encompassing a broad spectrum of AI applications in cardiology. These applications included AI models for ECG, echocardiography, coronary angiography, computed tomography, and cardiac MRI aimed at diagnosing various cardiovascular diseases such as coronary artery disease, hypertrophic cardiomyopathy, arrhythmias, pulmonary embolism, and valvulopathies. The papers also explored new methods for cardiovascular risk assessment, automated measurements, and optimizing treatment strategies, demonstrating the benefits of AI technologies in cardiology. In conclusion, the integration of artificial intelligence (AI) in cardiology promises substantial advancements in diagnosing and treating cardiovascular diseases.
ABSTRACT
To improve the outcome and quality of life for patients with head and neck carcinoma, an increasing amount of research has been performed on the particularities of this type of cancer and its treatment methods. Starting from clinical aspects, including histology and imaging features, up-to-date studies from different parts of the world have determined new data leading to a better understanding of the mechanisms behind the disease and proposed new treatment protocols. The head and neck areas are predisposed to almost all skin neoplasms, most commonly those related to ultraviolet exposure. Squamous cell carcinoma and basal cell carcinoma account for almost 90% of non-melanoma skin cancers in this region; therefore, reviewing the literature on cutaneous carcinomas of the head and neck area and sharing particular aspects of their physiopathology are beneficial for a great number of patients.
