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
According to current predictions, one-fifth of all Americans will develop skin cancer during their lifetime. Cutaneous squamous cell carcinoma (cSCC) most commonly occurs in the head and neck region, which is the area of the body with the highest level of sun exposure. High-risk head and neck cSCC (HNcSCC) is a broad category with numerous high-risk factors that are associated with unfavorable results. In cSCC staging systems, clinical and tumor traits that are likely to result in poor outcomes are identified. Metastasis occurs in ~2.5% of patients with cSCC, most often in the local lymph nodes, and there is some indication that lymph node metastasis has a distinct pattern based on the tumor site. Current findings on tumor molecular targets have suggested the use of systemic treatments, particularly immunotherapy (such as cemiplimab, pembrolizumab and nivolumab), over radiotherapy or chemotherapy for this type of metastasis. However, when used simultaneously with immunotherapy, radiotherapy may be beneficial in the treatment of metastatic HNcSCC by improving the efficacy of immunotherapy. The present review aims to assess the existing literature on metastatic HNcSCC pathways and treatment options, in order to define current and future directions. Notably, there is an urgent need to identify patients who may benefit from local or systemic cancer treatments. The treatment of lymph node metastasis presents a therapeutic challenge and requires comprehensive management.
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.
