This narrative review explores the burgeoning field of Artificial Intelligence (AI)-driven Breast Cancer (BC) survival prediction, emphasizing the transformative impact on patient care. From machine learning to deep neural networks, diverse models demonstrate the potential to refine prognosis accuracy and tailor treatment strategies. The literature underscores the need for clinician integration and addresses challenges of model generalizability and ethical considerations.
View Article and Find Full Text PDFAim: The management of metastatic prostate cancer has progressed immensely in the last decade. This study aims to investigate the real-world clinical outcomes of metastatic prostate adenocarcinoma treated with abiraterone and enzalutamide. The findings will assist healthcare providers in making more informed decisions when choosing between these two drugs for treating these patients.
View Article and Find Full Text PDFBackground: Renal cell carcinomas (RCCs) are renal parenchymal neoplasms that contribute to <5% of cancer cases worldwide. Within the diverse group of renal tumours, clear cell carcinoma is the most common subtype. The recommended first-line treatment for metastatic disease is a tyrosine kinase inhibitor given either as monotherapy or in combination with an immune checkpoint inhibitor, based on improved survival outcomes.
View Article and Find Full Text PDFBackground: Esophageal neoplasms rank as the 7th most common cancers in the world. Squamous cell carcinomas of esophagus (SCCE) are the predominant subset, linked to a number of genetic alterations. Gene-driven tumour pathways are being increasingly identified with the emerging role of next-generation sequencing.
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