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Reply to Letter to the Editor: "Can single CT slices revolutionize personal identification in emergency settings?".
Eur Radiol
October 2024
Department of Radiology, Jena University Hospital-Friedrich Schiller University, 07747, Jena, Germany.
Unveiling the impact of circulating tumor cells: Two decades of discovery and clinical advancements in solid tumors.
Crit Rev Oncol Hematol
November 2024
Department of Medicine, Weill Cornell Medicine, Englander Institute for Precision Medicine, New York Presbyterian Hospital, New York, NY 10021, USA.
Circulating tumor cells (CTCs) enumeration and molecular profiling hold promise in revolutionizing the management of solid tumors. Their understanding has evolved significantly over the past two decades, encompassing pivotal biological discoveries and clinical studies across various malignancies. While for some tumor types, such as breast, prostate, and colorectal cancer, CTCs are ready to enter clinical practice, for others, additional research is required.
View Article and Find Full Text PDFReply to: "Revolutionizing pancreatic cancer management: AI-enhanced vascular burden index assessment with CT imaging".
Eur J Surg Oncol
November 2024
Division of Hepatobiliary and Pancreatic Surgery, Department of Surgery, Brain Korea 21 Project, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea. Electronic address:
Early Breast Cancer Risk Assessment: Integrating Histopathology with Artificial Intelligence.
Cancers (Basel)
May 2024
Division of Pathology, European Institute of Oncology IRCCS, 20141 Milan, Italy.
Effective risk assessment in early breast cancer is essential for informed clinical decision-making, yet consensus on defining risk categories remains challenging. This paper explores evolving approaches in risk stratification, encompassing histopathological, immunohistochemical, and molecular biomarkers alongside cutting-edge artificial intelligence (AI) techniques. Leveraging machine learning, deep learning, and convolutional neural networks, AI is reshaping predictive algorithms for recurrence risk, thereby revolutionizing diagnostic accuracy and treatment planning.
View Article and Find Full Text PDFArtificial Intelligence and IBD: Where are We Now and Where Will We Be in the Future?
Curr Gastroenterol Rep
May 2024
Division of Gastroenterology, Department of Internal Medicine, Michigan Medicine, Ann Arbor, MI, USA.
Purpose Of Review: Artificial intelligence (AI) is quickly demonstrating the ability to address problems and challenges in the care of IBD. This review with commentary will highlight today's advancements in AI applications for IBD in image analysis, understanding text, and replicating clinical knowledge and experience.
Recent Findings: Advancements in machine learning methods, availability of high-performance computing, and increasing digitization of medical data are providing opportunities for AI to assist in IBD care.
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