Early Breast Cancer Risk Assessment: Integrating Histopathology with Artificial Intelligence

Cancers, Journal Year: 2024, Volume and Issue: 16(11), P. 1981 - 1981

Published: May 23, 2024

Effective risk assessment in early breast cancer is essential for informed clinical decision-making, yet consensus on defining categories remains challenging. This paper explores evolving approaches stratification, encompassing histopathological, immunohistochemical, and molecular biomarkers alongside cutting-edge artificial intelligence (AI) techniques. Leveraging machine learning, deep convolutional neural networks, AI reshaping predictive algorithms recurrence risk, thereby revolutionizing diagnostic accuracy treatment planning. Beyond detection, applications extend to histological subtyping, grading, lymph node assessment, feature identification, fostering personalized therapy decisions. With rising rates, it crucial implement accelerate breakthroughs practice, benefiting both patients healthcare providers. However, important recognize that while offers powerful automation analysis tools, lacks the nuanced understanding, context, ethical considerations inherent human pathologists patient care. Hence, successful integration of into practice demands collaborative efforts between medical experts computational optimize outcomes.

Language: Английский

Review of the monarchE trial suggests no evidence to support use of adjuvant abemaciclib in women with breast cancer – Authors' reply

The Lancet Oncology, Journal Year: 2023, Volume and Issue: 24(6), P. e238 - e238

Published: May 2, 2023

Language: Английский