Machine learning and natural language processing (NLP) approach to predict early progression to first-line treatment in real-world hormone receptor-positive (HR+)/HER2-negative advanced breast cancer patients.

TL;DR: Guilopgar et al. as mentioned in this paper used transformers for automatic clinical coding in Spanish using a transfer-learning-based approach and achieved state-of-the-art performance on three distinct clinical coding tasks.

TL;DR: A systematic search on PubMed was conducted, identifying 17,324 research papers related to breast cancer pathology as mentioned in this paper, following a semimanual screening, 664 papers were retrieved and pursued.

TL;DR: In this paper , the authors compared whether taking advantage of both structured and unstructured data from health records yields better prediction results than using any of the sources separately, and concluded that combining features from structured and non-structured sources would provide better results than either source alone.

TL;DR: Wang et al. as discussed by the authors introduced IoT cloud-based predictive analytics mainly based on fuzzy cluster-focused augmentation and optimal SVM classification for forecasting breast cancer infection via regular inspection and enhancing the health services by giving healthcare guidelines.

TL;DR: A unified neural network architecture and learning algorithm that can be applied to various natural language processing tasks including part-of-speech tagging, chunking, named entity recognition, and semantic role labeling is proposed.

TL;DR: The authors proposed a unified neural network architecture and learning algorithm that can be applied to various natural language processing tasks including: part-of-speech tagging, chunking, named entity recognition, and semantic role labeling.

TL;DR: In the setting of a challenge competition, some deep learning algorithms achieved better diagnostic performance than a panel of 11 pathologists participating in a simulation exercise designed to mimic routine pathology workflow; algorithm performance was comparable with an expert pathologist interpreting whole-slide images without time constraints.

TL;DR: Among patients with previously untreated ER-positive, HER2-negative advanced breast cancer, palbociclib combined with letrozole resulted in significantly longer progression-free survival than that with let rozole alone, although the rates of myelotoxic effects were higher with palbokiclib-letrozoles.