Natural Language Processing to Extract Meaningful Information from a Corpus of Written Knowledge in Breast Cancer: Transforming Books into Data.

Introduction: Books and papers are the most relevant source of theoretical knowledge for medical education. New technologies of artificial intelligence can be designed to assist in selected educational tasks, such as reading a corpus made up of multiple documents and extracting relevant information in a quantitative way.

Methods: Thirty experts were selected transparently using an online public call on the website of the sponsor organization and on its social media.

Should Acellular Dermal Matrices Be Used for Implant-based Breast Reconstruction after Mastectomy? Clinical Recommendation Based on the GRADE Approach.

Unlabelled: Acellular dermal matrices (ADMs) entered the market in the early 2000s and their use has increased thereafter. Several retrospective cohort studies and single surgeon series reported benefits with the use of ADMs. However, robust evidence supporting these advantages is lacking.

Evaluation of word embedding models to extract and predict surgical data in breast cancer.

Background: Decisions in healthcare usually rely on the goodness and completeness of data that could be coupled with heuristics to improve the decision process itself. However, this is often an incomplete process. Structured interviews denominated Delphi surveys investigate experts' opinions and solve by consensus complex matters like those underlying surgical decision-making.

Processing methods for human amniotic membrane as scaffold for tissue engineering with mesenchymal stromal human cells.

Tissue engineering is an interdisciplinary field that applies the principles of engineering and life sciences toward the development of biological substitutes that restore, maintain, or improve tissue function. The aims of this work were to compare chemically and physically processed human Amniotic Membranes (hAM) and analyze the cytocompatibility and proliferation rate (PR) of two primary human mesenchymal stromal cell lines, from different sources and donor conditions seeded over these scaffolds. The evaluated hAM processes were: cold shock to obtain a frozen amniotic membrane (FEAM) with remaining dead epithelial cells, denudation of hAM with trypsin for 20/10 min (DEAM20/10) or treatment with sodium dodecyl sulfate to decellularized hAM (DAM).

Text mining and word embedding for classification of decision making variables in breast cancer surgery.

Introduction: Decision making in surgical oncology of the breast has increased its complexity over the last twenty years. This Delphi survey investigates the opinion of an expert panel about the decision making process in surgical procedures on the breast for oncological purposes.

Methods: Twenty-seven experts were invited to partake into a Delphi Survey.