Using machine learning to parse breast pathology reports.

Purpose: Extracting information from electronic medical record is a time-consuming and expensive process when done manually. Rule-based and machine learning techniques are two approaches to solving this problem. In this study, we trained a machine learning model on pathology reports to extract pertinent tumor characteristics, which enabled us to create a large database of attribute searchable pathology reports.

Perceptions of pathology informatics by non-informaticist pathologists and trainees.

Background: Although pathology informatics (PI) is essential to modern pathology practice, the field is often poorly understood. Pathologists who have received little to no exposure to informatics, either in training or in practice, may not recognize the roles that informatics serves in pathology. The purpose of this study was to characterize perceptions of PI by noninformatics-oriented pathologists and to do so at two large centers with differing informatics environments.

Spinal cord glioblastoma: 25years of experience from a single institution.

Accounting for less than 0.2% of all glioblastomas, high grade gliomas of the spinal cord are very rare. Here, we discuss our approach to managing patients with high grade spinal cord glioma and review the literature on the subject.

Surgical excision of radial scars diagnosed by core biopsy may help predict future risk of breast cancer.

Radial scars (RS's) are benign breast lesions known to be associated with carcinomas and other high-risk lesions (HRL's). The upgrade rate to carcinoma after core biopsy revealing RS is 0-40 %. We sought to determine the outcomes of RS with and without HRL diagnosed by core biopsy.

Cutaneous and mammary apocrine carcinomas have different immunoprofiles.

Often the distinction of cutaneous apocrine carcinoma from metastatic mammary apocrine carcinoma to the skin can be a diagnostic dilemma because both tumors share similar histologic features and have overlapping immunohistochemical profile. We compared the expression of adipophilin, cytokeratin 5/6, p63, GATA3, mammaglobin, androgen receptor, estrogen receptor, progesterone receptor, and HER2 by immunohistochemistry in 14 cutaneous apocrine carcinomas (11 primary tumors, 3 metastases) and 26 primary apocrine carcinomas of the breast. Whereas focal adipophilin staining was seen in 36% (5/14) of cutaneous apocrine carcinoma, strong and diffuse adipophilin staining was seen in 88% (22/25) of mammary apocrine carcinoma (P = .

The feasibility of using natural language processing to extract clinical information from breast pathology reports.

Objective: The opportunity to integrate clinical decision support systems into clinical practice is limited due to the lack of structured, machine readable data in the current format of the electronic health record. Natural language processing has been designed to convert free text into machine readable data. The aim of the current study was to ascertain the feasibility of using natural language processing to extract clinical information from >76,000 breast pathology reports.

The pathology informatics curriculum wiki: Harnessing the power of user-generated content.

Background: The need for informatics training as part of pathology training has never been so critical, but pathology informatics is a wide and complex field and very few programs currently have the resources to provide comprehensive educational pathology informatics experiences to their residents. In this article, we present the "pathology informatics curriculum wiki", an open, on-line wiki that indexes the pathology informatics content in a larger public wiki, Wikipedia, (and other online content) and organizes it into educational modules based on the 2003 standard curriculum approved by the Association for Pathology Informatics (API).

Methods And Results: In addition to implementing the curriculum wiki at http://pathinformatics.

Health of U.S. Navy submarine crew during periods of isolation.

Background: An essential element in planning for long-term space missions is prediction of the medical support required. Medical data for analogous populations serving in isolated and/or contained environments are useful in predicting health risks for astronauts.

Methods: This study evaluated the rates of health events that occurred among a highly screened, healthy military population during periods of isolation using a centralized database of medical encounter records from U.