Preliminary findings regarding the association between patient demographics and ED experience scores across a regional health system: A cross sectional study using natural language processing of patient comments.

Objective: Existing literature shows associations between patient demographics and reported experiences of care, but this relationship is poorly understood. Our objective was to use natural language processing of patient comments to gain insight into associations between patient demographics and experiences of care.

Methods: This is a cross-sectional study of 14,848 unique emergency department (ED) patient visits from 1/1/2020 to 12/31/2020.

The Innate Immune System Surveillance Biomarker p87 in African Americans and Caucasians with Small High-Grade Dysplastic Adenoma [SHiGDA] and Right-Sided Colon Mutations May Explain the Presence of Multiple Cancers Revealing an Important Minority of Patients with Mutations and Colorectal Neoplasia.

Unlabelled: Colorectal cancer (CRC) outcomes in terms of incidence and mortality are significantly worse in African Americans than other Americans. While differences in primary preventions for neoplasia (diet, obesity remediation, aspirin prophylaxis) are being elucidated, genetic mutations affecting premalignant lesions and immune response mechanisms may possibly also explain the increased incidence and mortality, particularly from right-sided disease.

Objective: Our team therefore examined colonic segments seeking to test the hypothesis that the immune response and somatic genetic profiles of the colonic anatomic segments may vary and thus account for variations in neoplasia risk among the various colonic segments revealing an antigenic relationship with precancerous lesions.

A student trained convolutional neural network competing with a commercial AI software and experts in organ at risk segmentation.

This retrospective, multi-centered study aimed to improve high-quality radiation treatment (RT) planning workflows by training and testing a Convolutional Neural Network (CNN) to perform auto segmentations of organs at risk (OAR) for prostate cancer (PCa) patients, specifically the bladder and rectum. The objective of this project was to develop a clinically applicable and robust artificial intelligence (AI) system to assist radiation oncologists in OAR segmentation. The CNN was trained using manual contours in CT-datasets from diagnostic Ga-PSMA-PET/CTs by a student, then validated (n = 30, PET/CTs) and tested (n = 16, planning CTs).

Assessing the Risk of Interfacility Transport in Pregnant Patients Due to Progression of Labor: Lessons From a Specialized Maternal-Fetal Transport Program.

Background Pregnant laboring patients sometimes require interfacility transfer to a higher level of care. There is a paucity of evidence to inform when it is safe to transfer a laboring patient and when delivery may be too imminent to transfer. Methods This is a retrospective study of pregnant patients undergoing interfacility transfer with a specialized obstetric transport team deployed from a large Midwest regional healthcare system.