Effects of two training workshops upon university students' learning of critical thinking.

We evaluated the effect of two workshops on learning about critical thinking amongst first- year university students. 66 Chilean pedagogy students participated, all female, with ages ranging between 18 and 37 years. Two experimental groups were organized, one with direct teaching (n = 22) and another one with semi-directed teaching (n = 19), plus a control group (n = 25).

Acute Arterial Ischemia Secondary to Intrapelvic Acetabular Migration: A Multidisciplinary Approach.

This case report evaluates current diagnostic and treatment approaches for intrapelvic acetabular migration, focusing on the rare but serious complication of acute limb ischemia following hip arthroplasty. A 67-year-old female with a history of total hip arthroplasty 10 years ago presented with acute limb ischemia after experiencing a traumatic event 72 hours prior, which had caused displacement of her hip prosthesis. Notably, she had a history of a traumatic event two years earlier for which she had been advised to undergo surgical correction, which she had refused.

Assessing the documentation of publicly available medical image and signal datasets and their impact on bias using the BEAMRAD tool.

Medical datasets are vital for advancing Artificial Intelligence (AI) in healthcare. Yet biases in these datasets on which deep-learning models are trained can compromise reliability. This study investigates biases stemming from dataset-creation practices.

Missing History: Anarcha, Betsey, and Lucy's Legacy in Gynecologic Textbooks.

The legacy of J. Marion Sims as the "father of gynecology" has become widely controversial among medical professionals and lay public because of ethical concerns surrounding the development of his surgical techniques and his exploitation of enslaved women for his experiments. Notably, in April 2018, the City of New York relocated a commemorative statue of Sims from Central Park following an art commission's investigation of his controversial practices.

From intensive care monitors to cloud environments: a structured data pipeline for advanced clinical decision support.

Background: Clinical decision-making is increasingly shifting towards data-driven approaches and requires large databases to develop state-of-the-art algorithms for diagnosing, detecting and predicting diseases. The intensive care unit (ICU), a data-rich setting, faces challenges with high-frequency, unstructured monitor data. Here, we showcase a successful example of a data pipeline to efficiently move patient data to the cloud environment for structured storage.