Development and Evaluation of a Bariatric Mannequin Simulation System.

Physical assessment of obese patients is an essential clinical skill for identifying the numerous health problems of obese patients and monitoring treatment effectiveness. Use of simulation mannequins facilitates teaching and learning of physical assessment. Available bariatric simulation mannequins have poor functional design, unrealistic appearance, and limited assessment functions.

Correction: A Bayesian belief data mining approach applied to rice and shrimp aquaculture.

[This corrects the article DOI: 10.1371/journal.pone.

Impact of Transfer Learning Using Local Data on Performance of a Deep Learning Model for Screening Mammography.

Purpose To investigate the issues of generalizability and replication of deep learning models by assessing performance of a screening mammography deep learning system developed at New York University (NYU) on a local Australian dataset. Materials and Methods In this retrospective study, all individuals with biopsy or surgical pathology-proven lesions and age-matched controls were identified from a South Australian public mammography screening program (January 2010 to December 2016). The primary outcome was deep learning system performance-measured with area under the receiver operating characteristic curve (AUC)-in classifying invasive breast cancer or ductal carcinoma in situ ( = 425) versus no malignancy ( = 490) or benign lesions ( = 44).

Development and Evaluation of a Wearable Simulator System.

Background: Peer physical examination is a clinical teaching-learning approach used for decades because of the convenient sample of peers for practicing. However, this approach has limitations when learning to assess abnormalities and threatens psychologically safe learning. A wearable simulator system was designed for learning physical examination skills to minimize ethical and learning challenges.

Non-anatomical reconstruction of chronic posterolateral corner knee injuries show failure rates from 0% to 36% versus 4.3% to 24.2% for anatomic reconstruction techniques: An updated systematic review reflecting the 2019 expert consensus statement.

Objective: To review and update the literature regarding outcomes following surgical management of chronic, grade III posterolateral corner (PLC) injuries, with an emphasis on estimating failure rates based upon objective parameters in light of the 2019 expert consensus, while secondarily comparing the failure rates of anatomic versus non-anatomic reconstruction techniques.

Methods: A literature search was performed using the PubMed, Embase, MEDLINE, and Cochrane Library databases. Inclusion criteria consisted of level I-IV human clinical studies reporting subjective and objective outcomes in patients following surgical management for chronic (>6 weeks from injury) grade III PLC injuries, with a minimum two-year follow-up.