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Infertility is a growing global health concern, with male factor infertility contributing to half of all cases. Semen analysis is crucial to infertility diagnostics. However, sperm morphology assessment, as a routine part of analysis, is still performed manually and is thus highly subjective. Here, a stacked ensemble of convolutional neural networks (CNNs) is presented for automated classification of human sperm head morphology. By combining traditional CNN models with modern residual and densely connected architectures using a multi‐class meta‐classifier, classification rate improvements of 2.7% (to 98.2%) and 2.3% (to 63.3%) on the HuSHeM and SCIAN‐MorphoSpermGS (SCIAN) datasets, respectively, are achieved. This considerable improvement in prediction performance is achieved as the meta‐classifier improves upon the individual classification rates of the base models by ≈8.5%. The ensembled deep learning model is a powerful step toward an automated sperm morphology analysis, providing new opportunities to standardize clinical practice and reduce treatment costs to improve patient treatment.

Multiple theoretical orientations propose a link between economic anxiety and racial attitudes. This article explores this link using three studies. The first study uses observational data from the 2016 CCES and ANES to determine whether or not anticipating a loss in income in the coming year is associated with negative racial affect. The second study uses observational data from the 2020 CCES to determine whether or not perceiving a greater risk of personal discrimination is associated with racial resentment. The last uses an original survey experiment from the 2020 CCES to gain insight into how priming intergroup competition shapes whites’ racial attitudes. These studies find an association between perceived economic threat and negative racial attitudes. However, the way respondents perceive economic threats seems to be largely shaped by partisan identification with Republicans perceiving greater levels of threat. They also suggest that material and symbolic threats may be mutually reinforcing. These findings support the claim that racial attitudes are deeply connected to economic anxieties and provide insight into how party identification shapes our psychology.

The purpose of this research is to explore medical students’ knowledge of and interest in telemedicine services in urban and rural communities. In the past, medical students reported feeling unprepared to use telemedicine and uninformed about laws regarding telemedicine usage following graduation. However, they also reported that telemedicine training is relevant and important for their future work.MethodsStudy participants included medical students taking part in a 2-day telemedicine education program in 2018 and 2019. The first day included a faculty seminar where students were introduced to telemedicine by experts in telemedicine innovations. The second day was a simulation (SIM) day where medical students completed a rotation at the Avera eCARE virtual hospital hub. A survey was given prior to the faculty seminar and readministered following the SIM day. Questions were asked about telemedicine knowledge, curriculum, and willingness to practice via telemedicine.ResultsChi-square analysis was used to look for associations pre/post by year. Both years showed an increase in favorable responses for questions to telemedicine training and education. For analyses by topic area, we created clusters of questions to build scores. T-tests were used to look for associations pre/post by year. The analysis resulted in three topic areas to build scores. Both years showed a significant increase in Rating of Overall Knowledge and Interest in Curriculum and Utilization. There was no significant difference in Willingness to Practice.ConclusionsResults show notable differences in how students perceive and understand telemedicine after structured exposure to telemedicine services. Furthermore, this study demonstrates students’ need for and interest in more telemedicine training opportunities in their curriculum. There was no significant difference in the willingness to practice in rural settings. Future studies may focus on how telemedicine training is perceived by those more willing to work in rural communities.

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