The Mediating Effect of Social Problem-Solving Between Perfectionism and Subjective Well-Being.

This study examined the relationship between perfectionism and subjective well-being (SWB) and dimensions of social problem-solving ability. The Almost Perfect Scale-Revised (APS-R), Social problem-solving Inventory-Revised (SPSI-R) and Satisfaction with Life Scale (SWLS) were used to conduct a questionnaire survey of 202 Chinese adults. The results found that: (1) Subjective well-being was significantly negatively correlated with the discrepancy dimension of perfectionism and was also significantly negatively correlated with the negative problem orientation of social problem-solving. (2) The discrepancy dimension reflected in maladaptive perfectionism was significantly positively correlated with the negative aspects of social problem solving (Negative Problem Orientation, NPO; Impulsivity-Carelessness Style, ICS; and Avoidance Style, AS). (3) The negative problem orientation (NPO) dimension in SPSI-R, as a partial mediator, mediated the negative correlation between maladaptive perfectionism and subjective well-being. In conclusion, perfectionism and social problem-solving ability had different degrees of influence on the SWB of Chinese adults, and attention could be paid to dealing with discrepancy and how to reduce negative problem-solving tendency in education and clinical practice.

Rapid vessel segmentation and reconstruction of head and neck angiograms using 3D convolutional neural network.

The computed tomography angiography (CTA) postprocessing manually recognized by technologists is extremely labor intensive and error prone. We propose an artificial intelligence reconstruction system supported by an optimized physiological anatomical-based 3D convolutional neural network that can automatically achieve CTA reconstruction in healthcare services. This system is trained and tested with 18,766 head and neck CTA scans from 5 tertiary hospitals in China collected between June 2017 and November 2018. The overall reconstruction accuracy of the independent testing dataset is 0.931. It is clinically applicable due to its consistency with manually processed images, which achieves a qualification rate of 92.1%. This system reduces the time consumed from 14.22 ± 3.64 min to 4.94 ± 0.36 min, the number of clicks from 115.87 ± 25.9 to 4 and the labor force from 3 to 1 technologist after five months application. Thus, the system facilitates clinical workflows and provides an opportunity for clinical technologists to improve humanistic patient care.