Balanoposthitis(BP),a common male genitalia inflammation,is managed by clinicians from different specialties,including urology,pediatrics,dermatology,and venereology.Due to this diverse array of clinicians involved,th...Balanoposthitis(BP),a common male genitalia inflammation,is managed by clinicians from different specialties,including urology,pediatrics,dermatology,and venereology.Due to this diverse array of clinicians involved,there exists a lack of consistent,evidence-based recommendations for BP.The development of the consensus engaged 19 representative hospitals and it adhered to rigorous protocols,encompassing international registration(IPGRP-2021CN003)and the application of evidence grading criteria and recommendation standards[Appendix S1,Supplementary File,http://links.lww.com/CM9/C42].Over the period from December 2020 to October 2022,consensus on 12 clinical issues was reached through comprehensive evidence searches and two iterations of Delphi surveys[Supplementary File,http://links.lww.com/CM9/C42].展开更多
Role–event videos are rich in information but challenging to be understood at the story level.The social roles and behavior patterns of characters largely depend on the interactions among characters and the backgroun...Role–event videos are rich in information but challenging to be understood at the story level.The social roles and behavior patterns of characters largely depend on the interactions among characters and the background events.Understanding them requires analysis of the video contents for a long duration,which is beyond the ability of current algorithms designed for analyzing short-time dynamics.In this paper,we propose In Social Net,an interactive video analytics tool for analyzing the contents of role–event videos.It automatically and dynamically constructs social networks from role–event videos making use of face and expression recognition,and provides a visual interface for interactive analysis of video contents.Together with social network analysis at the back end,In Social Net supports users to investigate characters,their relationships,social roles,factions,and events in the input video.We conduct case studies to demonstrate the effectiveness of In Social Net in assisting the harvest of rich information from role–event videos.We believe the current prototype implementation can be extended to applications beyond movie analysis,e.g.,social psychology experiments to help understand crowd social behaviors.展开更多
基金National Natural Science Foundation of China(No.82273538)Public Health Research and Development Program of the Shenyang Science and Technology Bureau(No.22-321-33-12)National Key R&D Program of China(No.2023YFC2508200)
文摘Balanoposthitis(BP),a common male genitalia inflammation,is managed by clinicians from different specialties,including urology,pediatrics,dermatology,and venereology.Due to this diverse array of clinicians involved,there exists a lack of consistent,evidence-based recommendations for BP.The development of the consensus engaged 19 representative hospitals and it adhered to rigorous protocols,encompassing international registration(IPGRP-2021CN003)and the application of evidence grading criteria and recommendation standards[Appendix S1,Supplementary File,http://links.lww.com/CM9/C42].Over the period from December 2020 to October 2022,consensus on 12 clinical issues was reached through comprehensive evidence searches and two iterations of Delphi surveys[Supplementary File,http://links.lww.com/CM9/C42].
基金supported by National Natural Science Foundation of China(No.61802278).
文摘Role–event videos are rich in information but challenging to be understood at the story level.The social roles and behavior patterns of characters largely depend on the interactions among characters and the background events.Understanding them requires analysis of the video contents for a long duration,which is beyond the ability of current algorithms designed for analyzing short-time dynamics.In this paper,we propose In Social Net,an interactive video analytics tool for analyzing the contents of role–event videos.It automatically and dynamically constructs social networks from role–event videos making use of face and expression recognition,and provides a visual interface for interactive analysis of video contents.Together with social network analysis at the back end,In Social Net supports users to investigate characters,their relationships,social roles,factions,and events in the input video.We conduct case studies to demonstrate the effectiveness of In Social Net in assisting the harvest of rich information from role–event videos.We believe the current prototype implementation can be extended to applications beyond movie analysis,e.g.,social psychology experiments to help understand crowd social behaviors.
