BACKGROUND Emerging infectious diseases are a constant threat to the public’s health and health care systems around the world.Coronavirus disease 2019(COVID-2019),which was defined by the World Health Organization as...BACKGROUND Emerging infectious diseases are a constant threat to the public’s health and health care systems around the world.Coronavirus disease 2019(COVID-2019),which was defined by the World Health Organization as pandemic,has rapidly emerged as a global health threat.Outbreak evolution and prevention of international implications require substantial flexibility of frontline health care facilities in their response.AIM To explore the effect of the implementation and management strategy of prescreening triage in children during COVID-19.METHODS The standardized triage screening procedures included a standardized triage screening questionnaire,setup of pre-screening triage station,multi-point temperature monitoring,extensive screenings,and two-way protection.In order to ensure the implementation of the pre-screening triage,the prevention and control management strategies included training,emergency exercise,and staff protection.Statistical analysis was performed on the data from all the children hospitalized from January 20,2020 to March 20,2020 at solstice during the pandemic period.Data were obtained from questionnaires and electronic medical record systems.RESULTS A total of 17561 children,including 2652 who met the criteria for screening,192 suspected cases,and two confirmed cases without omission,were screened from January 20,2020 to March 20,2020 at solstice during the pandemic period.There was zero transmission of the infection to any medical staff.CONCLUSION The effective strategies for pre-screening triage have an essential role in the prevention and control of hospital infection.展开更多
Text-to-video retrieval(TVR)has made significant progress with advances in vision and language representation learning.Most existing methods use real-valued and hash-based embeddings to represent the video and text,al...Text-to-video retrieval(TVR)has made significant progress with advances in vision and language representation learning.Most existing methods use real-valued and hash-based embeddings to represent the video and text,allowing retrieval by computing their similarities.However,these methods are often inefficient for large volumes of video,and require significant storage and computing resources.In this work,we present a plug-and-play multi-modal multi-tagger-driven pre-screening framework,which pre-screens a substantial number of videos before applying any TVR algorithms,thereby efficiently reducing the search space of videos.We predict discrete semantic tags for video and text with our proposed multi-modal multi-tagger module,and then leverage an inverted index for space-efficient and fast tag matching to filter out irrelevant videos.To avoid filtering out relevant videos for text queries due to inconsistent tags,we utilize contrastive learning to align video and text embeddings,which are then fed into a shared multi-tag head.Extensive experimental results demonstrate that our proposed method significantly accelerates the TVR process while maintaining high retrieval accuracy on various TVR datasets.展开更多
文摘BACKGROUND Emerging infectious diseases are a constant threat to the public’s health and health care systems around the world.Coronavirus disease 2019(COVID-2019),which was defined by the World Health Organization as pandemic,has rapidly emerged as a global health threat.Outbreak evolution and prevention of international implications require substantial flexibility of frontline health care facilities in their response.AIM To explore the effect of the implementation and management strategy of prescreening triage in children during COVID-19.METHODS The standardized triage screening procedures included a standardized triage screening questionnaire,setup of pre-screening triage station,multi-point temperature monitoring,extensive screenings,and two-way protection.In order to ensure the implementation of the pre-screening triage,the prevention and control management strategies included training,emergency exercise,and staff protection.Statistical analysis was performed on the data from all the children hospitalized from January 20,2020 to March 20,2020 at solstice during the pandemic period.Data were obtained from questionnaires and electronic medical record systems.RESULTS A total of 17561 children,including 2652 who met the criteria for screening,192 suspected cases,and two confirmed cases without omission,were screened from January 20,2020 to March 20,2020 at solstice during the pandemic period.There was zero transmission of the infection to any medical staff.CONCLUSION The effective strategies for pre-screening triage have an essential role in the prevention and control of hospital infection.
基金supported by the National Natural Science Foundation of China(No.62476188)the Open Projects Program of the State Key Laboratory of Multimodal Artificial Intelligence Systems,and the Academy of Finland in the USSEE Project(No.345791).
文摘Text-to-video retrieval(TVR)has made significant progress with advances in vision and language representation learning.Most existing methods use real-valued and hash-based embeddings to represent the video and text,allowing retrieval by computing their similarities.However,these methods are often inefficient for large volumes of video,and require significant storage and computing resources.In this work,we present a plug-and-play multi-modal multi-tagger-driven pre-screening framework,which pre-screens a substantial number of videos before applying any TVR algorithms,thereby efficiently reducing the search space of videos.We predict discrete semantic tags for video and text with our proposed multi-modal multi-tagger module,and then leverage an inverted index for space-efficient and fast tag matching to filter out irrelevant videos.To avoid filtering out relevant videos for text queries due to inconsistent tags,we utilize contrastive learning to align video and text embeddings,which are then fed into a shared multi-tag head.Extensive experimental results demonstrate that our proposed method significantly accelerates the TVR process while maintaining high retrieval accuracy on various TVR datasets.
