Artificial intelligence(AI)is increasingly recognized as a transformative force in the field of solid organ transplantation.From enhancing donor-recipient matching to predicting clinical risks and tailoring immunosupp...Artificial intelligence(AI)is increasingly recognized as a transformative force in the field of solid organ transplantation.From enhancing donor-recipient matching to predicting clinical risks and tailoring immunosuppressive therapy,AI has the potential to improve both operational efficiency and patient outcomes.Despite these advancements,the perspectives of transplant professionals-those at the forefront of critical decision-making-remain insufficiently explored.To address this gap,this study utilizes a multi-round electronic Delphi approach to gather and analyses insights from global experts involved in organ transplantation.Participants are invited to complete structured surveys capturing demographic data,professional roles,institutional practices,and prior exposure to AI technologies.The survey also explores perceptions of AI’s potential benefits.Quantitative responses are analyzed using descriptive statistics,while open-ended qualitative responses undergo thematic analysis.Preliminary findings indicate a generally positive outlook on AI’s role in enhancing transplantation processes,particularly in areas such as donor matching and post-operative care.These mixed views reflect both optimism and caution among professionals tasked with integrating new technologies into high-stakes clinical workflows.By capturing a wide range of expert opinions,the findings will inform future policy development,regulatory considerations,and institutional readiness frameworks for the integration of AI into organ transplantation.展开更多
介绍了在以Delphi 7.0作为前台开发工具,SQL Server 2000作为后台服务器开发数据库过程中,JPEG格式图像数据存储和读取显示的两种方法,即内存流法和路径链接法。使用内存流法可以减少磁盘操作,更易于数据库的维护和管理,还可提高数据的...介绍了在以Delphi 7.0作为前台开发工具,SQL Server 2000作为后台服务器开发数据库过程中,JPEG格式图像数据存储和读取显示的两种方法,即内存流法和路径链接法。使用内存流法可以减少磁盘操作,更易于数据库的维护和管理,还可提高数据的安全性;使用路径链接法加快了数据库的检索速度和图像数据传输速度,极大地扩展了图像数据库的信息量。这两种方法对于图像数据库的应用开发有着重要意义。展开更多
文摘Artificial intelligence(AI)is increasingly recognized as a transformative force in the field of solid organ transplantation.From enhancing donor-recipient matching to predicting clinical risks and tailoring immunosuppressive therapy,AI has the potential to improve both operational efficiency and patient outcomes.Despite these advancements,the perspectives of transplant professionals-those at the forefront of critical decision-making-remain insufficiently explored.To address this gap,this study utilizes a multi-round electronic Delphi approach to gather and analyses insights from global experts involved in organ transplantation.Participants are invited to complete structured surveys capturing demographic data,professional roles,institutional practices,and prior exposure to AI technologies.The survey also explores perceptions of AI’s potential benefits.Quantitative responses are analyzed using descriptive statistics,while open-ended qualitative responses undergo thematic analysis.Preliminary findings indicate a generally positive outlook on AI’s role in enhancing transplantation processes,particularly in areas such as donor matching and post-operative care.These mixed views reflect both optimism and caution among professionals tasked with integrating new technologies into high-stakes clinical workflows.By capturing a wide range of expert opinions,the findings will inform future policy development,regulatory considerations,and institutional readiness frameworks for the integration of AI into organ transplantation.
文摘介绍了在以Delphi 7.0作为前台开发工具,SQL Server 2000作为后台服务器开发数据库过程中,JPEG格式图像数据存储和读取显示的两种方法,即内存流法和路径链接法。使用内存流法可以减少磁盘操作,更易于数据库的维护和管理,还可提高数据的安全性;使用路径链接法加快了数据库的检索速度和图像数据传输速度,极大地扩展了图像数据库的信息量。这两种方法对于图像数据库的应用开发有着重要意义。
