Each year, over 2.5 million people, most of them in developed countries, die from pneumonia [1]. Since many studies have proved pneumonia is successfully treatable when timely and correctly diagnosed, many of diagnosis aids have been developed, with AI-based methods achieving high accuracies [2]. However, currently, the usage of AI in pneumonia detection is limited, in particular, due to challenges in generalizing a locally achieved result. In this report, we propose a roadmap for creating and integrating a system that attempts to solve this challenge. We also address various technical, legal, ethical, and logistical issues, with a blueprint of possible solutions.
Deep Learning-Based Pneumonia Detection from Chest X-ray Images: A CNN Approach with Performance Analysis and Clinical Implications
Amity Institute of Bio Technology, Amity University Kolkata（阿米蒂大学加尔各答分校阿米蒂生物技术学院）；Dept of Computer Science, Heritage Institute of Technology, Kolkata（加尔各答遗产技术学院计算机科学系）；School of Engineering and Technology, Amity University Kolkata（阿米蒂大学加尔各答分校工程与技术学院）
Artificial Intelligence-driven Intelligent Wearable Systems: A full-stack Integration from Material Design to Personalized Interaction
The second hospital of Jilin University（吉林大学第二医院）；QMUL Digital Environment Research Institute（QMUL数字环境研究机构）；UCL Institute Of Health Informatics（UCL健康信息学研究所）
The Future of Intelligent Healthcare: A Systematic Analysis and Discussion on the Integration and Impact of Robots Using Large Language Models for Healthcare
Position: Intelligent Science Laboratory Requires the Integration of Cognitive and Embodied AI
University of Science and Technology of China（中国科学技术大学）；Nanjing University（南京大学）；University of New South Wales（新南威尔士大学）；Shanghai Jiao Tong University（上海交通大学）；Peking University（北京大学）；Harbin Institute of Technology（哈尔滨工业大学）；Tongji University（同济大学）；The University of Sydney, Oxford（悉尼大学，牛津）；Renmin University of China（中国人民大学）；Swiss Federal Institute of Technology Lausanne（苏黎世联邦理工学院）；Shanghai Institute of Ceramics, Chinese Academy of Sciences（中国科学院上海硅酸盐研究所）；Shanghai AI Laboratory（上海人工智能实验室）；Shanghai AI Laboratory & The Chinese University of Hong Kong（上海人工智能实验室 & 香港中文大学）
Image Segmentation with Large Language Models: A Survey with Perspectives for Intelligent Transportation Systems
Department of Computer Science, Iowa State University, Ames, IA, USA（Iowa State University）；Department of Civil, Construction and Environmental Engineering, Iowa State University, Ames, IA, USA（Iowa State University）
A "Wenlu" Brain System for Multimodal Cognition and Embodied Decision-Making: A Secure New Architecture for Deep Integration of Foundation Models and Domain Knowledge
College of Mechanical and Electrical Engineering, Shijiazhuang University（石家庄大学机械与电气工程学院）；School of Artificial Intelligence, Beijing University of Posts and Telecommunications（北京邮电大学人工智能学院）；The Key Laboratory of Agricultural Robotics Intelligent Perception in Shijiazhuang（石家庄农业机器人智能感知重点实验室）
TOM: A Development Platform For Wearable Intelligent Assistants
National University of Singapore（新加坡国立大学）；City University of Hong Kong（香港城市大学）；Smart Systems Institute（智能系统研究所）；School of Creative Media（创意媒体学院）；School of Computing（计算机学院）
Intelligent Reservoir Decision Support: An Integrated Framework Combining Large Language Models, Advanced Prompt Engineering, and Multimodal Data Fusion for Real-Time Petroleum Operations
Everglades University（埃弗格莱兹大学）；University of Campinas (UNICAMP)（坎皮纳斯州立大学）
