Frontiers in Intelligent Medicine & Health
Focusing on Intelligent Healthcare · Driving AI + Health Innovation
"Smart healthcare is reshaping the global health ecosystem. FIMH is committed to building a cross-disciplinary platform for medicine, AI, and health management, promoting data-driven precision diagnosis and equitable health. We invite global researchers to share cutting-edge achievements in intelligent medical systems, clinical decision support, and digital health."
— Prof. Li Min Editor-in-Chief
Authors: 王华, 张敏, John Smith
This study developed a deep learning model integrating CT, MRI, and clinical text data, achieving 96.7% accuracy in early lung cancer screening, significantly improving diagnostic efficiency.
Authors: 陈思, 赵宇, Maria Gonzalez
This paper analyzes the clinical value of wearable devices in hypertension and diabetes management, and proposes a federated learning-based data privacy protection framework, balancing utility and security.
Authors: 刘洋, 周杰, Ahmed Hassan
This study evaluates GPT-4 performance in clinical documentation generation, identifies hallucination, bias, and privacy risks, and proposes a human-machine collaborative review mechanism.
Authors: 张丽, 王伟, Kevin Zhang
This paper proposes a hybrid recommendation algorithm integrating medical knowledge graphs and collaborative filtering, achieving high accuracy and interpretability in chronic disease health management.
Authors: 李强, 王芳, 陈敏
This review systematically examines federated learning applications in cross-institutional medical data collaboration, analyzing latest breakthroughs in model performance, communication efficiency, and privacy protection.
