The field of health monitoring is moving towards more integrated and autonomous systems that leverage multimodal data and large language models to provide enhanced patient care. Recent developments have focused on creating systems that can continuously collect and analyze vital signs, detect anomalies, and provide personalized health guidance. These systems often incorporate natural language processing components, allowing for more intuitive human-machine interaction and enabling healthcare workers to access real-time patient information through user-friendly interfaces. The use of multimodal data, including sensor data, visual data, and patient-reported information, is becoming increasingly important in these systems. Additionally, there is a growing trend towards developing digital health applications that can bridge the healthcare divide for underserved populations, such as those with limited access to digital healthcare or those who speak languages that are not well-supported by existing platforms. Noteworthy papers in this area include: REMONI, an autonomous remote health monitoring system that integrates wearable devices, multimodal large language models, and the Internet of Things. AmarDoctor, a multilingual voice-interactive digital health app designed to provide comprehensive patient triage and AI-driven clinical decision support for Bengali speakers.