A deep learning based hybrid model for maternal health risk detection and multifaceted emotion analysis in social networks - Geethanjali, R.; Valarmathi, A. (Zielona Góra: Uniwersytet Zielonogórski)
In the field of public health, accurately identifying maternal health risks through social network data is both vital and challenging due to the complexities of multimodal sentiment analysis. Our study addresses this challenge by introducing the maternal health risk factor detection using deep learning approach (MHRFD-DLA), a novel framework that integrates convolutional neural networks, long short-term memory networks, and attention mechanisms. This approach enhances sentiment analysis and risk detection in maternal health, with the focus on critical areas such as prenatal care, mental health, and nutrition.
Keywords: multifaceted emotion analysis; social networks; maternal health risk factor detection; deep learning; hybrid approach