Dataset for Journal Artificial Intelligence (AI)-Based Early Diagnosis System for Hyaline Membrane Disease Severity in Premature Infants

This outlines a collaborative research plan between the National Research and Innovation Agency (BRIN) and Sam Ratulangi University (UNSRAT) to develop an AI-based product for the early diagnosis of Hyaline Membrane Disease (HMD), named AI-HMD. Infant Mortality Rate (IMR) in Indonesia, particularly among premature infants, remains a critical challenge in achieving Sustainable Development Goal (SDG) 3. One of the primary causes of IMR is Hyaline Membrane Disease (HMD), which requires early and accurate diagnosis. Unfortunately, the limited distribution of medical specialists, such as neonatologists and radiologists, leads to diagnostic delays in many regions. This proposal advocates for the development of AI-HMD, an Artificial Intelligence-based early diagnostic system for HMD that integrates neonatal chest X-ray image analysis with patient clinical data. The system is built using deep learning Convolutional Neural Network (CNN) approaches alongside multimodal AI algorithms to enhance diagnostic accuracy and adaptability within the Indonesian context. Ultimately, this system is expected to serve as an affordable, precise neonatal diagnostic solution ready for integration into Neonatal Intensive Care Unit (NICU) services across Indonesia