AI-based Smart Detection of Hormonal Changes in Women using Pixel Intensity Analysis

Female hormonal monitoring needs exact diagnostic capabilities to both detect and track fertility conditions and hormonal problems and pregnancy conditions. An artificial intelligence-based detection system for hormones uses pixel intensities from lateral flow test strips to produce results according to project research findings. Pixel intensities of two essential lines are measured by the system through ROI segmentation in lateral flow test kit images. Exact results become possible through the diagnostic system's ability to extract detailed segmentations while also reading pixel intensities. Reliability testing of the developed system achieved accurate results from its examination of chosen dataset materials. The identified results demonstrate the possibility of integrating this method as an automated diagnostic tool with pregnancy kits and hormonal tests to expand medical care options. The discovered information contributes to future AI-driven diagnostic instruments in healthcare alongside evidence of their capacity for expansion into both self-testing by patients and disease monitoring systems.