2023/03/04 by Qinghua He, Wanyu Li, He, Qinghua +13
Medicine · #FOS: Electrical engineering #Image and Video Processing (eess.IV) #Liver Disease Diagnosis and Treatment #Liver Disease and Transplantation #Neonatal Health and Biochemistry #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2303.02277
openalex publication_date 2023/03/04 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
We present the development of SpeCamX, a mobile application that transforms any unmodified smartphone into a powerful multispectral imager capable of capturing multispectral information. Our application includes an augmented bilirubinometer, enabling accurate prediction of blood bilirubin levels (BBL). In a clinical study involving 320 patients with liver diseases, we used SpeCamX to image the bulbar conjunctiva region, and we employed a hybrid machine learning prediction model to predict BBL. We observed a high correlation with blood test results, demonstrating the efficacy of our approach. Furthermore, we compared our method, which uses spectrally augmented learning (SAL), with traditional learning based on RGB photographs (RGBL), and our results clearly indicate that SpeCamX outperforms RGBL in terms of prediction accuracy, efficiency, and stability. This study highlights the potential of SpeCamX to improve the prediction of bio-chromophores, and its ability to transform an ordinary smartphone into a powerful medical tool without the need for additional investments or expertise. This makes it suitable for widespread use, particularly in areas where medical resources are scarce.