February 2024 in “Frontiers in physics” This study developed a model for detecting sparse hair clusters using enhanced object detection neural networks and medical images, which accurately identifies and counts sparse hair clusters with greater accuracy and efficiency than existing methods.
April 2026 in “Scientific Reports” In this study, the proposed MSF-VMDNet, combining dual encoder networks with a multi-frequency domain mechanism, significantly outperformed existing methods in segmenting skin cancer tissues from histological slide images, achieving high accuracy with an MIoU of 95.37% and a Dice coefficient of 95.11%.
February 2026 in “Pharmaceuticals” This study introduced the KRDQN predictive framework, which outperformed existing methods in predicting adverse drug reactions and provided interpretable insights into drug mechanisms, aiding pharmacovigilance and clinical decision-making.
7 citations
,
May 2021 in “Applied sciences” This study investigated various proteins as eco-friendly hair perming agents for Asian hair and found that bovine serum albumin and keratin achieved perming results comparable to commercial products, while also increasing hair moisture, indicating a protective effect during heat styling.
1 citations
,
December 2025 in “Scientific Reports” In this study, researchers developed a predictive model for the onset of alopecia areata by analyzing six datasets to identify key feature genes and employing various machine learning algorithms, ultimately finding the XGBoost model most effective for clinical application.