Hakje Yoo

Abstract To develop and validate a multimodal deep learning model that predicts treatment responses to intravitreal anti-vascular endothelial growth factor (anti-VEGF) injections in patients with diabetic macular oedema (DMO) by combining optical coherence tomography images and clinical data. This study included 107 DMO patients who received three consecutive anti-VEGF treatments.

Abstract Classification of fallers in Parkinson’s disease (PD) is challenging due to the heterogenous motor and non-motor symptoms. We developed a machine learning model integrating clinical and gait data to identify key clinical markers of faller status in PD. Of 468 participants, 396 with complete data were analyzed, with 298 assigned to training from one center and 98 to external validation from the other. Clinical assessments and GAITRite-derived gait metrics were obtained.

Abstract Accurate evaluation of liver fibrosis is essential for surgical planning in patients with hepatocellular carcinoma (HCC), as advanced fibrosis or cirrhosis can significantly alter resection strategy and postoperative outcomes. However, preoperative assessments using blood-based indices or imaging often fail to accurately reflect the true degree of fibrosis observed intraoperatively.