Yonsei University · Medicine
Professor Dong Wook Kim's research lab focuses on advancing clinical prediction and diagnostic methodologies through innovative applications of machine learning and biomedical imaging. The lab specializes in developing deep learning-based survival models for oncology, particularly in oral squamous cell carcinoma, while also exploring personalized treatment strategies such as the ketogenic diet in neurological conditions. Additionally, the lab investigates medical imaging techniques for accurate pediatric kidney volume assessment and examines the genetic and molecular underpinnings of cancers like small cell lung cancer. Their work bridges computational science with clinical practice to improve patient outcomes.
Figures are computed from collected data and may differ slightly.
The Cox proportional hazards model commonly used to evaluate prognostic variables in survival of cancer patients may be too simplistic to properly predict a cancer patient's outcome since it assumes that the outcome is a linear combination of covariates. In this retrospective study including 255 patients suitable for analysis who underwent surgical treatment in our department from 2000 to 2017, we applied a deep learning-based survival prediction method in oral squamous cell carcinoma (SCC) pati
These observations suggest that initial fasting and fluid restriction are not essential for the KD and that the tolerability of this treatment may be improved. These data support our intention to conduct a formal, prospective, randomized trial comparing 2 forms of the KD.
In a rapidly increasing Korean population, the lower socioeconomic groups as well as individuals with DM were significantly more likely to present with periodontitis.
Abstract: The discovery of recurrent alterations in genes encoding transcription regulators and chromatin modifiers is one of the most important recent developments in the study of the small cell lung cancer (SCLC) genome. With advances in models and analytical methods, the field of SCLC biology has seen remarkable progress in understanding the deregulated transcription networks linked to the tumor development and malignant progression. This review will discuss recent discoveries on the roles of
The unpredictable change in the rotational axis of the tibia and its broad variability after rotating platform mobile bearing TKA may provide a warning against the use of a fixed landmark for establishing tibial rotational alignment.
In this study, we aimed to develop a new automated method for kidney volume measurement in children using ultrasonography (US) with image pre-processing and hybrid learning and to formulate an equation to calculate the expected kidney volume. The volumes of 282 kidneys (141 subjects, <19 years old) with normal function and structure were measured using US. The volumes of 58 kidneys in 29 subjects who underwent US and computed tomography (CT) were determined by image segmentation and compared to
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