Soyun Kim
Korea University · Medicine
About the Lab
Professor Soyun Kim's research lab specializes in nuclear medicine and molecular imaging, with a focus on improving cancer diagnosis, prognosis, and treatment planning. The lab investigates the role of metabolic imaging—particularly 18F-FDG PET— in predicting outcomes for head and neck squamous cell carcinomas, including oropharyngeal and salivary gland cancers. Key research directions include identifying biomarkers such as HPV and p16 status, evaluating tumor metabolic activity, and understanding late recurrence patterns in head and neck cancers. The lab also explores quantitative imaging parameters to enhance detection of occult primary tumors and refine treatment strategies based on individualized risk assessment.
Research Overview
Research Output Trend
Figures are computed from collected data and may differ slightly.
Selected Papers
15If TTP is delayed significantly (dTTP > or =3.2 s), the FAIR with intermediate or short TI showed underestimation of perfusion in the same area with delay in TTP.
UNLABELLED: High tumor uptake of (18)F-FDG is associated with an unfavorable outcome in cancer patients. We evaluated pretreatment (18)F-FDG uptake as guidance for the primary treatment modality in patients with squamous cell carcinoma (SCC) of the oropharynx. METHODS: Fifty-two consecutive patients with newly diagnosed resectable SCC of the oropharynx underwent (18)F-FDG PET before treatment. Primary treatment modalities consisted of surgical resection plus radiotherapy (RT) (surgery group, n=3
OBJECTIVES: Lymph node (LN) metastasis of oral cavity squamous cell carcinoma (OSCC) is associated with survival outcomes. However, the relationship between different metastatic nodal factors and treatment outcomes requires further elucidation. This study examined nodal factors predictive of recurrence and survival in patients with OSCC. METHODS: This prospective observational study included 157 patients with OSCC who underwent surgery between 2010 and 2015. Clinicopathological and follow-up inf
OBJECTIVES: Recurrence in the late post-treatment period is relatively common in salivary gland cancer (SGC), but risk factors and survival associated with late recurrence have been rarely studied. We investigated the incidence and risk factors of SGC recurrence >5 years after treatment and associated survival. DESIGN: A retrospective cohort study. SETTING: University hospital. PARTICIPANTS: A total of 240 patients with previously untreated SGC who underwent definitive treatment. MAIN OUTCOME ME
OBJECTIVES: Due to relatively high (18) F-fluorodeoxyglucose accumulation in the tonsillar region, the detection of occult tonsillar cancers by (18) F-fluorodeoxyglucose positron emission tomography/computerised tomography remains controversial. Therefore, we assessed the usefulness of quantitative tonsil (18) F-fluorodeoxyglucose uptake in identifying occult tonsillar squamous cell carcinoma. DESIGN: A case-control study of retrospective cohorts. SETTING: University Teaching Hospital. MAIN OUTC
BACKGROUND: Next-generation sequencing (NGS) has become widely available but molecular profiling-guided therapy (MGT) had not been well established in the real world due to lack of available therapies and expertise to match treatment. Our study was designed to test the feasibility of a nationwide platform of NGS-guided MGT recommended by a central molecular tumor board (cMTB) for metastatic solid tumors. PATIENTS AND METHODS: Patients with advanced or metastatic solid tumors with available NGS r
OBJECTIVES: Cervical lymph node metastases from an unknown primary tumour are a heterogeneous disease entity with various clinical features. There are many controversies regarding treatment methods and treatment response predictions. Therefore, we examined the prognostic significance of biomarkers in patients with cervical metastasis of unknown primary tumour. DESIGN: A molecular study of retrospective cohorts. SETTING: University teaching hospital. MAIN OUTCOME MEASURES: Metastatic cervical lym
본 연구는 자연어처리 기반 인공지능이 발달장애인을 위한 보조공학으로 기능할 능성을 제시하며, 향후 연구 및 기술 개발의 방향을 모색한다. 인공지능 기술이 발전을 거듭하면서, 다양한 장애 보조공학으로 활용되고 있다. 여러 인공지능 기술 가운데 자연어처리는 특히 발달장애인의 학습과 의사소통을 지원하는 데 유용할 수 있다. 본 연구는 자연어처리 기반 보조공학이 발달장애인에게 제공할 수 있는 세 가지 주요 이점을 논의한다. 첫째, 텍스트 분석의 방법을 통하여 저렴하면서도 신속한 진단/평가 도구로 활용될 수 있다. 둘째, 발달장애인의 일상적인 생활과 학습 과정에서 지속적인 지원 도구로 기능한다. 셋째, 언어적 패턴 분석을 통해 연구자의 분석 정확도를 향상하고, 데이터 기반의 객관적인 연구 환경을 조성할 수 있다. 넷째, 특수교육 현장에서 교사의 보조자로 기능하며, 발달장애 학생들의 사회적 상호작용을 촉진할 수 있다. 종합하자면, 자연어처리 환경은 멀티모달 인공지능에 대비하여 발달장애인의 조기
Research Areas
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