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Ki-Sun Lee [CV-ENG]

Dentist & Programmer ( Specilized Mediacl AI & Deep Learning)

Tech Stacks

Work Experience

  • 2018-03 ~ Current Clinical Assistant Professor; Korea University Ansan Hospital, An-san, Gyungi do, South Korea
  • 2013-03 ~ 2018-02 Resident & Intern; Korea University Guro Hospital, Guro gu, Seoul, South Korea
  • 2001-07 ~ 2009-02 Programmer; Samsung SDS, Seoul, South Korea
  • 1996-03 ~ 1998-06 Lieutenant; ROTC office Republic of Korea Army, Gwang ju, South Korea

Education

  • 2017-09 ~ 2020-08 Ph.D - Biomedical Engineering, Seoul National University, Seoul, South Korea
  • 2009-05 ~ 2013-02 DDS(Doctor of Dental Surgery) & MDS(Master of Dental Surgery), Chosun University, Gwang ju, South Korea
  • 1992-03 ~ 1996-02 Bachelor of Engineering, Korea University, Seoul, South Korea

Research Project

  • 2022-2025 / National Research Foundation / A deep learning-based dental medical twin system research
  • 2019~2022 / National Research Foundation / Development of osteoporosis screening technology for panoramic images based on deep learning
  • 2020~2021 / Korea University Medical Center / Development of customized deep learning-based clinical decision support system (CDSS) algorithm
  • 2019~2020 / Korea University Medical Center / Optimal design based on finite element analysis for 3D printing implants and prostheses

Research Journals

  • Lee, K.-S.; Lee, E.; Choi, B.; Pyun, S.-B. Automatic Pharyngeal Phase Recognition in Untrimmed Videofluoroscopic Swallowing Study Using Transfer Learning with Deep Convolutional Neural Networks. Diagnostics 2021, 11, 300. https://doi.org/10.3390/diagnostics11020300
  • Lee, K.-S.; Kim, J.Y.; Jeon, E.-T.; Choi, W.S.; Kim, N.H.; Lee, K.Y. Evaluation of Scalability and Degree of Fine-Tuning of Deep Convolutional Neural Networks for COVID-19 Screening on Chest X-ray Images Using Explainable Deep-Learning Algorithm. J. Pers. Med. 2020, 10, 213. https://doi.org/10.3390/jpm10040213
  • Lee, K.-S.; Jung, S.-K.; Ryu, J.-J.; Shin, S.-W.; Choi, J.J.J.o.C.M. Evaluation of Transfer Learning with Deep Convolutional Neural Networks for Screening Osteoporosis in Dental Panoramic Radiographs. 2020, 9, 392. https://www.mdpi.com/2077-0383/9/2/392
  • Lee, K.-S.; Ryu, J.-J.; Jang, H.S.; Lee, D.-Y.; Jung, S.-K.J.A.S. Deep Convolutional Neural Networks Based Analysis of Cephalometric Radiographs for Differential Diagnosis of Orthognathic Surgery Indications. 2020, 10, 2124. https://doi.org/10.3390/app10062124
  • Lee, K.-S.; Shin, J.-H.; Kim, J.-E.; Kim, J.-H.; Lee, W.-C.; Shin, S.-W.; Lee, J.-Y.J.B.r.i. Biomechanical evaluation of a tooth restored with high performance polymer PEKK post-core system: A 3D finite element analysis. 2017, 2017.
  • Lee, K.-S.; Shin, S.-W.; Lee, S.-P.; Kim, J.-E.; Kim, J.-H.; Lee, J.-Y.; Lee, K.-S.; Shin, S.-W.; Lee, S.-P.; Kim, J.-E.J.I.J.o.P. Comparative Evaluation of a Four-Implant-Supported Polyetherketoneketone Framework Prosthesis: A Three-Dimensional Finite Element Analysis Based on Cone Beam Computed Tomography and Computer-Aided Design. 2017, 30.

Awards and Honors

  • 2021 Samsung Medical Center hosted Medical Artificial Intelligence Development Contest, 2nd place in teeth identification in panoramic x-ray
  • 2019 Seoul Asan Hospital hosted Medical Artificial Intelligence Development Contest, 2nd place in breast cancer analysis
  • 2019 Samsung Medical Center hosted Digital Health Hackathon Encouragement Award
  • 2019 NAVER Corp. hosted Open Source Contest Encouragement Award
  • 2018 Korean Associate of Digital Dentistry (KADD) hosted Regular Academic Conference Poster 1st Place
  • 2016 Korea University Medical Center Best Resident Award

Lecture/Presentation/Seminar

Personal Characteristics

  • Multitalented dentist with experience in Artificial Intelligent software development field.
  • Demonstrated excellent skills in Python and Google Deep Learning platform (Tensorflow)
  • Conducting various research projects in the medical field
  • Published a number of research papers related to medical artificial intelligence.
  • True team player with strengths in adaptability and accuracy.

이기선 [CV-KOR-Summary]

코딩하는 치과의사 (의료분야 인공지능 및 딥러닝)

Work Experience (경력)

  • 2018-03 ~ Current 고려대학교 안산병원/임상조교수겸 연구교수
  • 2013-03 ~ 2018-02 고려대학교 구로병원/인턴-레지던트(치과 전문의)
  • 2001-07 ~ 2009-02 삼성SDS 소프트웨어 엔지니어
  • 1996-03 ~ 1998-06 ROTC 장교 복무

Education (학력)

  • 2017-09 ~ 2020-08 서울대학교 의과대학 의공학박사
  • 2009-05 ~ 2013-02 조선대학교 치의학전문대학원 치의학전문석사
  • 1992-03 ~ 1996-02 고려대학교 공학박사

Research Project (연구프로젝트)

  • 2022~2025 / 한국연구재단 / 딥러닝 기반 치과용 메디컬 트윈시스템 개발
  • 2019~2022 / 한국연구재단 / 딥러닝 기반 치과용 파노라마 엑스레이를 이용한 골다공증 스크리닝 기술 개발
  • 2020~2021 / 고려대학교의료원 / 딥러닝 기반 맞춤형 임상의사결정지원시스템(CDSS) 기본 알고리즘 개발
  • 2019~2020 / 고려대학교의료원 / 3D 프린팅 임플란트 및 보철물 유한요소해석 기반 최적설계

Awards and Honors (수상경력)

  • 2021년 삼성서울병원 의료인공지능 개발 경진대회 개최, 파노라마 엑스레이 치아식별 부문 2위
  • 2019 서울아산병원 의료인공지능 개발 경진대회 유방암 분석 2위
  • 2019년 삼성서울병원 디지털헬스 해커톤 장려상
  • 2019 네이버(주) 오픈소스 공모전 장려상 개최
  • 2018년 한국디지털치과학회(KADD) 주최 정기학술대회 포스터 1위
  • 2016 고려대학교의료원 최우수 전공의 표창

저서

Updating...

강의/발표/세미나

언론홍보

교육 및 컨설팅 지원

  • 인공지능 관련 교육 및 컨설팅
  • 딥러닝 및 머신러닝을 통한 문제 해결 관련 교육 및 컨설팅
  • 딥러닝 및 머신러닝 모델 설계 및 제작과정 교육 및 컨설팅

ki-sun Lee's Projects

2019-6thd2cf-image-cluster icon 2019-6thd2cf-image-cluster

2019 Naver hosted open source contest 1st place in unsupervised image classification - 2019 Naver 주최 오픈소스 경진대회 이미지 분류 부분 1위

cadrres icon cadrres

Cancer Drug Response prediction using a Recommender System

cat-dog-classification-flask-app icon cat-dog-classification-flask-app

We successfully built a deep neural network model by implementing Convolutional Neural Network (CNN) to classify dog and cat images with very high accuracy 97.32 %. In addition, we also built a Flask application so user can upload their images and classify easily.

cnn_car_detector icon cnn_car_detector

Training a deep-learning classifier for aerial top view detection of vehicles.

cs231n_17_kor_sub icon cs231n_17_kor_sub

CS231N 2017 video subtitles translation project for Korean Computer Science students

cv-ko icon cv-ko

CV (Curriculum Vitae - Korean)

cvat icon cvat

Annotate better with CVAT, the industry-leading data engine for machine learning. Used and trusted by teams at any scale, for data of any scale.

data_science_bowl_2018 icon data_science_bowl_2018

My 5th place (out of 816 teams) solution to The 2018 Data Science Bowl organized by Booz Allen Hamilton

detectron2-pipeline icon detectron2-pipeline

Modular image processing pipeline using OpenCV and Python generators powered by Detectron2.

handtracking icon handtracking

Building a Real-time Hand-Detector using Neural Networks (SSD) on Tensorflow

hdbscan icon hdbscan

A high performance implementation of HDBSCAN clustering.

image-segmentation icon image-segmentation

Mask R-CNN, FPN, LinkNet, PSPNet and UNet with multiple backbone architectures support readily available

image-similarity-clustering icon image-similarity-clustering

This project allows images to be automatically grouped into like clusters using a combination of machine learning techniques.

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