Yosep Chong

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Associate Professor

Uijeongbu Saint Mary's Hospital

South Korea

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About

Yosep Chong is an Associate Professor at Uijeongbu Saint Mary's Hospital in South Korea. His research areas focus on artificial intelligence applications in cytopathology and histopathology, including developing models for image classification and automated grading systems. He has published articles on topics such as humanoid artificial consciousness, digital cytopathology, and the integration of AI solutions into clinical workflows.

Recent Grants

Grant: Close

암진단에서 면역염색 데이터를 이용한 인공지능 진단추정기술

Open Date: 2016-11-01

Close Date: 2017-10-01

Articles (24)

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2022

Collaborators (19)

Jin Hwi Kim

The Catholic University of Korea

SOUTH KOREA

Yosep Chong

Research Interests

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About

Recent Grants

Articles (24)

Large-Scale Dermatopathology Dataset for Lesion Segmentation: Model Development and Analysis

Humanoid artificial consciousness designed with Large Language Model based on psychoanalysis and personality theory

National quality assurance program using digital cytopathology: a 5-year digital transformation experience by the Korean Society for Cytopathology

CLASS-M: Adaptive stain separation-based contrastive learning with pseudo-labeling for histopathological image classification

Commercially Available Artificial Intelligence Solutions for Gynaecologic Cytology Screening and Their Integration Into Clinical Workflow

A Nuclei-Focused Strategy for Automated Histopathology Grading of Renal Cell Carcinoma

Integration of Digital Cytology in Quality Assurance Programs for Cytopathology

Comparative analysis of Ki-67 labeling index morphometry using deep learning, conventional image analysis, and manual counting

Artificial-Intelligence-Assisted Detection of Metastatic Colorectal Cancer Cells in Ascitic Fluid

Response to comment on “A stepwise approach to fine needle aspiration cytology of lymph nodes”

CAWM: Class-Aware Weight Map for Improved Semi-Supervised Nuclei Segmentation

Development of CytoAcademy: a new web- and mobile-based E-learning platform for cytopathologists and cytotechnologists by the Korean Society for Cytopathology in the post-pandemic era

A stepwise approach to fine needle aspiration cytology of lymph nodes

Uterine Cervical Angioleiomyoma Mimicking Squamous Cell Carcinoma

Deep Learning-Based Computational Cytopathologic Diagnosis of Metastatic Breast Carcinoma in Pleural Fluid

Validation of a Machine Learning Expert Supporting System, ImmunoGenius, Using Immunohistochemistry Results of 3000 Patients with Lymphoid Neoplasms

Two Cases of Lymph Node Metastasis Found in Differentiated, Small-Sized Gastric Adenocarcinomas: Did Tumor Budding Play a Critical Role?

Diagnostic proficiency test using digital cytopathology and comparative assessment of whole slide images of cytologic samples for quality assurance program in Korea

Current status of cytopathology practice in Korea: impact of the coronavirus pandemic on cytopathology practice

Development of quality assurance program for digital pathology by the Korean Society of Pathologists

Recent Application of Artificial Intelligence in Non-Gynecological Cancer Cytopathology: A Systematic Review

Intratumoral Budding in Pretreatment Biopsies, among Tumor Microenvironmental Components, Can Predict Prognosis and Neoadjuvant Therapy Response in Colorectal Adenocarcinoma

Recent Applications of Artificial Intelligence from Histopathologic Image-Based Prediction of Microsatellite Instability in Solid Cancers: A Systematic Review

Current Trend of Artificial Intelligence Patents in Digital Pathology: A Systematic Evaluation of the Patent Landscape

Collaborators (19)

Jin Hwi Kim

Soo Jin Jung

Hee Jeong Cha

Seung-Won Jung

Sung Hak Lee

GYEONGSIN PARK

Uiju Cho

Dong Wook Kang

So Young Lee

Won Mo Jang

Hyun Joo Choi

Kyung Jin Seo

Tolga Tasdizen

HYE SEUNG HAN

Yoonjin Kwak

Young Sub Lee

Kwangil Yim

Soon Auck Hong

Ji Yun Jeong

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