日期:
2020 年 — 2026 年
2020
2021
2022
2023
2024
2025
2026
影响因子:

Multi-modal molecular and spatial profiling reveals NNT as a prognostic biomarker in obesity-associated colorectal cancer.

多模态分子和空间分析揭示 NNT 是肥胖相关结直肠癌的预后生物标志物。

Park Sungjin, Lee Jae-Ghi, Park Ilkyu, Jeong Soyeon, An Jungsuk, Kim Jisup, Kang Myunghee, Nam Seungyoon, Kim Jung Ho

AI caption generation model for digital pathology of adenocarcinoma in endoscopic histopathology using multi-instance attention mechanisms

基于多实例注意力机制的内镜组织病理学腺癌数字病理学AI图像描述生成模型

Lee, Youngseop; Bai, Kyungah; Kim, Young Jae; Kim, Jisup; Kim, Kwang Gi

Elucidating prognostic significance of purine metabolism in colorectal cancer through integrating data from transcriptomic, immunohistochemical, and single-cell RNA sequencing analysis.

通过整合转录组学、免疫组织化学和单细胞 RNA 测序分析的数据,阐明嘌呤代谢在结直肠癌中的预后意义

Kim Sungyeon, Kang Myunghee, Jeong Soyeon, Kim Jisup, Kim Kyoung Oh, Lee Won-Suk, Baek Jeong-Heum, Kim Jung Ho, Nam Seungyoon

Multi-institutional validation of AI models for classifying urothelial neoplasms in digital pathology

数字病理学中用于分类尿路上皮肿瘤的人工智能模型的多机构验证

Park, Jun Young; Kim, Jisup; Kim, Young Jae; Kim, Sung Hyun; An, Chi Sung; Kim, Kwang Gi; Jung, Chan Kwon

Leveraging explainable AI and large-scale datasets for comprehensive classification of renal histologic types

利用可解释人工智能和大规模数据集对肾脏组织学类型进行全面分类

Moon, Seung Wan; Kim, Jisup; Kim, Young Jae; Kim, Sung Hyun; An, Chi Sung; Kim, Kwang Gi; Jung, Chan Kwon

Correction: Integrating E-cadherin expression levels with TNM staging for enhanced prognostic prediction in colorectal cancer patients

更正:将E-钙黏蛋白表达水平与TNM分期相结合,以提高结直肠癌患者的预后预测能力

Lee, Jae-Ghi; Park, Ilkyu; Lee, Hannah; Nam, Seungyoon; Kim, Jisup; Lee, Won-Suk; Kang, Myunghee; Kim, Jung Ho

Somatostatin receptor 2 (SSTR2) expression is associated with better clinical outcome and prognosis in rectal neuroendocrine tumors

生长抑素受体 2 (SSTR2) 表达与直肠神经内分泌肿瘤更好的临床结果和预后相关

Joo Young Kim, Jisup Kim, Yong-Il Kim, Dong-Hoon Yang, Changhoon Yoo, In Ja Park, Baek-Yeol Ryoo, Jin-Sook Ryu, Seung-Mo Hong

Prognostic significance of pyroptosis-associated molecules in endometrial cancer: a comprehensive immunohistochemical analysis

细胞焦亡相关分子在子宫内膜癌中的预后意义:一项全面的免疫组织化学分析

Ha, Seong-Chan; Park, Yeon Soo; Kim, Jisup

Predicting Mismatch Repair Deficiency Status in Endometrial Cancer through Multi-Resolution Ensemble Learning in Digital Pathology

利用数字病理学中的多分辨率集成学习预测子宫内膜癌中的错配修复缺陷状态

Whangbo, Jongwook; Lee, Young Seop; Kim, Young Jae; Kim, Jisup; Kim, Kwang Gi

A Comparative Study of Performance Between Federated Learning and Centralized Learning Using Pathological Image of Endometrial Cancer

基于子宫内膜癌病理图像的联邦学习与集中式学习性能比较研究

Yeom, Jong Chan; Kim, Jae Hoon; Kim, Young Jae; Kim, Jisup; Kim, Kwang Gi