Author

Seunghwan Shin

Observed names: S.W. Shin, Shin, Seunghwan

Observed institution: Lunit (South Korea)

ORCID: 0000-0001-7397-9131

Observed ORCID: 0000-0001-7397-9131

OpenAlex ID: A5059287005

Artificial Intelligence–Powered Spatial Analysis of Tumor-Infiltrating Lymphocytes as Complementary Biomarker for Immune Checkpoint Inhibition in Non–Small-Cell Lung Cancer

2022 · Sehhoon Park, Chan-Young Ock, et al. · Journal of Clinical Oncology · 295

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Artificial intelligence–powered programmed death ligand 1 analyser reduces interobserver variation in tumour proportion score for non–small cell lung cancer with better prediction of immunotherapy response

2022 · Sangjoon Choi, Soo Ick Cho, et al. · European Journal of Cancer · 63

Deep Learning Analysis of CT Images Reveals High-Grade Pathological Features to Predict Survival in Lung Adenocarcinoma

2021 · Yeonu Choi, Jaehong Aum, et al. · Cancers · 22

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Discontinuation risk from adverse events: immunotherapy alone vs. combined with chemotherapy: a systematic review and network meta-analysis

2024 · Sangwon Shin, Jimin Moon, et al. · BMC Cancer · 10

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Artificial intelligence (AI)-powered HER2 quantification continuous score (QCS) and tumor microenvironment (TME) analysis in HER2-amplified metastatic colorectal cancer (mCRC) treated with pertuzumab plus trastuzumab.

2023 · Mitsuho Imai, Yoshiaki Nakamura, et al. · JCO Global Oncology · 4

Pathologic validation of artificial intelligence-powered prediction of combined positive score of PD-L1 immunohistochemistry in urothelial carcinoma.

2021 · Jeong Hwan Park, Kyu Sang Lee, et al. · Journal of Clinical Oncology · 3

Clinical performance of artificial intelligence-powered annotation of tumor cell PD-L1 expression for treatment of immune-checkpoint inhibitor (ICI) in advanced non-small cell lung cancer (NSCLC).

2021 · Hyojin Kim, Sangjoon Choi, et al. · Journal of Clinical Oncology · 3

1308 Artificial intelligence (AI)-powered immune phenotyping based on programmed death ligand 1 (PD-L1) immunohistochemistry (IHC) in triple negative breast cancer (TNBC)

2023 · Sangwon Shin, Gahee Park, et al. · Journal for ImmunoTherapy of Cancer · 1

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Artificial intelligence–powered tumor-infiltrating lymphocytes analyzer to reveal distinct immune landscapes in breast cancer by molecular subtype and HER2 score.

2023 · Seunghwan Shin, Soo Youn Cho, et al. · Journal of Clinical Oncology · 1

Abstract 553: Assessment of CNTN4 expression and its association with PD-L1 across 18 various cancers using an artificial intelligence-powered immunohistochemistry analyzer

2024 · Seunghwan Shin, Jimin Moon, et al. · Cancer Research

961 Tumor-infiltrating lymphocytes in tumor microenvironment assessed by artificial intelligence powered H&E image analyzer is correlated with immunomodulatory subtype of triple-negative breast cancer

2023 · Jimin Moon, Chang Ho Ahn, et al. · Journal for ImmunoTherapy of Cancer

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202 Spatial analysis of tumor-infiltrating lymphocytes in tumor microenvironment in non-small cell lung cancer patients who have resistance after EGFR tyrosine kinase inhibitors

2023 · Yeong Hak Bang, Chang Ho Ahn, et al. · Journal for ImmunoTherapy of Cancer

Exploring expression levels of HER2, HER3, MET, Claudin18.2, and MUC16 across 16 cancer types using an artificial intelligence-powered immunohistochemistry analyzer.

2023 · Seunghwan Shin, Soo Ick Cho, et al. · Journal of Clinical Oncology

Deep learning-based ensemble model using hematoxylin and eosin (H&E) whole slide images (WSIs) for the prediction of MET mutations in non-small cell lung cancer (NSCLC).

2023 · Yoon-La Choi, Sehhoon Park, et al. · Journal of Clinical Oncology

Predictive value of tumor-infiltrating lymphocyte (TIL) dynamics in the tumor microenvironment (TME) during preoperative chemoradiotherapy (CRT) on pathologic complete response (pCR) in microsatellite-stable (MSS) locally advanced rectal cancer (LARC).

2023 · Mitsuho Imai, Hideaki Bando, et al. · Journal of Clinical Oncology

Abstract 5392: Universal immunohistochemistry positivity classification of cancer cells across multiple cancer types and antibodies using artificial intelligence

2023 · Biagio Brattoli, Mohammad Mostafavi, et al. · Cancer Research

Abstract 5399: Deep learning-based ensemble model using H&E images for the prediction of KRAS G12C mutations in non-small cell lung cancer

2023 · Sehhoon Park, Jongchan Park, et al. · Cancer Research

Abstract 5389: Micron-resolution spatial analysis near the tumor-stromal border reveals a distinct density distribution of tumor-infiltrating lymphocytes and related genomic features

2023 · Sanghoon Song, Gahee Park, et al. · Cancer Research

Abstract 438: Deep learning based radiomic biomarker for predicting the presence of high-grade histologic patterns in lung adenocarcinoma

2021 · Yeonu Choi, Jaehong Aum, et al. · Cancer Research

541 ERBB3 promoter polymorphisms and mRNA expression associated with lung cancer risk in Korean lung cancer patients

2010 · J. Sung, L. Jin, et al. · European Journal of Cancer Supplements

Works count: 23

Citation count: 402

H-index: 4

I10-index: 4