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Akademický článek

Integrated clinical and genomic models using machine-learning methods to predict the efficacy of paclitaxel-based chemotherapy in patients with advanced gastric cancer

Autor: Yonghwa Choi, Jangwoo Lee, Keewon Shin, Ji Won Lee, Ju Won Kim, Soohyeon Lee, Yoon Ji Choi, Kyong Hwa Park, Jwa Hoon Kim

Publikováno v: BMC Cancer, Vol 24, Iss 1, Pp 1-9 (2024)

Abstract Background Paclitaxel is commonly used as a second-line therapy for advanced gastric cancer (AGC). The decision to proceed with second-line chemotherapy and select an appropriate regimen is critical for vulnerable patients with AGC progressi

Externí odkaz: https://doaj.org/article/75ad08ec2c4640feb610b5b597e9b92f

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Akademický článek

Diagnosis of osteoporotic vertebral compression fractures and fracture level detection using multitask learning with U-Net in lumbar spine lateral radiographs

Autor: Seung Min Ryu, Soyoung Lee, Miso Jang, Jung-Min Koh, Sung Jin Bae, Seong Gyu Jegal, Keewon Shin, Namkug Kim

Publikováno v: Computational and Structural Biotechnology Journal, Vol 21, Iss , Pp 3452-3458 (2023)

Recent studies of automatic diagnosis of vertebral compression fractures (VCFs) using deep learning mainly focus on segmentation and vertebral level detection in lumbar spine lateral radiographs (LSLRs). Herein, we developed a model for simultaneous

Externí odkaz: https://doaj.org/article/d78bb8ed18144f85b6851f26918f07ea

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Akademický článek

Diagnosis of Scoliosis Using Chest Radiographs with a Semi-Supervised Generative Adversarial Network

Autor: Woojin Lee, Keewon Shin, Junsoo Lee, Seung-Jin Yoo, Min A Yoon, Yo Won Choi, Gil-Sun Hong, Namkug Kim, Sanghyun Paik

Publikováno v: 대한영상의학회지, Vol 83, Iss 6, Pp 1298-1311 (2022)

Purpose To develop and validate a deep learning-based screening tool for the early diagnosis of scoliosis using chest radiographs with a semi-supervised generative adversarial network (GAN). Materials and Methods Using a semi-supervised learning fr

Externí odkaz: https://doaj.org/article/e4c1be80b8b64163a4e00c76f1918301

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Akademický článek

Screening of adolescent idiopathic scoliosis using generative adversarial network (GAN) inversion method in chest radiographs.

Autor: Jun Soo Lee, Keewon Shin, Seung Min Ryu, Seong Gyu Jegal, Woojin Lee, Min A Yoon, Gil-Sun Hong, Sanghyun Paik, Namkug Kim

Publikováno v: PLoS ONE, Vol 18, Iss 5, p e0285489 (2023)

ObjectiveConventional computer-aided diagnosis using convolutional neural networks (CNN) has limitations in detecting sensitive changes and determining accurate decision boundaries in spectral and structural diseases such as scoliosis. We devised a n

Externí odkaz: https://doaj.org/article/6b6c41cf3bb541159468a663419d6ee9

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Akademický článek

Convolutional Neural Network Technology in Endoscopic Imaging: Artificial Intelligence for Endoscopy

Autor: Joonmyeong Choi, Keewon Shin, Jinhoon Jung, Hyun-Jin Bae, Do Hoon Kim, Jeong-Sik Byeon, Namku Kim

Publikováno v: Clinical Endoscopy, Vol 53, Iss 2, Pp 117-126 (2020)

Recently, significant improvements have been made in artificial intelligence. The artificial neural network was introduced in the 1950s. However, because of the low computing power and insufficient datasets available at that time, artificial neural n

Externí odkaz: https://doaj.org/article/8010c34373f7451aa6388b45833d752f

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Akademický článek

Can deep learning reduce the time and effort required for manual segmentation in 3D reconstruction of MRI in rotator cuff tears?

Autor: Hyojune Kim, Keewon Shin, Hoyeon Kim, Eui-Sup Lee, Seok Won Chung, Kyoung Hwan Koh, Namkug Kim

Publikováno v: PLoS ONE, Vol 17, Iss 10, p e0274075 (2022)

Background/purposeThe use of MRI as a diagnostic tool has gained popularity in the field of orthopedics. Although 3-dimensional (3D) MRI offers more intuitive visualization and can better facilitate treatment planning than 2-dimensional (2D) MRI, man

Externí odkaz: https://doaj.org/article/a9be8e27752f42dab37df253c1669a0f

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Akademický článek

Deep Learning in Medical Imaging

Autor: Mingyu Kim, Jihye Yun, Yongwon Cho, Keewon Shin, Ryoungwoo Jang, Hyun-jin Bae, Namkug Kim

Publikováno v: Neurospine, Vol 16, Iss 4, Pp 657-668 (2019)

The artificial neural network (ANN), one of the machine learning (ML) algorithms, inspired by the human brain system, was developed by connecting layers with artificial neurons. However, due to the low computing power and insufficient learnable data,

Externí odkaz: https://doaj.org/article/f36bb58d19cf4ad3b917e9187b7dc9cf

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