Monoclonal antibody Y01 prevents tauopathy progression induced by lysine 280-acetylated tau in cell and mouse models by Song, Ha-Lim, Kim, Na-Young, Park, Jaewan, Kim, Meong Il, Jeon, Yu-Na, Lee, Se-Jong, Cho, Kwangmin, Shim, Young-Lim, Lee, Kyoung-Hye, Mun, Yeon-Seon, Song, Jung-A, Kim, Min-Seok, Pack, Chan-Gi, Jung, Minkyo, Jang, Hyemin, Na, Duk L, Hong, Minsun, Kim, Dong-Hou, Yoon, Seung-Yong

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The inclination of threading dislocation in chemical vapor deposition-grown single-crystal diamond analyzed by synchrotron white beam X-ray topography by Jang, Hyemin, Na, Moonkyong, Bahng, Wook, Lee, Jung Woo

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Staging and quantification of florbetaben PET images using machine learning: impact of predicted regional cortical tracer uptake and amyloid stage on clinical outcomes by Kim, Jun Pyo, Kim, Jeonghun, Kim, Yeshin, Moon, Seung Hwan, Park, Yu Hyun, Yoo, Sole, Jang, Hyemin, Kim, Hee Jin, Na, Duk L., Seo, Sang Won, Seong, Joon-Kyung

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Author Correction: Concordance in detecting amyloid positivity between 18F-florbetaben and 18F-flutemetamol amyloid PET using quantitative and qualitative assessments by Cho, Soo Hyun, Choe, Yeong Sim, Kim, Young Ju, Lee, Byungju, Kim, Hee Jin, Jang, Hyemin, Kim, Jun Pyo, Jung, Young Hee, Kim, Soo-Jong, Kim, Byeong C., Farrar, Gill, Na, Duk L., Moon, Seung Hwan, Seo, Sang Won

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Feasibility of MRI for the evaluation of interosseous ligament vertical segment via subtalar arthroscopy correlation: comparison of 2D and 3D MR images by Jung, Hong-Geun, Moon, Sung Gyu, Yoon, Deuk Young, Jang, Hyemin, Kang, Ji Hee

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Prediction of amyloid β PET positivity using machine learning in patients with suspected cerebral amyloid angiopathy markers by Jung, Young Hee, Lee, Hyejoo, Kim, Hee Jin, Na, Duk L., Han, Hyun Jeong, Jang, Hyemin, Seo, Sang Won

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Enhancing foveal avascular zone analysis for Alzheimer’s diagnosis with AI segmentation and machine learning using multiple radiomic features by Yoon, Je Moon, Lim, Chae Yeon, Noh, Hoon, Nam, Seung Wan, Jun, Sung Yeon, Kim, Min Ji, Song, Mi Yeon, Jang, Hyemin, Kim, Hee Jin, Seo, Sang Won, Na, Duk L., Chung, Myung Jin, Ham, Don-Il, Kim, Kyungsu

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Cerebrospinal fluid from Alzheimer’s disease patients as an optimal formulation for therapeutic application of mesenchymal stem cells in Alzheimer’s disease by Lee, Jeongmin, Kwon, Soo Jin, Kim, Jang Hoon, Jang, Hyemin, Lee, Na Kyung, Hwang, Jung Won, Kim, Jong Hwa, Chang, Jong Wook, Na, Duk L.

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Bee Venom Activates the Nrf2/HO-1 and TrkB/CREB/BDNF Pathways in Neuronal Cell Responses against Oxidative Stress Induced by Aβ1–42 by Nguyen, Cong Duc, Yoo, Jaehee, Hwang, Sun-Young, Cho, Sung-Young, Kim, Myeonghun, Jang, Hyemin, No, Kyoung Ok, Shin, Jeong Cheol, Kim, Jae-Hong, Lee, Gihyun

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Clinical application of sparse canonical correlation analysis to detect genetic associations with cortical thickness in Alzheimer's disease by Kim, Bo-Hyun, Seo, Sang Won, Park, Yu Hyun, Kim, JiHyun, Kim, Hee Jin, Jang, Hyemin, Yun, Jihwan, Kim, Mansu, Kim, Jun Pyo

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Linguistic, visuospatial, and kinematic writing characteristics in cognitively impaired patients with beta-amyloid deposition by An, Seo Kyung, Jang, Hyemin, Kim, Hee Jin, Yoon, Ji Hye

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Disease progression modeling of Alzheimer’s disease according to education level by Kim, Ko Woon, Woo, Sook Young, Kim, Seonwoo, Jang, Hyemin, Kim, Yeshin, Cho, Soo Hyun, Kim, Si Eun, Kim, Seung Joo, Shin, Byoung-Soo, Kim, Hee Jin, Na, Duk L., Seo, Sang Won

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Relationships between educational attainment, hypertension, and amyloid negative subcortical vascular dementia: The brain-battering hypothesis by Hwangbo, Song, Kim, Young Ju, Park, Yu Hyun, Kim, Hee Jin, Jang, Hyemin, Seo, Sang Won

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Effects of risk factors on the development and mortality of early- and late-onset dementia: an 11-year longitudinal nationwide population-based cohort study in South Korea by Chun, Min Young, Chae, Wonjeong, Seo, Sang Won, Jang, Hyemin, Yun, Jihwan, Na, Duk L, Kang, Dongwoo, Lee, Jungkuk, Hammers, Dustin B, Apostolova, Liana G, Jang, Sung-In, Kim, Hee Jin

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Harmonisation of PET imaging features with different amyloid ligands using machine learning-based classifier by Kang, Sung Hoon, Kim, Jeonghun, Kim, Jun Pyo, Cho, Soo Hyun, Choe, Yeong Sim, Jang, Hyemin, Kim, Hee Jin, Koh, Seong-Beom, Na, Duk L., Seong, Joon-Kyung, Seo, Sang Won

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Application of an amyloid and tau classification system in subcortical vascular cognitive impairment patients by Jang, Hyemin, Kim, Hee Jin, Park, Seongbeom, Park, Yu Hyun, Choe, Yeongsim, Cho, Hanna, Lyoo, Chul Hyoung, Yoon, Uicheul, Lee, Jin San, Kim, Yeshin, Kim, Seung Joo, Kim, Jun Pyo, Jung, Young Hee, Ryu, Young Hoon, Choi, Jae Yong, Moon, Seung Hwan, Seong, Joon-Kyung, DeCarli, Charles, Weiner, Michael W., Lockhart, Samuel N., Cho, Soo Hyun, Na, Duk L., Seo, Sang Won

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Deep learning model for individualized trajectory prediction of clinical outcomes in mild cognitive impairment by Jung, Wonsik, Kim, Si Eun, Kim, Jun Pyo, Jang, Hyemin, Park, Chae Jung, Kim, Hee Jin, Na, Duk L, Seo, Sang Won, Suk, Heung-Il

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Predicting conversion of brain β-amyloid positivity in amyloid-negative individuals by Park, Chae Jung, Seo, Younghoon, Choe, Yeong Sim, Jang, Hyemin, Lee, Hyejoo, Kim, Jun Pyo

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Correlations between Gray Matter and White Matter Degeneration in Pure Alzheimer’s Disease, Pure Subcortical Vascular Dementia, and Mixed Dementia by Jang, Hyemin, Kwon, Hunki, Yang, Jin-Ju, Hong, Jinwoo, Kim, Yeshin, Kim, Ko Woon, Lee, Jin San, Jang, Young Kyoung, Kim, Sung Tae, Lee, Kyung Han, Lee, Jae Hong, Na, Duk L., Seo, Sang Won, Kim, Hee Jin, Lee, Jong-Min

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Performance of the plasma Aβ42/Aβ40 ratio, measured with a novel HPLC-MS/MS method, as a biomarker of amyloid PET status in a DPUK-KOREAN cohort by Jang, Hyemin, Kim, Ji Sun, Lee, Hye Joo, Kim, Chi-Hun, Na, Duk L, Kim, Hee Jin, Allué, José Antonio, Sarasa, Leticia, Castillo, Sergio, Pesini, Pedro, Gallacher, John, Seo, Sang Won

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