User profiles for Yu-Seop Kim
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The application of a deep learning system developed to reduce the time for RT-PCR in COVID-19 detection
Reducing the time to diagnose COVID-19 helps to manage insufficient isolation-bed
resources and adequately accommodate critically ill patients. There is currently no alternative …
resources and adequately accommodate critically ill patients. There is currently no alternative …
Prediction of stroke outcome using natural language processing-based machine learning of radiology report of brain MRI
Brain magnetic resonance imaging (MRI) is useful for predicting the outcome of patients
with acute ischemic stroke (AIS). Although deep learning (DL) using brain MRI with certain …
with acute ischemic stroke (AIS). Although deep learning (DL) using brain MRI with certain …
Portable triboelectric-electromagnetic hybrid biomechanical energy harvester for driving various functional light-emitting diodes with a wide range of wavelengths
As the application range of light-emitting diode (LED) has rapidly expanded in various fields
and functional LED-implanted electronic devices have deeply permeated human daily lives, …
and functional LED-implanted electronic devices have deeply permeated human daily lives, …
Comparison of named entity recognition methodologies in biomedical documents
Background Biomedical named entity recognition (Bio-NER) is a fundamental task in handling
biomedical text terms, such as RNA, protein, cell type, cell line, and DNA. Bio-NER is one …
biomedical text terms, such as RNA, protein, cell type, cell line, and DNA. Bio-NER is one …
Named entity recognition using word embedding as a feature
This study applied word embedding to feature for named entity recognition (NER) training,
and used CRF as a learning algorithm. Named entities are phrases that contain the names of …
and used CRF as a learning algorithm. Named entities are phrases that contain the names of …
Deep learning based prediction of prognosis in nonmetastatic clear cell renal cell carcinoma
…, JM Choi, YS Jeong, YS Kim, WK Lee, C Kim - Scientific reports, 2021 - nature.com
Survival analyses for malignancies, including renal cell carcinoma (RCC), have primarily
been conducted using the Cox proportional hazards (CPH) model. We compared the random …
been conducted using the Cox proportional hazards (CPH) model. We compared the random …
Convolutional neural network and language model-based sequential CT Image captioning for intracerebral hemorrhage
GY Kim, BD Oh, C Kim, YS Kim - Applied Sciences, 2023 - mdpi.com
Intracerebral hemorrhage is a severe problem where more than one-third of patients die
within a month. In diagnosing intracranial hemorrhage, neuroimaging examinations are …
within a month. In diagnosing intracranial hemorrhage, neuroimaging examinations are …
Prediction of persistent hemodynamic depression after carotid angioplasty and stenting using artificial neural network model
JP Jeon, C Kim, BD Oh, SJ Kim, YS Kim - Clinical neurology and …, 2018 - Elsevier
Objectives To assess and compare predictive factors for persistent hemodynamic depression
(PHD) after carotid artery angioplasty and stenting (CAS) using artificial neural network (…
(PHD) after carotid artery angioplasty and stenting (CAS) using artificial neural network (…
[PDF][PDF] Detection of Defect Inside Duct Using Recurrent Neural Networks.
Prestressed concrete (PSC) box-girder bridges are grouted after inserting a tendon in the
duct in order to protect the tendon from the risk of corrosion. However, because of the small …
duct in order to protect the tendon from the risk of corrosion. However, because of the small …
Inter-sentence segmentation of youtube subtitles using long-short term memory (LSTM)
Recently, with the development of Speech to Text, which converts voice to text, and machine
translation, technologies for simultaneously translating the captions of video into other …
translation, technologies for simultaneously translating the captions of video into other …