Search Results - "Jo, Yong‐Yeon"

Predicting intraoperative hypotension using deep learning with waveforms of arterial blood pressure, electroencephalogram, and electrocardiogram: Retrospective study by Jo, Yong-Yeon, Jang, Jong-Hwan, Kwon, Joon-myoung, Lee, Hyung-Chul, Jung, Chul-Woo, Byun, Seonjeong, Jeong, Han-Gil

“…To develop deep learning models for predicting Interoperative hypotension (IOH) using waveforms from arterial blood pressure (ABP), electrocardiogram (ECG),…”
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Impact of image compression on deep learning-based mammogram classification by Jo, Yong-Yeon, Choi, Young Sang, Park, Hyun Woo, Lee, Jae Hyeok, Jung, Hyojung, Kim, Hyo-Eun, Ko, Kyounglan, Lee, Chan Wha, Cha, Hyo Soung, Hwangbo, Yul

“…Image compression is used in several clinical organizations to help address the overhead associated with medical imaging. These methods reduce file size by…”
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Artificial intelligence for detecting electrolyte imbalance using electrocardiography by Kwon, Joon‐myoung, Jung, Min‐Seung, Kim, Kyung‐Hee, Jo, Yong‐Yeon, Shin, Jae‐Hyun, Cho, Yong‐Hyeon, Lee, Yoon‐Ji, Ban, Jang‐Hyeon, Jeon, Ki‐Hyun, Lee, Soo Youn, Park, Jinsik, Oh, Byung‐Hee

“…Introduction The detection and monitoring of electrolyte imbalance is essential for appropriate management of many metabolic diseases; however, there is no…”
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Artificial Intelligence-Enhanced Smartwatch ECG for Heart Failure-Reduced Ejection Fraction Detection by Generating 12-Lead ECG by Kwon, Joon-Myoung, Jo, Yong-Yeon, Lee, Soo Youn, Kang, Seonmi, Lim, Seon-Yu, Lee, Min Sung, Kim, Kyung-Hee

“…We developed and validated an artificial intelligence (AI)-enabled smartwatch ECG to detect heart failure-reduced ejection fraction (HFrEF). This was a cohort…”
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Reduction of time‐releasing ammonia from polymer foam using low acidic polymers by Cho, Mi Yeon, Kim, Tae Min, Kim, Yeon Wook, Shin, Min‐Seung, Jo, Yong Yeon, Lee, Kangtaek, Kim, Bo‐Hyun, Lee, Sunjong

“…Polymer foams are used in everyday life for industrial and household applications. However, the time‐releasing ammonia is environmentally harmful that becomes…”
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Efficient processing of recommendation algorithms on a single-machine-based graph engine by Jo, Yong-Yeon, Jang, Myung-Hwan, Kim, Sang-Wook, Han, Kyungsik

“…The wide use of recommendation systems includes more users and items in system operations, leading to a significant increase in the size of related datasets…”
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ECGT2T: Towards Synthesizing Twelve-Lead Electrocardiograms from Two Asynchronous Leads by Jo, Yong-Yeon, Choi, Young Sang, Jang, Jong-Hwan, Kwon, Joon-Myoung

“…Electrocardiograms (ECGs) are a non-invasive measurement used to observe the condition of the heart. Modern wearable devices can record ECGs, but typically…”
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Identifying Atrial Fibrillation With Sinus Rhythm Electrocardiogram in Embolic Stroke of Undetermined Source: A Validation Study With Insertable Cardiac Monitors by Jeon, Ki-Hyun, Jang, Jong-Hwan, Kang, Sora, Lee, Hak Seung, Lee, Min Sung, Son, Jeong Min, Jo, Yong-Yeon, Park, Tae Jun, Oh, Il-Young, Kwon, Joon-myoung, Lee, Ji Hyun

“…BACKGROUND AND OBJECTIVESParoxysmal atrial fibrillation (AF) is a major potential cause of embolic stroke of undetermined source (ESUS). However, identifying…”
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Deep-learning model for screening sepsis using electrocardiography by Kwon, Joon-myoung, Lee, Ye Rang, Jung, Min-Seung, Lee, Yoon-Ji, Jo, Yong-Yeon, Kang, Da-Young, Lee, Soo Youn, Cho, Yong-Hyeon, Shin, Jae-Hyun, Ban, Jang-Hyeon, Kim, Kyung-Hee

“…Abstract Background Sepsis is a life-threatening organ dysfunction and a major healthcare burden worldwide. Although sepsis is a medical emergency that…”
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Prediction of Prolonged Length of Hospital Stay After Cancer Surgery Using Machine Learning on Electronic Health Records: Retrospective Cross-sectional Study by Jo, Yong-Yeon, Han, JaiHong, Park, Hyun Woo, Jung, Hyojung, Lee, Jae Dong, Jung, Jipmin, Cha, Hyo Soung, Sohn, Dae Kyung, Hwangbo, Yul

“…Postoperative length of stay is a key indicator in the management of medical resources and an indirect predictor of the incidence of surgical complications and…”
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The uFLIP benchmark revisited for evaluating SSDs by Kang, Yoonsuk, Jo, Yong-Yeon, Cha, Jaehhyuk, Kim, Sang-Wook, Shin, Young Kyun

“…Summary Solid‐state drives (SSDs) provide higher bandwidth and lower access latency than hard disk drives (HDDs) and thus have been rapidly replacing HDDs. SSD…”
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Explainable artificial intelligence to detect atrial fibrillation using electrocardiogram by Jo, Yong-Yeon, Cho, Younghoon, Lee, Soo Youn, Kwon, Joon-myoung, Kim, Kyung-Hee, Jeon, Ki-Hyun, Cho, Soohyun, Park, Jinsik, Oh, Byung-Hee

“…Early detection and intervention of atrial fibrillation (AF) is a cornerstone for effective treatment and prevention of mortality. Diverse deep learning models…”
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Artificial intelligence using electrocardiography: strengths and pitfalls by Kwon, Joon-myoung, Jo, Yong-Yeon, Lee, Soo Youn, Kim, Kyung-Hee

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An artificial intelligence electrocardiogram analysis for detecting cardiomyopathy in the peripartum period by Lee, Yeji, Choi, Byungjin, Lee, Min Sung, Jin, Uram, Yoon, Seokyoung, Jo, Yong-Yeon, Kwon, Joon-myoung

“…Peripartum cardiomyopathy (PPCM) is a fatal maternal complication, with left ventricular systolic dysfunction (LVSD; Left ventricular ejection fraction 45% or…”
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A Data Layout with Good Data Locality for Single-Machine based Graph Engines by Jo, Yong-Yeon, Jang, Myung-Hwan, Kim, Sang-Wook, Park, Sunju

“…Graph engines have been used in many applications to handle big graphs efficiently. The majority of the research to improve their performance has focused…”
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FORESEE: An Effective and Efficient Framework for Estimating the Execution Times of IO Traces on the SSD by Kang, Yoonsuk, Jo, Yong-Yeon, Cha, Jaehyuk, Bae, Wan D., Lee, Wonjun, Kim, Sang-Wook

“…If we had the performance information of every application on every SSD, it would be very beneficial to both SSD users and SSD manufacturers. For SSD users,…”
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AI-enabled ECG index for predicting left ventricular dysfunction in patients with ST-segment elevation myocardial infarction by Jeon, Ki-Hyun, Lee, Hak Seung, Kang, Sora, Jang, Jong-Hwan, Jo, Yong-Yeon, Son, Jeong Min, Lee, Min Sung, Kwon, Joon-myoung, Kwun, Ju-Seung, Cho, Hyoung-Won, Kang, Si-Hyuck, Lee, Wonjae, Yoon, Chang-Hwan, Suh, Jung-Won, Youn, Tae-Jin, Chae, In-Ho

“…Electrocardiogram (ECG) changes after primary percutaneous coronary intervention (PCI) in ST-segment elevation myocardial infarction (STEMI) patients are…”
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Detection and classification of arrhythmia using an explainable deep learning model by Jo, Yong-Yeon, Kwon, Joon-myoung, Jeon, Ki-Hyun, Cho, Yong-Hyeon, Shin, Jae-Hyun, Lee, Yoon-Ji, Jung, Min-Seung, Ban, Jang-Hyeon, Kim, Kyung-Hee, Lee, Soo Youn, Park, Jinsik, Oh, Byung-Hee

“…Early detection and intervention is the cornerstone for appropriate treatment of arrhythmia and prevention of complications and mortality. Although diverse…”
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Artificial intelligence assessment for early detection and prediction of renal impairment using electrocardiography by Kwon, Joon-myoung, Kim, Kyung-Hee, Jo, Yong-Yeon, Jung, Min-Seung, Cho, Yong-Hyeon, Shin, Jae-Hyun, Lee, Yoon-Ji, Ban, Jang-Hyeon, Lee, Soo Youn, Park, Jinsik, Oh, Byung-Hee

“…Purpose Although renal failure is a major healthcare burden globally and the cornerstone for preventing its irreversible progression is an early diagnosis, an…”
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Optimization of GPU-based Sparse Matrix Multiplication for Large Sparse Networks by Lee, Jeongmyung, Kang, Seokwon, Yu, Yongseung, Jo, Yong-Yeon, Kim, Sang-Wook, Park, Yongjun

“…Sparse matrix multiplication (spGEMM) is widely used to analyze the sparse network data, and extract important information based on matrix representation. As…”
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