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( Jungho Shin ),( Jin Ho Hwang ),( Sung Bin Park ),( Su Hyun Kim ) 대한신장학회 2023 Kidney Research and Clinical Practice Vol.42 No.4
Background: Microcirculatory dysfunction plays a critical role in sepsis-associated acute kidney injury (S-AKI) development; however, its impact on renal recovery remains uncertain. We investigated the association between cortical microcirculatory function assessed using contrast-enhanced ultrasonography (CEUS) and renal recovery after S-AKI needing renal replacement therapy (RRT). Methods: This retrospective study included 23 patients who underwent CEUS among those who underwent acute RRT for S-AKI. In addition, we acquired data from 17 healthy individuals and 18 patients with chronic kidney disease. Renal recovery was defined as sustained independence from RRT for at least 14 days. Results: Of the CEUS-derived parameters, rise time, time to peak, and fall time were longer in patients with S-AKI than in healthy individuals (p = 0.045, 0.01, and 0.096, respectively). Fourteen patients (60.9%) with S-AKI receiving RRT experienced renal recovery; and these patients had higher values of peak enhancement, wash-in area under the curve (AUC), wash-in perfusion index, and wash-out AUC than those without recovery (p = 0.03, 0.01, 0.03, and 0.046, respectively). We evaluated the receiver operating characteristic curve and found that the peak enhancement, wash-in AUC, wash-in perfusion index, and wash-out AUC of CEUS derivatives estimated the probability of renal recovery after S-AKI requiring RRT (p = 0.03, 0.01, 0.03, and 0.04, respectively). Conclusion: CEUS-assessed cortical microvascular perfusion may predict renal recovery following S-AKI that requires RRT. Further studies are essential to validate the clinical utility of microcirculatory parameters obtained from CEUS to estimate renal outcomes in various etiologies and severities of kidney disease.
Jungho Seo,Jin-Young Kim,Hyun-Woo Lim,Jin-Goo Park,Songjun Lee,Bonghoe Kim,Sungchae Jeon,Young Huh 한국물리학회 2010 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.57 No.1
A Si-PIN X-ray detector for digital x-ray imaging with single photon counting capability has been fabricated and characterized. It consists of an array of 32 × 32 pixels with an area of 80 × 80 µm2. An extrinsic gettering process was performed to reduce the leakage current by removing the impurities and defects from the X-ray detector’s Si substrate. Multiple guard-rings (MGRs) and metal filed plates (MFPs) techniques were adopted to reduce the leakage current and to improve the breakdown performance. The simulation verified that the breakdown voltage was improved with the MGRs and that the leakage current was significantly reduced with the MFPs. The electrical properties, such as the leakage current and the breakdown voltage, of the Si-PIN X-ray detector were characterized. The extrinsic gettering process played a significant role in reducing the leakage current, and a leakage current lower than 60 pA could be achieved at 100 Vdc.
Machine Learning Frameworks for Automated Software Testing Tools
Jungho Kim,Joung Woo Ryu,Hyun-Jeong Shin,Jin-Hee Song 한국콘텐츠학회(IJOC) 2017 International Journal of Contents Vol.13 No.1
Increased use of software and complexity of software functions, as well as shortened software quality evaluation periods, have increased the importance and necessity for automation of software testing. Automating software testing by using machine learning not only minimizes errors in manual testing, but also allows a speedier evaluation. Research on machine learning in automated software testing has so far focused on solving special problems with algorithms, leading to difficulties for the software developers and testers, in applying machine learning to software testing automation. This paper, proposes a new machine learning framework for software testing automation through related studies. To maximize the performance of software testing, we analyzed and categorized the machine learning algorithms applicable to each software test phase, including the diverse data that can be used in the algorithms. We believe that our framework allows software developers or testers to choose a machine learning algorithm suitable for their purpose.
Hyun-Jung Kwon,Chan-Sik Kim,Sungwon Kim,Syn Hae Yoon,Jungho Koh,Young Ki Kim,Seong-Soo Choi,Jin-Woo Shin,Doo-Hwan Kim 대한통증학회 2023 The Korean Journal of Pain Vol.36 No.3
Background: Recent attention has been directed towards fatty infiltration in the cervical extensor muscles for predicting clinical outcomes in several cervical disorders. This study aimed to investigate the potential association between fatty infiltration in the cervical multifidus and treatment response following cervical interlaminar epidural steroid injection (CIESI) in patients with cervical radicular pain. Methods: The data of patients with cervical radicular pain who received CIESIs between March 2021 and June 2022 were reviewed. A responder was defined as a patient with a numerical rating scale decrease of ≥ 50% from the baseline to three months after the procedure. The presence of fatty infiltration in the cervical multifidus was assessed, along with patient characteristics, and cervical spine disease severity. To assess cervical sarcopenia, fatty infiltration in the bilateral multifidus muscles was evaluated at the C5–C6 level using the Goutallier classification. Results: Among 275 included patients, 113 (41.1%) and 162 (58.9%) were classified as non-responders and responders, respectively. The age, severity of disc degeneration, and grade of cervical multifidus fatty degeneration were significantly lower in responders. Multivariate logistic regression analysis revealed that pre-procedural symptoms (radicular pain with neck pain, odd ratio [OR] = 0.527, P = 0.024) and high-grade cervical multifidus fatty degeneration (Goutallier grade 2.5–4, OR = 0.320, P = 0.005) were significantly associated with an unsuccessful response to CIESI. Conclusions: These results suggest high-grade cervical multifidus fatty infiltration is an independent predictor of poor response to CIESI in patients with cervical radicular pain.