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Article ; Online: Applications of Artificial Intelligence in Mammography from a Development and Validation Perspective

Ki Hwan Kim / Sang Hyup Lee

대한영상의학회지, Vol 82, Iss 1, Pp 12-

2021 Volume 28

Abstract: Mammography is the primary imaging modality for breast cancer detection; however, a high level of expertise is needed for its interpretation. To overcome this difficulty, artificial intelligence (AI) algorithms for breast cancer detection have recently ... ...

Abstract	Mammography is the primary imaging modality for breast cancer detection; however, a high level of expertise is needed for its interpretation. To overcome this difficulty, artificial intelligence (AI) algorithms for breast cancer detection have recently been investigated. In this review, we describe the characteristics of AI algorithms compared to conventional computer-aided diagnosis software and share our thoughts on the best methods to develop and validate the algorithms. Additionally, several AI algorithms have introduced for triaging screening mammograms, breast density assessment, and prediction of breast cancer risk have been introduced. Finally, we emphasize the need for interest and guidance from radiologists regarding AI research in mammography, considering the possibility that AI will be introduced shortly into clinical practice.
Keywords	mammography ; artificial intelligence ; breast cancer ; Medical physics. Medical radiology. Nuclear medicine ; R895-920
Subject code	006
Language	English
Publishing date	2021-01-01T00:00:00Z
Publisher	The Korean Society of Radiology
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Prediction of Remaining Life for Bridge Decks Considering Deterioration Factors and Propose of Prioritization Process for Bridge Deck Maintenance

Ki Hwan Kim / Moon S. Nam / Hoon Hee Hwang / Ki Yong Ann

Sustainability, Vol 12, Iss 10625, p

2020 Volume 10625

Abstract: Aged highway bridges have become substantially prevalent in recent years. Moreover, combined deterioration, caused by using deicing agents in winter, has led to increased bridge maintenance costs. Accordingly, to extend the service life of bridge decks, ... ...

Abstract	Aged highway bridges have become substantially prevalent in recent years. Moreover, combined deterioration, caused by using deicing agents in winter, has led to increased bridge maintenance costs. Accordingly, to extend the service life of bridge decks, this study utilized actual inspection data and major deterioration factors to derive the remaining service life of bridge decks. Based on this study, the following three factors are selected: deicing agent exposure grade, pavement condition state, and surface improvement status. Performance degradation curves were derived for 11 cases that considered the representative three deterioration factors, and the performance degradation of decks was examined for each deterioration factor. Additionally, a process to determine maintenance priorities, using the current condition of highway bridges and the deterioration factors of individual bridges, was proposed. The maintenance demand was predicted based on the end of deck life, which indicated that the demand for deck replacement will sharply increase in 15 years, and that the decks of more than 2000 bridges will reach the end of life in 40 years. Furthermore, this paper proposes a process for prioritizing the maintenance of approximately 9000 highway bridge decks. By applying the prioritization process for bridge deck maintenance to the bridge deck, not only can the life of the bridge deck be extended, but also environmental pollution can be minimized. Additionally, an optimizing design for bridge decks, by considering the remaining life and deterioration factors, can be possible. Therefore, it is expected that the sustainability of the bridge deck can be accomplished.
Keywords	bridge decks ; maintenance ; deterioration factors ; remaining service life ; Environmental effects of industries and plants ; TD194-195 ; Renewable energy sources ; TJ807-830 ; Environmental sciences ; GE1-350
Subject code	690
Language	English
Publishing date	2020-12-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Detection of fast oscillating magnetic fields using dynamic multiple TR imaging and Fourier analysis.

Ki Hwan Kim / Hyo-Im Heo / Sung-Hong Park

PLoS ONE, Vol 13, Iss 1, p e

2018 Volume 0189916

Abstract: Neuronal oscillations produce oscillating magnetic fields. There have been trials to detect neuronal oscillations using MRI, but the detectability in in vivo is still in debate. Major obstacles to detecting neuronal oscillations are (i) weak amplitudes, ( ...

Abstract	Neuronal oscillations produce oscillating magnetic fields. There have been trials to detect neuronal oscillations using MRI, but the detectability in in vivo is still in debate. Major obstacles to detecting neuronal oscillations are (i) weak amplitudes, (ii) fast oscillations, which are faster than MRI temporal resolution, and (iii) random frequencies and on/off intervals. In this study, we proposed a new approach for direct detection of weak and fast oscillating magnetic fields. The approach consists of (i) dynamic acquisitions using multiple times to repeats (TRs) and (ii) an expanded frequency spectral analysis. Gradient echo echo-planar imaging was used to test the feasibility of the proposed approach with a phantom generating oscillating magnetic fields with various frequencies and amplitudes and random on/off intervals. The results showed that the proposed approach could precisely detect the weak and fast oscillating magnetic fields with random frequencies and on/off intervals. Complex and phase spectra showed reliable signals, while no meaningful signals were observed in magnitude spectra. A two-TR approach provided an absolute frequency spectrum above Nyquist sampling frequency pixel by pixel with no a priori target frequency information. The proposed dynamic multiple-TR imaging and Fourier analysis are promising for direct detection of neuronal oscillations and potentially applicable to any pulse sequences.
Keywords	Medicine ; R ; Science ; Q
Subject code	621
Language	English
Publishing date	2018-01-01T00:00:00Z
Publisher	Public Library of Science (PLoS)
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Clinical characteristics and cytokine profiles of children with acute lower respiratory tract infections caused by human rhinovirus.

Jong Gyun Ahn / Dong Soo Kim / Ki Hwan Kim

PLoS ONE, Vol 13, Iss 7, p e

2018 Volume 0198624

Abstract: The clinical profile of human rhinovirus (HRV) with regard to lower respiratory infections remains unclear. We analyzed the clinical features and cytokine responses of HRV isolates in children with respiratory infections. Quantitative analysis and ... ...

Abstract	The clinical profile of human rhinovirus (HRV) with regard to lower respiratory infections remains unclear. We analyzed the clinical features and cytokine responses of HRV isolates in children with respiratory infections. Quantitative analysis and genotyping of the HRV-positive samples from 601 nasopharyngeal aspirates (NPAs) were performed using VP4/VP2 sequencing. To compare T-helper1 (Th1) type (IFN-γ, TNF-α) and Th2 type (IL-4, IL-10) cytokine responses between HRV-A, B and C, the levels of the four cytokines were measured. The HRV-positive children had shorter fever duration (P = 0.018), and higher frequencies of chest retraction (P = 0.002) and wheezing (P = 0.022) than did the HRV-negative group. HRV-A was identified in 55 cases (58.5%), HRV-B in 8 (8.5%), and HRV-C in 31 (33.0%). There were no significant differences in the clinical data or NPA cytokines levels between patients with HRV-A and HRV-C infections. HRV is an important pathogen of the lower respiratory tract in young children. HRV-A and HRV-C are the dominant species that cause respiratory difficulty in young children.
Keywords	Medicine ; R ; Science ; Q
Subject code	610
Language	English
Publishing date	2018-01-01T00:00:00Z
Publisher	Public Library of Science (PLoS)
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Mammographically occult breast cancers detected with AI-based diagnosis supporting software

Hee Jeong Kim / Hak Hee Kim / Ki Hwan Kim / Woo Jung Choi / Eun Young Chae / Hee Jung Shin / Joo Hee Cha / Woo Hyun Shim

Insights into Imaging, Vol 13, Iss 1, Pp 1-

clinical and histopathologic characteristics

2022 Volume 11

Abstract: Abstract Background To demonstrate the value of an artificial intelligence (AI) software in the detection of mammographically occult breast cancers and to determine the clinicopathologic patterns of the cancers additionally detected using the AI software. ...

Abstract	Abstract Background To demonstrate the value of an artificial intelligence (AI) software in the detection of mammographically occult breast cancers and to determine the clinicopathologic patterns of the cancers additionally detected using the AI software. Methods By retrospectively reviewing our institutional database (January 2017–September 2019), we identified women with mammographically occult breast cancers and analyzed their mammography with an AI software that provided a malignancy score (range 0–100; > 10 considered as positive). The hot spots in the AI report were compared with the US and MRI findings to determine if the cancers were correctly marked by the AI software. The clinicopathologic characteristics of the AI-detected cancers were analyzed and compared with those of undetected cancers. Results Among the 1890 breast cancers, 6.8% (128/1890) were mammographically occult, among which 38.3% (49/128) had positive results in the AI analysis. Of them, 81.6% (40/49) were correctly marked by the AI software and determined as “AI-detected cancers.” As such, 31.3% (40/128) of mammographically occult breast cancers could be identified by the AI software. Of the AI-detected cancers, 97.5% were found in heterogeneously or extremely dense breasts, 52.5% were asymptomatic, 86.5% were invasive, and 29.7% had axillary lymph node metastasis. Compared with undetected cancers, the AI-detected cancers were more likely to be found in younger patients (p < 0.001), undergo neoadjuvant chemotherapy as well as mastectomy rather than breast-conserving operation (both p < 0.001), and accompany axillary lymph node metastasis (p = 0.003). Conclusions AI conferred an added value in the detection of mammographically occult breast cancers.
Keywords	Artificial intelligence ; Mammography ; Breast neoplasms ; Medical physics. Medical radiology. Nuclear medicine ; R895-920
Subject code	616
Language	English
Publishing date	2022-03-01T00:00:00Z
Publisher	SpringerOpen
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Whole-genome sequences of 37 breeding line Bombyx mori strains and their phenotypes established since 1960s

Seong-Wan Kim / Min Jee Kim / Seong-Ryul Kim / Jeong Sun Park / Kee-Young Kim / Ki Hwan Kim / Woori Kwak / Iksoo Kim

Scientific Data, Vol 9, Iss 1, Pp 1-

2022 Volume 8

Abstract: Measurement(s) Larval period • Cocoon yield • Single cocoon weight • Egg color • Cocoon shape • Number of cocoons per liter • Voltinism • Moltinism • Cocoon color• Larva pattern Technology Type(s) Clock Device • scale • Eye • amount Factor Type(s) ... ...

Abstract	Measurement(s) Larval period • Cocoon yield • Single cocoon weight • Egg color • Cocoon shape • Number of cocoons per liter • Voltinism • Moltinism • Cocoon color• Larva pattern Technology Type(s) Clock Device • scale • Eye • amount Factor Type(s) Artificial feed • Target Season Sample Characteristic - Organism Bombyx mori Sample Characteristic - Environment house Sample Characteristic - Location South Korea
Keywords	Science ; Q
Language	English
Publishing date	2022-04-01T00:00:00Z
Publisher	Nature Portfolio
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Feasibility of Quantifying Arterial Cerebral Blood Volume Using Multiphase Alternate Ascending/Descending Directional Navigation (ALADDIN).

Ki Hwan Kim / Seung Hong Choi / Sung-Hong Park

PLoS ONE, Vol 11, Iss 6, p e

2016 Volume 0156687

Abstract: Arterial cerebral blood volume (aCBV) is associated with many physiologic and pathologic conditions. Recently, multiphase balanced steady state free precession (bSSFP) readout was introduced to measure labeled blood signals in the arterial compartment, ... ...

Abstract	Arterial cerebral blood volume (aCBV) is associated with many physiologic and pathologic conditions. Recently, multiphase balanced steady state free precession (bSSFP) readout was introduced to measure labeled blood signals in the arterial compartment, based on the fact that signal difference between labeled and unlabeled blood decreases with the number of RF pulses that is affected by blood velocity. In this study, we evaluated the feasibility of a new 2D inter-slice bSSFP-based arterial spin labeling (ASL) technique termed, alternate ascending/descending directional navigation (ALADDIN), to quantify aCBV using multiphase acquisition in six healthy subjects. A new kinetic model considering bSSFP RF perturbations was proposed to describe the multiphase data and thus to quantify aCBV. Since the inter-slice time delay (TD) and gap affected the distribution of labeled blood spins in the arterial and tissue compartments, we performed the experiments with two TDs (0 and 500 ms) and two gaps (300% and 450% of slice thickness) to evaluate their roles in quantifying aCBV. Comparison studies using our technique and an existing method termed arterial volume using arterial spin tagging (AVAST) were also separately performed in five subjects. At 300% gap or 500-ms TD, significant tissue perfusion signals were demonstrated, while tissue perfusion signals were minimized and arterial signals were maximized at 450% gap and 0-ms TD. ALADDIN has an advantage of visualizing bi-directional flow effects (ascending/descending) in a single experiment. Labeling efficiency (α) of inter-slice blood flow effects could be measured in the superior sagittal sinus (SSS) (20.8±3.7%.) and was used for aCBV quantification. As a result of fitting to the proposed model, aCBV values in gray matter (1.4-2.3 mL/100 mL) were in good agreement with those from literature. Our technique showed high correlation with AVAST, especially when arterial signals were accentuated (i.e., when TD = 0 ms) (r = 0.53). The bi-directional perfusion imaging with ...
Keywords	Medicine ; R ; Science ; Q
Subject code	610
Language	English
Publishing date	2016-01-01T00:00:00Z
Publisher	Public Library of Science (PLoS)
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Cross-Method-Based Analysis and Classification of Malicious Behavior by API Calls Extraction

Bruce Ndibanje / Ki Hwan Kim / Young Jin Kang / Hyun Ho Kim / Tae Yong Kim / Hoon Jae Lee

Applied Sciences, Vol 9, Iss 2, p

2019 Volume 239

Abstract: Data-driven public security networking and computer systems are always under threat from malicious codes known as malware; therefore, a large amount of research and development is taking place to find effective countermeasures. These countermeasures are ... ...

Abstract	Data-driven public security networking and computer systems are always under threat from malicious codes known as malware; therefore, a large amount of research and development is taking place to find effective countermeasures. These countermeasures are mainly based on dynamic and statistical analysis. Because of the obfuscation techniques used by the malware authors, security researchers and the anti-virus industry are facing a colossal issue regarding the extraction of hidden payloads within packed executable extraction. Based on this understanding, we first propose a method to de-obfuscate and unpack the malware samples. Additional, cross-method-based big data analysis to dynamically and statistically extract features from malware has been proposed. The Application Programming Interface (API) call sequences that reflect the malware behavior of its code have been used to detect behavior such as network traffic, modifying a file, writing to stderr or stdout, modifying a registry value, creating a process. Furthermore, we include a similarity analysis and machine learning algorithms to profile and classify malware behaviors. The experimental results of the proposed method show that malware detection accuracy is very useful to discover potential threats and can help the decision-maker to deploy appropriate countermeasures.
Keywords	malware classification ; behavior analysis ; machine learning ; feature selection ; API ; static analysis ; dynamic analysis ; Technology ; T ; Engineering (General). Civil engineering (General) ; TA1-2040 ; Biology (General) ; QH301-705.5 ; Physics ; QC1-999 ; Chemistry ; QD1-999
Subject code	006
Language	English
Publishing date	2019-01-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Quantitative Computed Tomography Parameters in Coronavirus Disease 2019 Patients and Prediction of Respiratory Outcomes Using a Decision Tree

Jieun Kang / Jiyeon Kang / Woo Jung Seo / So Hee Park / Hyung Koo Kang / Hye Kyeong Park / Je Eun Song / Yee Gyung Kwak / Jeonghyun Chang / Sollip Kim / Ki Hwan Kim / Junseok Park / Won Joo Choe / Sung-Soon Lee / Hyeon-Kyoung Koo

Frontiers in Medicine, Vol

2022 Volume 9

Abstract: BackgroundChest computed tomography (CT) scans play an important role in the diagnosis of coronavirus disease 2019 (COVID-19). This study aimed to describe the quantitative CT parameters in COVID-19 patients according to disease severity and build ... ...

Abstract	BackgroundChest computed tomography (CT) scans play an important role in the diagnosis of coronavirus disease 2019 (COVID-19). This study aimed to describe the quantitative CT parameters in COVID-19 patients according to disease severity and build decision trees for predicting respiratory outcomes using the quantitative CT parameters.MethodsPatients hospitalized for COVID-19 were classified based on the level of disease severity: (1) no pneumonia or hypoxia, (2) pneumonia without hypoxia, (3) hypoxia without respiratory failure, and (4) respiratory failure. High attenuation area (HAA) was defined as the quantified percentage of imaged lung volume with attenuation values between −600 and −250 Hounsfield units (HU). Decision tree models were built with clinical variables and initial laboratory values (model 1) and including quantitative CT parameters in addition to them (model 2).ResultsA total of 387 patients were analyzed. The mean age was 57.8 years, and 50.3% were women. HAA increased as the severity of respiratory outcome increased. HAA showed a moderate correlation with lactate dehydrogenases (LDH) and C-reactive protein (CRP). In the decision tree of model 1, the CRP, fibrinogen, LDH, and gene Ct value were chosen as classifiers whereas LDH, HAA, fibrinogen, vaccination status, and neutrophil (%) were chosen in model 2. For predicting respiratory failure, the decision tree built with quantitative CT parameters showed a greater accuracy than the model without CT parameters.ConclusionsThe decision tree could provide higher accuracy for predicting respiratory failure when quantitative CT parameters were considered in addition to clinical characteristics, PCR Ct value, and blood biomarkers.
Keywords	coronavirus disease 2019 ; pneumonia ; hypoxia ; respiratory failure ; quantitative CT ; decision tree ; Medicine (General) ; R5-920
Subject code	610
Language	English
Publishing date	2022-05-01T00:00:00Z
Publisher	Frontiers Media S.A.
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Comparative evaluation of Nanopore polishing tools for microbial genome assembly and polishing strategies for downstream analysis

Jin Young Lee / Minyoung Kong / Jinjoo Oh / JinSoo Lim / Sung Hee Chung / Jung-Min Kim / Jae-Seok Kim / Ki-Hwan Kim / Jae-Chan Yoo / Woori Kwak

Scientific Reports, Vol 11, Iss 1, Pp 1-

2021 Volume 11

Abstract: Abstract Assembling high-quality microbial genomes using only cost-effective Nanopore long-read systems such as Flongle is important to accelerate research on the microbial genome and the most critical point for this is the polishing process. In this ... ...

Abstract	Abstract Assembling high-quality microbial genomes using only cost-effective Nanopore long-read systems such as Flongle is important to accelerate research on the microbial genome and the most critical point for this is the polishing process. In this study, we performed an evaluation based on BUSCO and Prokka gene prediction in terms of microbial genome assembly for eight state-of-the-art Nanopore polishing tools and combinations available. In the evaluation of individual tools, Homopolish, PEPPER, and Medaka demonstrated better results than others. In combination polishing, the second round Homopolish, and the PEPPER × medaka combination also showed better results than others. However, individual tools and combinations have specific limitations on usage and results. Depending on the target organism and the purpose of the downstream research, it is confirmed that there remain some difficulties in perfectly replacing the hybrid polishing carried out by the addition of a short-read. Nevertheless, through continuous improvement of the protein pores, related base-calling algorithms, and polishing tools based on improved error models, a high-quality microbial genome can be achieved using only Nanopore reads without the production of additional short-read data. The polishing strategy proposed in this study is expected to provide useful information for assembling the microbial genome using only Nanopore reads depending on the target microorganism and the purpose of the research.
Keywords	Medicine ; R ; Science ; Q
Subject code	306
Language	English
Publishing date	2021-10-01T00:00:00Z
Publisher	Nature Portfolio
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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