• Journal of Digestive Cancer Research
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• v.11 no.3
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• pp.157-164
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• 2023

Prediction is a significant topic in clinical research. The development and validation of a prediction model has been increasingly published in clinical research. In this review, we investigated analytical methods and validation schemes for a clinical prediction model used in digestive cancer research. Deep learning and logistic regression, with split-sample validation as an internal or external validation, were the most commonly used methods. Furthermore, we briefly introduced and summarized the advantages and disadvantages of each method. Finally, we discussed several points to consider when conducting prediction model studies.

• Toxicological Research
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• v.25 no.1
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• pp.1-8
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• 2009

Validation specifies and coordinates all relevant activities to ensure compliance with good laboratory practices (GLP) according to suitable international standards. This includes validation activities of past, present and future for the best possible actions to ensure the integrity of non-clinical laboratory data. Recently, validation has become increasingly important, not only in good manufacturing practice (GMP) institutions but also in GLP facilities. In accordance with the guideline for GLP regulations, all equipments used to generate, measure, or assess data should undergo validation to ensure that this equipment is of appropriate design and capacity and that it will consistently function as intended. Therefore, the implantation of validation processes is considered to be an essential step in a global institution. This review describes the procedures and documentations required for validation of GLP. It introduces basic elements such as the validation master plan, risk assessment, gap analysis, design qualification, installation qualification, operational qualification, performance qualification, calibration, traceability, and revalidation.

• Journal of the Korean Medical Association
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• v.61 no.12
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• pp.765-775
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• 2018

With growing interest in novel digital healthcare devices, such as artificial intelligence (AI) software for medical diagnosis and prediction, and their potential impacts on healthcare, discussions have taken place regarding the regulatory approval, coverage, and clinical implementation of these devices. Despite their potential, 'digital exceptionalism' (i.e., skipping the rigorous clinical validation of such digital tools) is creating significant concerns for patients and healthcare stakeholders. This white paper presents the positions of the Korean Society of Radiology, a leader in medical imaging and digital medicine, on the clinical validation, regulatory approval, coverage decisions, and clinical implementation of novel digital healthcare devices, especially AI software for medical diagnosis and prediction, and explains the scientific principles underlying those positions. Mere regulatory approval by the Food and Drug Administration of Korea, the United States, or other countries should be distinguished from coverage decisions and widespread clinical implementation, as regulatory approval only indicates that a digital tool is allowed for use in patients, not that the device is beneficial or recommended for patient care. Coverage or widespread clinical adoption of AI software tools should require a thorough clinical validation of safety, high accuracy proven by robust external validation, documented benefits for patient outcomes, and cost-effectiveness. The Korean Society of Radiology puts patients first when considering novel digital healthcare tools, and as an impartial professional organization that follows scientific principles and evidence, strives to provide correct information to the public, make reasonable policy suggestions, and build collaborative partnerships with industry and government for the good of our patients.

• Journal of Biomedical Engineering Research
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• v.38 no.3
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• pp.111-115
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• 2017

Blood pressure is one of the important vital signs for monitoring the medical condition of a patient. Automated NIBP(non-invasive blood pressure) monitoring devices calculate systolic and diastolic blood pressures from the oscillation in cuff pressure caused by a pulsation of an artery. To validate the NIBP devices, we developed a simulator to supply the oscillometric waveforms obtained from human subjects. The simulator provided pressure pulses to device-under-test and device readings were compared to the auscultatory references. Fully automated simulation system including OCR(optical character recognition) were developed and used for NIBP monitoring devices. The validation results using the simulator agreed well with previous clinical validation. More validation studies using the standardized oscillometric waveforms would be required for the replacement of clinical trials to validate a new automated NIBP monitoring device.

• Radiation Oncology Journal
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• v.35 no.2
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• pp.101-111
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• 2017

The number of imaging data sets has significantly increased during radiation treatment after introducing a diverse range of advanced techniques into the field of radiation oncology. As a consequence, there have been many studies proposing meaningful applications of imaging data set use. These applications commonly require a method to align the data sets at a reference. Deformable image registration (DIR) is a process which satisfies this requirement by locally registering image data sets into a reference image set. DIR identifies the spatial correspondence in order to minimize the differences between two or among multiple sets of images. This article describes clinical applications, validation, and algorithms of DIR techniques. Applications of DIR in radiation treatment include dose accumulation, mathematical modeling, automatic segmentation, and functional imaging. Validation methods discussed are based on anatomical landmarks, physical phantoms, digital phantoms, and per application purpose. DIR algorithms are also briefly reviewed with respect to two algorithmic components: similarity index and deformation models.

• Biomedical Science Letters
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• v.29 no.4
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• pp.220-230
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• 2023

Identification of the pathogens causing infection is important in terms of patient's health management and infection control. Synovial fluids could be used as clinical samples to detect causative pathogens of prosthetic joint infections (PJIs) using molecular diagnostic assays, therefore, normalization and validation of clinical samples are necessary. Microbial culture is considered the gold standard for all infections, including PJIs. Recently, molecular diagnostic methods have been developed to overcome the limitation of microbial culture. Therefore, guideline for validating clinical samples to provide reliable results of molecular diagnostic assays for infectious diseases is required in clinical field. The present study aimed to develop an accurate validating method of synovial fluid clinical samples using GAPDH gene as an internal control to perform the quantitative PCR TaqMan probe assay to detect pathogens causing PJIs.

• BMB Reports
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• v.38 no.5
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• pp.555-562
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• 2005

Single nucleotide polymorphisms (SNPs) are becoming the most common type of markers used in genetic analysis. In the present report a SNP has been chosen to test the applicability of Real Time PCR to discriminate and quantify SNPs alleles on DNA pools. Amplification Refractory Mutation System (ARMS) and Mismatch Amplification Mutation Assay (MAMA) has been applied. Each assay has been pre-validated testing specificity and performances (linearity, PCR efficiency, interference limit, limit of detection, limit of quantification, precision and accuracy). Both the approaches achieve a precise and accurate estimation of the allele frequencies on pooled DNA samples in the range from 5% to 95% and don't require standard curves or calibrators. The lowest measurement that could be significantly distinguished from the background noise has been determined around the 1% for both the approaches, allowing to extend the range of quantifications from 1% to 99%. Furthermore applicability of Real Time PCR assays for general diagnostic purposes is discussed.

• The Korean Journal of Applied Statistics
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• v.25 no.1
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• pp.139-152
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• 2012

The result of the analysis of a population pharmacokinetic model can directly influence the decision of the dose level applied to the targeted patients. Therefore the validation procedure of the final model is very important in this area. This paper reviews the validation methods of population pharmacokinetic models from a statistical viewpoint. In addition, the whole procedure of the analysis of population pharmacokinetics, from the base model to the final model (that includes various validation procedures for the final model) is tested with real clinical data.

• Proceedings of the PSK Conference
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• 2001.10a
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• pp.281.1-281.1
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• 2001

• ETRI Journal
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• v.32 no.3
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• pp.440-446
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• 2010

Array-based gas sensors now offer the potential of a robust analytical approach to odor measurement for medical use. We are developing a fast reliable method for detection of microbial infection by monitoring the headspace from the infected wound. In this paper, we present initial results obtained from wound-state monitoring for burn patients using an electronic nose incorporating an automated solid-phase microextraction (SPME) desorption system to enable the system to be used for clinical validation. SPME preconcentration is used for sampling of the headspace air and the response of the sensor module to variable concentrations of volatiles emitted from SPME fiber is evaluated. Gas chromatography-mass spectrometry studies prove that living bacteria, the typical infectious agents in clinical practice, can be distinguished from each other by means of a limited set of key volatile products. Principal component analysis results give the first indication that infected patients may be distinguished from uninfected patients. Microbial laboratory analysis using clinical samples verifies the performance of the system.