인공지능 알고리즘 개발 논문
• Park MG et al, Medical Dataset Preparation Platform Based on a Common Data Model for Machine Learning. Test Engineering and Management. 2019.
• Kim SJ et al, Development of a Dedicated Software for Sarcopenia Quantitative Analysis. Test Engineering and Management. 2019.
• Park J et al, Reliable and robust method for abdominal muscle mass quantification using CT/MRI: An explorative study in healthy subjects. PLoS One. 2019.
• Ko H et al, COVID-19 Pneumonia Diagnosis Using a Simple 2D Deep Learning Framework With a Single Chest CT Image: Model Development and Validation. J Med Internet Res. 2020.
• Park HJ et al, Development and Validation of a Deep Learning System for Segmentation of Abdominal Muscle and Fat on Computed Tomography. Korean J Radiol. 2020.
• Chung M et al, Liver segmentation in abdominal CT images via auto-context neural network and self-supervised contour attention. Artificial Intelligence in Medicine. 2021.
• Chung H et al, Prediction and Feature Importance Analysis for Severity of COVID-19 in South Korea Using Artificial Intelligence: Model Development and Validation. J Med Internet Res. 2021.
• Chung H et al, Artificial-intelligence-driven discovery of prognostic biomarker for sarcopenia. J Cachexia Sarcopenia Muscle. 2021.
• Aziz A et al, An Ensemble of Optimal Deep Learning Features for Brain Tumor Classification. CMC-Computers, Materials & Continua. 2021.
• Mehmood A et al, Human Gait Recognition: A Deep Learning and Best Feature Selection Framework. CMC-Computers, Materials & Continua. 2021.
• Ebada A. I. et al, Applying Apache Spark on Streaming Big Data for Health Status Prediction. CMC-Computers, Materials & Continua. 2021.
• Ha J et al, Development of a fully automatic deep learning system for L3 selection and body composition assessment on computed tomography. Sci Rep. 2021.
• Lee CS et al, Urinary Stones Segmentation Model and AI Web Application Development in Abdominal CT Images Through Machine Learning. KIPS Transactions on Computer and Communication Systems. 2021.
• Aziz A et al, An Ensemble of Optimal Deep Learning Features for Brain Tumor Classification. CMC-Computers, Materials & Continua. 2021.
• Kang WS et al, Artificial intelligence to predict in-hospital mortality using novel anatomical injury score. Sci Rep. 2021.
• Ko H et al, A Deep Residual U-Net Algorithm for Automatic Detection and Quantification of Ascites on Abdominopelvic Computed Tomography Images Acquired in the Emergency Department: Model Development and Validation. J Med Internet Res. 2022.
• Na S et al, Development and validation of an ensemble artificial intelligence model for comprehensive imaging quality check to classify body parts and contrast enhancement. BMC Med Imaging. 2022.
• Ko Y et al, Artificial Intelligence Mortality Prediction Model for Gastric Cancer Surgery Based on Body Morphometry, Nutritional, and Surgical Information: Feasibility Study. Applied Sciences. 2022.
• Chung HW et al, Prognotic artificial intelligence model to predict 5 Year survival at 1 year aafter gastric cancer surgery based on nutririon and body morphometry J Cachexia Sarcopenia Muscle. 2023.
• Na SW et al, A Study of the Use of Contrast Agent and the Improvement of Body Part Classification Performance through Deep Learning-Based CT Scan Reconstruction. Journal of Broadcast Engineering. 2023.
• Na SW et al, Sequence-Type Classification of Brain MRI for Acute Stroke Using a Self-Superised Machine Learning Algorithm. Diagnostics. 2023.
인공지능 알고리즘의 임상검증 논문
• Kim DW et al, Design Characteristics of Studies Reporting the Performance of Artificial Intelligence Algorithms for Diagnostic Analysis of Medical Images: Results from Recently Published Papers. Korean J Radiol. 2019.
• Kim DW et al, Assessment of Myosteatosis on Computed Tomography by Automatic Generation of a Muscle Quality Map Using a Web-Based Toolkit: Feasibility Study. JMIR Med Inform. 2020.
개발된 인공지능 기술을 임상에 활용한 논문
• Kim TH et al, Noninvasive Differential Diagnosis of Liver Iron Contents in Nonalcoholic Steatohepatitis and Simple Steatosis Using Multiecho Dixon Magnetic Resonance Imaging. Acad Radiol. 2019.
• Kim TH et al, Development of liver surface nodularity quantification program and its clinical application in nonalcoholic fatty liver disease. Scientific reports. 2019.
• Kim TH et al, Accuracy of proton magnetic resonance for diagnosing non-alcoholic steatohepatitis: a meta-analysis. Scientific reports. 2019.
• Jang M et al, Predictive value of sarcopenia and visceral obesity for postoperative pancreatic fistula after pancreaticduodenectomy analyzed on clinically acquired CT and MRI. Eur Radiol. 2019.
• Lee K et al, Impact of remnant stomach volume and anastomosis on nutrition and body composition in gastric cnacer patients. Surg Oncol. 2019.
• Choe J et al, What Is New in the 2017 World Health Organization Classification and 8th American Joint Committee on Cancer Staging System for Pancreatic Neuroendocrine Neoplasms? Korean J Radiol. 2019.
• Kim SJ et al, Development of quantification software for evaluating body composition contents and its clinical application in sarcopenic obesity. Scientific reports. 2020.
• Han JS et al, Association of Body Composition with Long-Term Survival in Non-metastatic Rectal Cancer Patients. Cancer Res Treat. 2020.
• Kim EH et al, Reference Data and T-Scores of Lumbar Skeletal Muscle Area and Its Skeletal Muscle Indices Measured by CT Scan in a Healthy Korean Population. J Gerontol A Biol Sci Med Sci. 2020.
• Kim DW et al, Reliability of Skeletal Muscle Area Measurement on CT with Different Parameters: A Phantom Study. Korean J Radiol. 2020.
• Yoon YH et al, Prognostic Value of Baseline Sarcopenia on 1-year Mortality in Patients Undergoing Transcatheter Aortic Valve Implantation. Am J Cardiol. 2020.
• Kim KW et al, Preoperative nutritional risk index and postoperative one-year skeletal muscle loss can predict the prognosis of patients with gastric adenocarcinoma: a registry-based study. BMC Cancer. 2021.
• Kim HK et al, Age-related changes in muscle quality and development of diagnostic cutoff points for myosteatosis in lumbar skeletal muscles measured by CT scan. Clin Nutr. 2021.
• Hong SI et al, Long-Term Outcomes After In-Hospital Cardiac Arrest: Does Pre-arrest Skeletal Muscle Depletion Metter? Front Physiol. 2021.
• Lee C et al, Influence of Postoperative Changes in Sarcopenia on Long-Term Survival in Non-Metastatic Colorectal Cancer Patients. Cancers. 2021.
• Kim GH et al, Impact of Comorbidities, Sarcopenia, and Nutritional Status on the Long-Term Outcomes after Endoscopic Submucosal Dissection for Early Gastric Cancer in Elderly Patients Aged ≥ 80 Years. Cancer (Basel). 2021.
• Kim HH et al, Longitudinal Changes in Body Composition of Long-Term Survivors of Pancreatic Head Cancer and Factors Affecting the Changes. J Clin Med. 2021.
• Lee MJ et al, Association Between Muscle Quality Measured by Abdominal Computed Tomography and Subclinical Coronary Atherosclerosis. Arterioscler Thromb Biol. 2021.
• Kim DW et al, Effects of Contrast Phase on Automated Measurements of Muscle Quantity and Quality Using CT. Korean J Radiol. 2021.
• Kim YJ et al, Subcutaneous fat area at the upper thigh level is a useful prognostic marker in the elderly with femur fracture. J Cachexia Sarcopenia Muscle. 2021.
• Lim J et al, The role of muscle depletion and visceral adiposity in HCC patients aged 65 and over undergoing TACE. BMC Cancer. 2021.
• Jeon YW et al, Intermuscular fat density as a novel prognostic factor in breast cancer patients treated with adjuvant chemotherapy. Breast Cancer Res Treat. 2021.
• Ko Y et al, A reliable and robust method for the upper thigh muscle quantification on computed tomography: toward a quantitative biomarker for sarcopenia. BMC Musculoskelet Disord. 2022.
• Hong S et al, Impact of Baseline Muscle Mass and Myosteatosis on the Development of Early Toxicity During First-Line Chemotherapy in Patients With Initially Metastatic Pancreatic Cancer. Front Oncol. 2022.
• Kim JS et al, The Impact of Myosteatosis Percentage on Short-Term Mortality in Patients With Septic Shock. J Clin Med. 2022.
• Kim A et al, Larger Remaining Stomach Volume Is Associated With Better Nutrition and Muscle Preservation in Patients With Gastric Cancer Receiving Distal Gastrectomy With Gastroduodenostomy. J Gastric Cancer. 2022.
• Ko Y et al, Change of Computed Tomography-Based Body Composition after Adrenalectomy in Patients with Pheochromocytoma. Cancers (Basel). 2022.
• Jung JY et al, The effects of muscle mass and quality on mortality of patients with acute kidney injury requiring continuous renal replacement therapy. Sci Rep. 2023.
인공지능 학습데이터셋 구축에 관련된 논문
• Lee CS et al, Construction of Artificial Intelligence Training Platform for Multi-Center Clinical. KIPS Transactions on Computer and Communication Systems. 2020.
• Lee K et al, Recent Issues on Body composition Imaging for Sarcopenia Evaluation. Korean J Radiol. 2019.
• Ahn H et al, Updated systematic review and meta-analysis on diagnostic issues and the prognostic impact of myosteatosis: A new paradigm beyond sarcopenia. Ageing Research Reviews. 2021.
• Kaushik H et al, Screening of COVID-19 Patients Using Deep Learning and loT Framework. CMC-Computers, Materials & Continua. 2021.
• Noh SH et al, Development of Web Service for Liver Cirrhosis Diagnosis Based on Machine Learning. KIPS Transactions on Computer and Communication Systems. 2021.
• Park HJ et al, Comparison of RECIST 1.1 and iRECIST in Patients Treated with Immune Checkpoint Inhibitors: A Sysmatic Review and Meta-Analysis. Cancer (Basel). 2021.
• You MW et al, Impact of liver-stiffness measurement on hepatocellular carcinoma development in chronic hepatitis C patients treated with direct-acting antivirals: A systematic review and time-to-event meta-analysis. Journal of Gastroenterology and Hepatology. 2021.
• Kim TH et al, Assessment of Liver Fibrosis Stage Using Integrative Analysis of Hepatic Heterogeneity and Nodularity in Routine MRI with FIB-4 Index as Reference Standard. J Clin Med. 2021.
• Kim KW et al, Artificial Intelligence in Gastric Cancer Imaging With Emphasis on Diagnostic Imaging and Body Morphometry. J Gastric Cancer 2023.
