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안기훈 교수

Kihun Ahn

고려대학교 의학과 · 의학

연구실 소개

안기훈 교수의 연구실은 산모와 태아의 건강을 종합적으로 진단하고 예측하는 데 초점을 맞춘 의료 인공지능 기반 연구를 수행하고 있습니다. 특히 조기 출산, 선천성 기형, 태반 이상 등 산과 관련 질환의 조기 진단 및 위험 예측에 인공지능 알고리즘을 적용한 응용 연구가 중심이며, 초음파 영상 분석과 임상 데이터 기반의 정밀의료 모델 개발도 진행 중입니다. 또한 선천성 변형과 태반 이상과 같은 고위험 임신의 임상적 관리 전략에 대한 기초 연구도 함께 수행하고 있습니다.

의료 인공지능조기 출산 예측산모-태아 질환초음파 영상 분석선천성 기형

연구 현황

논문 수
188
총 인용 수
1,707
최근 5년 논문
55
주요 분야
의학

연구 성과 추이

표시된 성과는 수집된 데이터 기준으로 산출되며, 일부 차이가 있을 수 있습니다.

5개년 연도별 논문 게재 수
55총합
2022
2023
2024
2025
2026
5개년 연도별 피인용 수
218총합
20222023202420252026

주요 논문

15
1
논문|인용수 79·2012
Transvaginal Single-Port Natural Orifice Transluminal Endoscopic Surgery for Benign Uterine Adnexal Pathologies
Ki Hoon Ahn, Jae Yun Song, Sun Haeng Kim, Kyu Wan Lee, Tak Kim
SJR Q2Journal of Minimally Invasive Gynecology
SurgeryMedicine
2
리뷰|인용수 66·2016
Congenital varicella syndrome: A systematic review
Ki Hoon Ahn, Yun-Jung Park, Soon–Cheol Hong, Eun Hee Lee, Ji Sung Lee, Min‐Jeong Oh, Hai‐Joong Kim
SJR Q3Journal of Obstetrics and Gynaecology

Varicella-zoster virus (VZV) is a teratogen that can cross the placenta and cause the congenital varicella syndrome (CVS), which is characterised by multi-system anomalies. There have been 130 reported cases of CVS from 1947 to 2013. The estimated incidence of CVS was 0.59% and 0.84% for women infected with VZV during the entire pregnancy and for those infected the first 20 weeks of pregnancy, respectively. Nine cases were reported at 21-27 weeks of gestation and one case was identified at 36 we

EpidemiologyMedicine
3
리뷰|인용수 57·2020
Application of Artificial Intelligence in Early Diagnosis of Spontaneous Preterm Labor and Birth
Kwang‐Sig Lee, Ki Hoon Ahn
SJR Q2DiagnosticsOA

This study reviews the current status and future prospective of knowledge on the use of artificial intelligence for the prediction of spontaneous preterm labor and birth ("preterm birth" hereafter). The summary of review suggests that different machine learning approaches would be optimal for different types of data regarding the prediction of preterm birth: the artificial neural network, logistic regression and/or the random forest for numeric data; the support vector machine for electrohystero

EpidemiologyMedicine
4
논문|인용수 35·2021
Artificial intelligence in obstetrics
Ki Hoon Ahn, Kwang‐Sig Lee
SJR Q2Obstetrics & Gynecology ScienceOA

This study reviews recent advances on the application of artificial intelligence for the early diagnosis of various maternal-fetal conditions such as preterm birth and abnormal fetal growth. It is found in this study that various machine learning methods have been successfully employed for different kinds of data capture with regard to early diagnosis of maternal-fetal conditions. With the more popular use of artificial intelligence, ethical issues should also be considered accordingly.

Pediatrics, Perinatology and Child HealthMedicine
5
리뷰|인용수 29·2014
Intrapartum ultrasound: A useful method for evaluating labor progress and predicting operative vaginal delivery
Ki Hoon Ahn, Min‐Jeong Oh
SJR Q2Obstetrics & Gynecology ScienceOA

The last step of a successful pregnancy is the safe delivery of the fetus. An important question is if the delivery should vaginal or operative. In addition to the use of conventional antenatal ultrasound, the use of intrapartum ultrasound to evaluate fetal head station, position, cervical ripening, and placental separation is promising. This review evaluates and summarizes the usefulness of intrapartum ultrasound for the evaluation of labor progress and predicting successful operative vaginal d

Obstetrics and GynecologyMedicine
6
논문|인용수 24·2018
Anterior placenta previa in the mid-trimester of pregnancy as a risk factor for neonatal respiratory distress syndrome
Ki Hoon Ahn, Eun Hee Lee, Geum Joon Cho, Soon–Cheol Hong, Min‐Jeong Oh, Hai‐Joong Kim
SJR Q1PLoS ONEOA

This study investigated whether anterior placenta previa in the second trimester is associated with neonatal respiratory distress syndrome (RDS). The neonates delivered by 2067 women between 2007 and 2015 were evaluated for the presence of RDS through birth records. The location of the placenta and the presence of placenta previa during the second and third trimesters were assessed and recorded. Demographic, prenatal, and perinatal records were reviewed. Anterior placenta previa in the second an

Pediatrics, Perinatology and Child HealthMedicine
7
논문|인용수 20·2010
Prenatally Detected Congenital Perineal Mass Using 3D Ultrasound which was Diagnosed as Lipoblastoma Combined with Anorectal Malformation: Case Report
Ki Hoon Ahn, Yoon Jung Boo, Hyun Joo Seol, Hyun Tae Park, Soon–Cheol Hong, Min‐Jeong Oh, Tak Kim, Hai‐Joong Kim, Young Tae Kim, Sun Haeng Kim, Kyu Wan Lee
SJR Q2Journal of Korean Medical ScienceOA

We report a case of prenatally diagnosed congenital perineal mass which was combined with anorectal malformation. The mass was successfully treated with posterior sagittal anorectoplasty postnatally. On ultrasound examination at a gestational age of 23 weeks the fetal perineal mass were found on the right side. Any other defects were not visible on ultrasonography during whole gestation. Amniocentesis was performed to evaluate the fetal karyotyping and acetylcholinesterase which were also normal

RheumatologyMedicine
8
논문|인용수 16·2017
Placental thickness-to-estimated foetal weight ratios and small-for-gestational-age infants at delivery
Ki Hoon Ahn, Joo Hak Lee, Geum Joon Cho, Soon–Cheol Hong, Min‐Jeong Oh, Hai‐Joong Kim
SJR Q3Journal of Obstetrics and Gynaecology

This study aimed to determine the correlation between the placental thickness-to-estimated foetal weight ratio on midterm ultrasonography and small-for-gestational-age (SGA) infants. In this retrospective study, the placental thickness at the umbilical cord insertion site was measured and adjusted for foetal body weight at 18-24 weeks gestation. Investigators compared the data of women who delivered SGA infants (birth weight <10th percentile) with those of women who delivered non-SGA infants. Am

Obstetrics and GynecologyMedicine
9
논문|인용수 15·2022
COVID-19 and vaccination during pregnancy: a systematic analysis using Korea National Health Insurance claims data
Ki Hoon Ahn, Hae-In Kim, Kwang‐Sig Lee, Ju Sun Heo, Hoyeon Kim, Geumjoon Cho, Soon-Cheol Hong, Min‐Jeong Oh, Haejoong Kim
SJR Q2Obstetrics & Gynecology ScienceOA

OBJECTIVE: This study systematically analyzed coronavirus disease 2019 (COVID-19) and vaccination details during pregnancy by using the national health insurance claims data. METHODS: Population-based retrospective cohort data of 12,399,065 women aged 15-49 years were obtained from the Korea National Health Insurance Service claims database between 2019 and 2021. Univariate analysis was performed to compare the obstetric outcomes of pregnant women (ICD-10 O00-O94) and their newborns (ICD-10 P00-

Obstetrics and GynecologyMedicine
10
리뷰|인용수 15·2016
The safety of progestogen in the prevention of preterm birth: meta-analysis of neonatal mortality
Ki Hoon Ahn, Na-Young Bae, Soon–Cheol Hong, Ji Sung Lee, Eun Hee Lee, Hee‐Jung Jee, Geum Joon Cho, Min‐Jeong Oh, Hai-Joong Kim
SJR Q2Journal of Perinatal Medicine

BACKGROUND: The safety of preventive progestogen therapy for preterm birth remains to be established. This meta-analysis aimed to evaluate the effects of preventive progestogen therapy on neonatal mortality. METHODS: Randomized controlled trials (RCTs) on the preventive use of progestogen therapy, published between October 1971 and November 2015, were identified by searching MEDLINE/PubMed, EMBASE, Scopus, ClinicalTrials.gov, Cochrane Library databases, CINAHL, POPLINE, and LILACS using "progest

EpidemiologyMedicine
11
논문|인용수 14·2011
Relationship between serum estradiol and follicle-stimulating hormone levels and urodynamic results in women with stress urinary incontinence
Ki Hoon Ahn, Tak Kim, Jun Young Hur, Sun Haeng Kim, Kyu Wan Lee, Young Tae Kim
SJR Q2International Urogynecology Journal
RheumatologyMedicine
12
논문|인용수 13·2021
Association of Preterm Birth with Depression and Particulate Matter: Machine Learning Analysis Using National Health Insurance Data
Kwang‐Sig Lee, Hae-In Kim, Ho Yeon Kim, Geum Joon Cho, Soon–Cheol Hong, Min‐Jeong Oh, Hai‐Joong Kim, Ki Hoon Ahn
SJR Q2DiagnosticsOA

This study uses machine learning and population data to analyze major determinants of preterm birth including depression and particulate matter. Retrospective cohort data came from Korea National Health Insurance Service claims data for 405,586 women who were aged 25-40 years and gave births for the first time after a singleton pregnancy during 2015-2017. The dependent variable was preterm birth during 2015-2017 and 90 independent variables were included (demographic/socioeconomic information, p

Public Health, Environmental and Occupational HealthMedicine
13
논문|인용수 12·2020
Effect of patient blood management system and feedback programme on appropriateness of transfusion: An experience of Asia's first Bloodless Medicine Center on a hospital basis
Hyeon Ju Shin, Jong Hun Kim, Yujin Park, Ki Hoon Ahn, Jae Seung Jung, Jong Hoon Park
SJR Q3Transfusion Medicine

BACKGROUND: Patient blood management (PBM) programmes minimise red blood cell (RBC) transfusion and improve patient outcomes worldwide. This study evaluated the effect of a multidisciplinary, collaborative PBM programme on the appropriateness of RBC transfusion in medical and surgical departments at a hospital level. METHODS/MATERIALS: In 2018, the revised PBM programme was launched at the Korea University Anam Hospital, a tertiary hospital with 1048 hospital beds and the first Asian institution

BiochemistryMedicine
14
논문|인용수 12·2022
Association of preterm birth with medications: machine learning analysis using national health insurance data
Kwang‐Sig Lee, In‐Seok Song, Eun Sun Kim, Hae-In Kim, Ki Hoon Ahn
SJR Q1Archives of Gynecology and Obstetrics
EpidemiologyMedicine
15
논문|인용수 11·2011
Microarray Analysis of Gene Expression During Differentiation of Human Mesenchymal Stem Cells Treated with Vitamin E in vitro into Osteoblasts
Ki Hoon Ahn, Hwa Kyung Jung, So Eun Jung, Kyong Wook Yi, Hyun Tae Park, Jung Ho Shin, Young Tae Kim, Jun Young Hur, Sun Haeng Kim, Tak Kim
SJR Q2Journal of Bone Metabolism
Molecular BiologyBiochemistry, Genetics and Molecular Biology

대표 연구 분야

EpidemiologyPediatrics, Perinatology and Child HealthObstetrics and GynecologyRheumatologyReproductive MedicinePublic Health, Environmental and Occupational Health

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