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대한당뇨병학회> 당뇨병(JKD)> 특집 : 당뇨병 분야의 Big Data와 인공지능

특집 : 당뇨병 분야의 Big Data와 인공지능

Focused Issue : Real World Data and Artificial Intelligence in Diabetology

김광준 ( Kwang Joon Kim )
  • : 대한당뇨병학회
  • : 당뇨병(JKD) 21권3호
  • : 연속간행물
  • : 2020년 09월
  • : 140-148(9pages)

DOI


목차

서론
의료의 디지털화와 인공지능
디지털화된 의료 환경에서 의료 빅데이터
당뇨병 분야에서 의료 빅데이터와 인공지능의 활용
빅데이터와 인공지능을 활용할 때 유의할 점
결론
REFERENCES

키워드 보기


초록 보기

In the modern society in which we live, digitalization, big data and artificial intelligence (AI) are widely used in finance, e-commerce, manufacturing, and logistics. This trend is no exception in healthcare, and many healthcare professionals have the expectation that digital healthcare, including AI, which produce and utilize medical big data, can help doctors to improve the quality of healthcare services. In particular, in the endocrine area to which we belong, it can be seen that it is relatively easy to conduct AI research using medical big data, i.e., real world data, which is relatively well organized compared to other diseases. Already, AI technologies for diagnosing diabetic complication or vision recognition technologies for determining diabetic retinopathy have been studied for quite a long time and are also used in clinical practice. Hence, there is no doubt that medical big data will play an essential role in healthcare, especially in endocrinology and diabetology. However, there is a need to review the clinical implications of AI research results utilizing medical big data. Medical staff should clarify the purpose of AI to leverage medical big data. In addition, healthcare professionals must understand the precautions and benefits required to use medical big data when perform AI research. Therefore, in this manuscript, some studies are being conducted using real world data in the field of diabetology, and I would like to discuss the implications of these studies and future development directions.

UCI(KEPA)

간행물정보

  • : 의약학분야  > 내과학
  • :
  • :
  • : 계간
  • : 2233-7431
  • :
  • : 학술지
  • : 연속간행물
  • : 2000-2020
  • : 950


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발행기관 최신논문
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1Guideline : 제2형 당뇨병 환자에서 장기간의 Sodium-Glucose Cotransporter 2 억제제 치료가 신장기능에 미치는 효과

저자 : 백종하 ( Jong Ha Baek ) , 오태정 ( Tae Jung Oh ) , 문주영 ( Ju-young Moon ) , 김태희 ( Taehee Kim ) , 고승현 ( Seung Hyun Ko ) , 문민경 ( Min Kyong Moon ) , 김현정 ( Hyun Jung Kim ) , 이동원 ( Dong Won Lee ) , 허규연 ( Kyu Yeon Hur )

발행기관 : 대한당뇨병학회 간행물 : 당뇨병(JKD) 21권 3호 발행 연도 : 2020 페이지 : pp. 105-115 (11 pages)

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(기관인증 필요)

초록보기

Chronic kidney disease commonly develops in patients with type 2 diabetes mellitus (T2DM) and is the most common cause of end-stage renal disease and related cardiovascular complications. Meanwhile, despite the current standard of care that includes optimized glucose control and the use of single-agent blockade of the renin-angiotensin-aldosterone system (RAAS), patients with T2DM remain at increased risk for premature death and complications due to cardiorenal causes. Recent studies using sodium-glucose cotransporter 2 (SGLT2) inhibitors have shown not only glucose lowering effects, but also a reduction in blood pressure, weight loss, and lower cardiovascular risk. Regarding renal outcomes, the use of SGLT2 inhibitors slows the progression of kidney disease compared to placebo when added to standard care. However, concern has been raised that currently available SGLT2 inhibitors in Korea may also be associated with improved renal outcomes during long-term treatment. As a result, we aimed to evaluate the effect of long-term SGLT2 inhibitor treatment on renal function in patients with T2DM using meta-analysis.

2시론 : 당뇨병과 COVID-19

저자 : 박정현 ( Jeong Hyun Park )

발행기관 : 대한당뇨병학회 간행물 : 당뇨병(JKD) 21권 3호 발행 연도 : 2020 페이지 : pp. 116-119 (4 pages)

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(기관인증 필요)

키워드 보기
초록보기

Diabetes mellitus is known to be associated with more severe outcomes and increased mortality in patients presenting with coronavirus disease 2019 (COVID-19; severe acute respiratory syndrome coronavirus-2 [SARS-CoV-2]) infection. The government driven so-called lock down strategy to prevent the spread of COVID-19 infection has changed not only social life styles but also disease related behaviors of diabetic patients. The mortality and morbidity of diabetic patients may be increasing during the COVID-19 pandemic. In this short article, I will describe this complex situation from the view-points of both diabetic patients and health care specialists, and offer several suggestions to solve these problems.

3Statement : Coronavirus Disease 2019 환자의 당뇨병 관리: 예후 및 임상적 고려사항들

저자 : 김혜순 ( Hye Soon Kim )

발행기관 : 대한당뇨병학회 간행물 : 당뇨병(JKD) 21권 3호 발행 연도 : 2020 페이지 : pp. 120-125 (6 pages)

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(기관인증 필요)

초록보기

The coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was declared a global pandemic by the World Health Organization on March 11, 2020. COVID-19 pandemic emphasizes the importance of understanding the pathophysiology which can potentially influence the treatment choices of people with chronic disease such as type 2 diabetes. The reasons for worse prognosis with COVID-19 in people with diabetes include age, sex, ethnicity, comorbidities such as hypertension, cardiovascular disease, obesity and a proinflammatory status. Medications for glucose-lowering and antihypertensive agents should be carefully assessed which can modulate the risk or may have potential interactions with SARS-CoV-2. It is also important to note that SARS-CoV-2 may exacerbate glucose metabolism through direct beta-cell damage, leading to acute hyperglycemic complications and potential new onset diabetes.

4특집 : 빅데이터, 인공지능시대의 의료윤리

저자 : 나해란 ( Hae-ran Na ) , 김헌성 ( Hun-sung Kim )

발행기관 : 대한당뇨병학회 간행물 : 당뇨병(JKD) 21권 3호 발행 연도 : 2020 페이지 : pp. 126-129 (4 pages)

다운로드

(기관인증 필요)

초록보기

When incorporating artificial intelligence (AI) based on medical big data into the clinical and research settings, it is important to consider the associated ethical philosophy in addition to medical behavior. Simply improving the processing speed and increasing the amount of data will not suffice. Instead, it is necessary to continuously provide a direction for AI progress in medical algorithms that are required in order to make use of medical big data. To integrate AI with healthcare research and medical practice, it is essential that AI algorithms are reviewed by experienced medical staff. Additionally, the question regarding which levels of data can or cannot be trusted by medical staff needs to be answered. AI algorithms are best suited to provide assistance (decision-supporting) during the decision-making process. Hence, if more AI algorithms are implemented through such a series of processes, skilled medical personnel can play large roles, and their roles can be subcategorized. Furthermore, based on the medical value of AI, health care providers should have a role in determining the reasonableness and suitability of AI algorithms.

5특집 : 당뇨병 및 내분비질환 분야 머신러닝 활용

저자 : 홍남기 ( Namki Hong ) , 박혜정 ( Heajeong Park ) , 이유미 ( Yumie Rhee )

발행기관 : 대한당뇨병학회 간행물 : 당뇨병(JKD) 21권 3호 발행 연도 : 2020 페이지 : pp. 130-139 (10 pages)

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(기관인증 필요)

초록보기

Recently, machine learning (ML) applications have received attention in diabetes and metabolism research. This review briefly provides the basic concepts of ML and specific topics in diabetes research. Exemplary studies are reviewed to provide an overview of the methodology, main findings, limitations, and future research directions for ML-based studies. Well-defined, testable study hypotheses that stem from unmet clinical needs are always the first prerequisite for successful deployment of an ML-based approach to clinical scene. The management of data quality with enough quantity and active collaboration with ML engineers can enhance the ML development process. The interpretable high-performance ML models beyond the black-box nature of some ML principles can be one of the future goals expected by ML and artificial intelligence in the diabetes research and clinical practice settings that is beyond hype. Most importantly, endocrinologists should play a central role as domain experts who have clinical expertise and scientific rigor, for properly generating, refining, analyzing, and interpreting data by successfully integrating ML models into clinical research.

6특집 : 당뇨병 분야의 Big Data와 인공지능

저자 : 김광준 ( Kwang Joon Kim )

발행기관 : 대한당뇨병학회 간행물 : 당뇨병(JKD) 21권 3호 발행 연도 : 2020 페이지 : pp. 140-148 (9 pages)

다운로드

(기관인증 필요)

초록보기

In the modern society in which we live, digitalization, big data and artificial intelligence (AI) are widely used in finance, e-commerce, manufacturing, and logistics. This trend is no exception in healthcare, and many healthcare professionals have the expectation that digital healthcare, including AI, which produce and utilize medical big data, can help doctors to improve the quality of healthcare services. In particular, in the endocrine area to which we belong, it can be seen that it is relatively easy to conduct AI research using medical big data, i.e., real world data, which is relatively well organized compared to other diseases. Already, AI technologies for diagnosing diabetic complication or vision recognition technologies for determining diabetic retinopathy have been studied for quite a long time and are also used in clinical practice. Hence, there is no doubt that medical big data will play an essential role in healthcare, especially in endocrinology and diabetology. However, there is a need to review the clinical implications of AI research results utilizing medical big data. Medical staff should clarify the purpose of AI to leverage medical big data. In addition, healthcare professionals must understand the precautions and benefits required to use medical big data when perform AI research. Therefore, in this manuscript, some studies are being conducted using real world data in the field of diabetology, and I would like to discuss the implications of these studies and future development directions.

7특집 : 병원 밖 의료데이터: 환자 유래 건강데이터

저자 : 이지산 ( Jisan Lee ) , 김헌성 ( Hun-sung Kim ) , 김정은 ( Jeongeun Kim )

발행기관 : 대한당뇨병학회 간행물 : 당뇨병(JKD) 21권 3호 발행 연도 : 2020 페이지 : pp. 149-155 (7 pages)

다운로드

(기관인증 필요)

초록보기

Patient-generated health data (PGHD) are health-related data generated, recorded, and collected by patients or caregivers. Its main advantage is that patients can actively participate in their own health care, since the data-generating agents are patients and caregivers, not hospitals. Due to the development and popularization of information and communications technology and digital devices, the number of studies using PGHD for better health care is increasing. When PGHD was used in the outpatient setting, healthcare providers were better able to understand each patients' condition using more accurate data, and to monitor patient health status between visits. In particular, to manage chronic diseases such as diabetes, it is essential to monitor daily blood sugar and change nutrient intake in the context of medication, overall diet, and exercise. However, problems associated with data quality, data extraction, and insufficient evidence and research to guide use of this kind of data in clinical setting are yet to be solved. Further, the gap between patient and healthcare providers' perceptions of PGHD persists. We suggest that PGHD, electronic medical record data in hospitals, and claims and genome data could be combined to good effect. This combination can help patients and healthcare providers make better decisions with respect to patient health and to maintain patient engagement. In addition, the collection of PGHD through sophisticated sensors, and data analysis through advanced portals could combine medical big data with daily big data. Eventually, a personalized healthcare automation system through PGHD-based algorithms could provide healthcare artificial intelligence services.

8당뇨병 교육을 위한 정보광장 : 성인 제1형 당뇨병 환자의 관리

저자 : 윤혜령 ( Hye Ryoung Yun )

발행기관 : 대한당뇨병학회 간행물 : 당뇨병(JKD) 21권 3호 발행 연도 : 2020 페이지 : pp. 156-160 (5 pages)

다운로드

(기관인증 필요)

초록보기

The number of adults living with type 1 diabetes is increasing due to an increase in the number of newly diagnosed adult type 1 patients, and the longevity of individuals with childhood-onset diabetes. In addition, adults with type 1 diabetes currently span a wide range of ages, from 18 to 100 years of age, and diabetes self-management may vary by developmental stage. A reasonable A1C goal for many nonpregnant adults with type 1 diabetes is < 7%. But, as with all management issues for people with type 1 diabetes, providers need to individualize assessment and treatment options by individual patient. A structured education program for type 1 diabetes patients includes procedures for blood glucose self-monitoring, carbohydrate counting, and insulin dose adjustment at mealtimes to achieve optimal glycemic control and quality of life. Diabetes self-management education is the ongoing process of facilitating the knowledge, skill, and abilities necessary for diabetes patients to accomplish self-care, which includes the needs, goals, and life experiences of each individual with diabetes.

9당뇨병 교육을 위한 정보광장 : 일차의료기관에서의 당뇨병 관리를 위한 과제

저자 : 이연경 ( Yeon Kyung Lee )

발행기관 : 대한당뇨병학회 간행물 : 당뇨병(JKD) 21권 3호 발행 연도 : 2020 페이지 : pp. 161-165 (5 pages)

다운로드

(기관인증 필요)

초록보기

Diabetes management in primary care is critical to reducing the occurrence and severity of complications through blood sugar management and early detection. A chronic disease management in primary care pilot project, based on the Chronic Care Model (CCM) model that provides patient education on, regular monitoring blood glucose level, medication intake, healthy lifestyle practice, and complications has been developed and applied. Primary care in Korea should provide appropriate education to patients with diabetes and increase the rate of complication testing. In addition, it is of the utmost importance to establish an infrastructure for medical staff to manage patients on a team basis and to establish a patient management system in the community by strengthening primary center (private) and public health care center (public) cooperation activities.

10당뇨병 교육을 위한 정보광장 : 비만 환자의 동기 증진을 위한 행동치료와 동기면담 통합 전략

저자 : 임성철 ( Sung-chul Lim )

발행기관 : 대한당뇨병학회 간행물 : 당뇨병(JKD) 21권 3호 발행 연도 : 2020 페이지 : pp. 166-171 (6 pages)

다운로드

(기관인증 필요)

초록보기

Motivation enhancement is important in behavioral therapy for patients with obesity. Depending on the clinician's communication style, the patient's motivation level may change. Motivational interviewing helps clinicians interact with patients effectively. The purpose of this article was to introduce how to integrate motivational interviewing into obesity behavioral therapy.

1
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8권 4호 ~ 8권 4호

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18권 4호 ~ 18권 4호

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35권 6호 ~ 35권 6호

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76권 4호 ~ 76권 4호

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44권 5호 ~ 44권 5호

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53권 5호 ~ 53권 5호

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14권 5호 ~ 14권 5호

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39권 3호 ~ 39권 3호

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Gut and Liver
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