A5100707540- Topic Modeling
- Machine Learning in Healthcare
- Educational Systems and Policies
- Education and Learning Interventions
- Artificial Intelligence in Healthcare
- Biomedical Text Mining and Ontologies
- Educational Research and Pedagogy
- Natural Language Processing Techniques
- Education, Safety, and Science Studies
- Psychosocial Factors Impacting Youth
- Artificial Intelligence in Healthcare and Education
- Diverse Approaches in Healthcare and Education Studies
- Energy and Environmental Systems
- Health Systems, Economic Evaluations, Quality of Life
- Semantic Web and Ontologies
- Speech and dialogue systems
- AI in cancer detection
- Technology and Data Analysis
- Pharmaceutical studies and practices
- Biosimilars and Bioanalytical Methods
Sungkyunkwan University
2018-2025
Korea Advanced Institute of Science and Technology
2023
Despite the remarkable progress in development of predictive models for healthcare, applying these algorithms on a large scale has been challenging. Algorithms trained particular task, based specific data formats available set medical records, tend to not generalize well other tasks or databases which fields may differ. To address this challenge, we propose General Healthcare Predictive Framework (GenHPF), is applicable any EHR with minimal preprocessing multiple prediction tasks. GenHPF...
Abstract Many verbs in English show causative and noncausative uses. The goal of this paper is to identify a factor most strongly associated with the realizations alternation. We report corpus study that tested effects three semantic contextual factors – intentionality, identifiability, external causality against 3,864 instances uses 135 alternating extracted from automatically parsed British National Corpus. Our results series multifactorial analyses data indicate intentionality...
Abstract Aim The introduction of biosimilars is expected to reduce the cost biologic drugs, but actual savings have not yet been quantified in Korea. aim this study was estimate annual attributed infliximab biosimilar. Methods We conducted a retrospective analysis using data from Health Insurance Review and Assessment Service‐National Patients Sample (HIRA‐NPS) between 2011 2014. subjects were patients who treated with infliximab, adalimumab or etanercept. compared drug costs before after...
The development of large language models tailored for handling patients' clinical notes is often hindered by the limited accessibility and usability these due to strict privacy regulations. To address challenges, we first create synthetic large-scale using publicly available case reports extracted from biomedical literature. We then use train our specialized model, Asclepius. While Asclepius trained on data, assess its potential performance in real-world applications evaluating it real...
This study introduces EHRNoteQA, a novel patient-specific question answering benchmark tailored for evaluating Large Language Models (LLMs) in clinical environments. Based on MIMIC-IV Electronic Health Record (EHR), team of three medical professionals has curated the dataset comprising 962 unique questions, each linked to specific patient's EHR notes. What makes EHRNoteQA distinct from existing EHR-based benchmarks is as follows: Firstly, it first adopt multi-choice format, design choice...
Despite the abundance of Electronic Healthcare Records (EHR), its heterogeneity restricts utilization medical data in building predictive models. To address this challenge, we propose Universal Predictive Framework (UniHPF), which requires no domain knowledge and minimal pre-processing for multiple prediction tasks. Experimental results demonstrate that UniHPF is capable large-scale EHR models can process any form from distinct systems. We believe our findings provide helpful insights...
Making the most use of abundant information in electronic health records (EHR) is rapidly becoming an important topic medical domain. Recent work presented a promising framework that embeds entire features raw EHR data regardless its form and code standards. The framework, however, only focuses on encoding with minimal preprocessing fails to consider how learn efficient representation terms computation memory usage. In this paper, we search for versatile encoder not reducing large into...
ABSTRACT In this study, we propose a method of categorizing relations between headword and its aliases using Korean Wikipedia data. We orthographically similar types different types. Orthographically are divided into 5 types: Word space, Pronunciation difference, Omission, Abbreviation, order change while also classified 4 Foreign word, Acronym, Paraphrased expression Call name. show examples to verify the proposed method.
본 연구의 목적은 수도권에 소재한 중규모대학인 A대학교 재학생의 핵심역량을 진단하는 측정도구를 개발하고 타당화 하는 것이다. 연구 방법으로는 2020년 9월부터 11월에 걸쳐 학부생을 대상으로 2차례에 걸친 예비조사를 실시하여 6개의 핵심역량, 110개 문항을 선정한 뒤, 2021년 3월 23일부터 4월 4일까지 조사를 통해 얻은 3,381명의 자료를 SPSS 26, AMOS 26.0 프로그램을 활용하여 분석하였다. 첫째, 빈도분석(frequency analysis)으로 평균, 표준편차, 왜도, 첨도 등을 검토하였다. 둘째, 탐색적 요인분석(exploratory factor analysis, EFA)으로 도구들을 구성하고 있는 문항과 도구측정의 정확성과 요인 차원의 독립성을 검증하였다. 셋째, 내적일치도(Cronbach's α)로 측정문항들의 구성요인에 대해 내적일관성을 확인하였다. 넷째, 최종 문항에 대한 확인적 요인분석(confirmatory CFA)을 하였다. 다섯째,...
Despite the remarkable progress in development of predictive models for healthcare, applying these algorithms on a large scale has been challenging. Algorithms trained particular task, based specific data formats available set medical records, tend to not generalize well other tasks or databases which fields may differ. To address this challenge, we propose General Healthcare Predictive Framework (GenHPF), is applicable any EHR with minimal preprocessing multiple prediction tasks. GenHPF...
The purpose of the study is to provide implications for multi-cultural education in Korea. So we comparatively analyze how programs student teachers are implemented teacher training institutions Finland and South In order achieve this purpose, collected analyzed primary secondary data each educational institution’s by intentionally selecting two countries. from 3 were according criteria based on previous studies. This meaningful that it conducted a comparative analysis considering context...
연구 목적: 본 연구는 예비유아교사가 학교현장실습 기간 중 실행하는 수업실습 과정에서 실습지도교사가 중점적으로 지도한 내용을 분석함으로써 수업능력을 향상시킬 수 있는 방안을 모색하고자 실시되었다. 방법: 연구대상은 N시의 4년제 대학 유아교육학과에서 「학교현장실습」을 수강한 4학년 예비유아교사들의 실습지도교사들이다. 내용: 수업실습을 지도하면서 <교수방법>과 <수업운영> 영역에서 중점지도한 것으로 나타났다. 결론 및 제언: 예비유아교사의 수업능력 향상을 위해 대학-유아교육현장-실습지도교사와의 유기적인 상호협력이 필요하며, 예비유아교사들에게 실천적 경험을 제공할 유아교육현장과의 다양한 연계방안을 논의하였다.
연구 목적: 이 연구는 간호대학생의 스마트폰 중독과 관련된 영향요인을 파악하고, 자기통제력간의 관계를 규명하기 위한 연구이다. 방법: 대상은 J시에 소재한 간호대학에 재학 중인 간호대학생 252명을 대상으로 구조화된 설문지로 자료를 수집하였다. 자료 분석은 SPSS 23.0프로그램을 이용하여 빈도, 평균, 표준편차, t-test, ANOVA, 상관관계분석, 다중회귀분석을 실시하였다. 결과: 중독 평균 점수는 34.3점, 자기통제력 40.6점이었고, 고위험 사용자군은 8.7%로 나타났다. 자기통제력은 유의한 음의 상관관계가 있었다. 회귀분석결과 중독에 영향을 미치는 요인이며, 설명력은 51.4%였다. 결론 및 제언: 본 결과를 토대로 중독을 감소시키기 위해 자기통제력을 증진시키기 다양한 프로그램의 개발 적용을 제안한다.
The purpose of this study was to check whether there is a difference in the effect strategy gradually fading help worked examples on mathematics achievement, cognitive load, self-efficacy and interest middle school students. In addition, through interviews, we tried examine students' perception faded strategy. To end, 269 sophomores were divided into two groups (faded strategy, example-problem strategy) provided task unit application simultaneous linear equations. findings are as follows....