Jihye Lim
Biographic Data
| ID | 6794457 |
|---|---|
| NAME | Jihye Lim |
| GIVEN NAMES | Jihye |
| FAMILY NAME | Lim |
| SIGNATURE | LIM J |
| AFFILIATIONS | Youngsan University |
| ORCID | 0000-0003-3819-5192 |
| VERIFIED | Yes |
| TOTAL WORKS | 8 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 8 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2019 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
Exploring trends and topics in hybrid intelligence using keyword co-occurrence networks and topic modelling
Examining the life satisfaction, behavioural intentions, and well-being of scuba divers
A Deep Neural Network-Based Method for Prediction of Dementia Using Big Data
The rise in dementia among the aging Korean population will quickly create a financial burden on society, but timely recognition of early warning for dementia and proper responses to the occurrence of dementia can enhance medical treatment. Health behavior and medical service usage data are relatively more accessible than clinical data, and a prescreening tool with easily accessible data could be a good solution for dementia-related problems. In …
Status of Constipation and Its Association with Sarcopenia in Older Adults
(1) Background: As the clinical relevance of constipation and sarcopenia is not well studied, we aimed to investigate the association between them in older adults. (2) Methods: A cross-sectional study was conducted on 1278 community-dwelling older adults in South Korea. The Rome IV criteria were used to identify patients with clinically defined constipation, while sarcopenia was defined by the Asian Working Group for Sarcopenia consensus. The coh…
Big Data-Driven Determinants of Length of Stay for Patients with Hip Fracture
It is important that length of stay (LOS) management for alleviating health care financial burdens and improving patient outcomes. The aim of this study was to report the differences of LOS and the factors affecting LOS of hip fracture patients using big data. A total of 463,194 data were collected from 2016 to 2017 KNHDS. Of those, 2238 patients with the hip fracture primary diagnosis were included in the study population. As independent variabl…
Utilization of Magnetic Resonance Imaging by Comorbidity of Patients with Dementia
Dementia produces major clinical and social problems that have catastrophic consequences for patients and their families. Dementia also complicates clinical care for other co-existing medical conditions. Magnetic Resonance Imaging (MRI) utilization is increasingly used for diagnostic purposes, such as early diagnosis of dementia and special examination of dementia. This study analyzed the utilization status and factors affecting use of MRI examin…
The Use of Deep Learning to Predict Stroke Patient Mortality
The increase in stroke incidence with the aging of the Korean population will rapidly impose an economic burden on society. Timely treatment can improve stroke prognosis. Awareness of stroke warning signs and appropriate actions in the event of a stroke improve outcomes. Medical service use and health behavior data are easier to collect than medical imaging data. Here, we used a deep neural network to detect stroke using medical service use and h…
A Deep Neural Network-Based Method for Early Detection of Osteoarthritis Using Statistical Data
A large number of people suffer from certain types of osteoarthritis, such as knee, hip, and spine osteoarthritis. A correct prediction of osteoarthritis is an essential step to effectively diagnose and prevent severe osteoarthritis. Osteoarthritis is commonly diagnosed by experts through manual inspection of patients' medical images, which are usually collected in hospitals. Checking the occurrence of osteoarthritis is somewhat time-consuming fo…
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Utilization of Magnetic Resonance Imaging by Comorbidity of Patients with Dementia
Dementia produces major clinical and social problems that have catastrophic consequences for patients and their families. Dementia also complicates clinical care for other co-existing medical conditions. Magnetic Resonance Imaging (MRI) utilization is increasingly used for diagnostic purposes, such as early diagnosis of dementia and special examination of dementia. This study analyzed the utilization status and factors affecting use of MRI examin…
The Use of Deep Learning to Predict Stroke Patient Mortality
The increase in stroke incidence with the aging of the Korean population will rapidly impose an economic burden on society. Timely treatment can improve stroke prognosis. Awareness of stroke warning signs and appropriate actions in the event of a stroke improve outcomes. Medical service use and health behavior data are easier to collect than medical imaging data. Here, we used a deep neural network to detect stroke using medical service use and h…
A Deep Neural Network-Based Method for Early Detection of Osteoarthritis Using Statistical Data
A large number of people suffer from certain types of osteoarthritis, such as knee, hip, and spine osteoarthritis. A correct prediction of osteoarthritis is an essential step to effectively diagnose and prevent severe osteoarthritis. Osteoarthritis is commonly diagnosed by experts through manual inspection of patients' medical images, which are usually collected in hospitals. Checking the occurrence of osteoarthritis is somewhat time-consuming fo…
Big Data-Driven Determinants of Length of Stay for Patients with Hip Fracture
It is important that length of stay (LOS) management for alleviating health care financial burdens and improving patient outcomes. The aim of this study was to report the differences of LOS and the factors affecting LOS of hip fracture patients using big data. A total of 463,194 data were collected from 2016 to 2017 KNHDS. Of those, 2238 patients with the hip fracture primary diagnosis were included in the study population. As independent variabl…
A Deep Neural Network-Based Method for Prediction of Dementia Using Big Data
The rise in dementia among the aging Korean population will quickly create a financial burden on society, but timely recognition of early warning for dementia and proper responses to the occurrence of dementia can enhance medical treatment. Health behavior and medical service usage data are relatively more accessible than clinical data, and a prescreening tool with easily accessible data could be a good solution for dementia-related problems. In …
Status of Constipation and Its Association with Sarcopenia in Older Adults
(1) Background: As the clinical relevance of constipation and sarcopenia is not well studied, we aimed to investigate the association between them in older adults. (2) Methods: A cross-sectional study was conducted on 1278 community-dwelling older adults in South Korea. The Rome IV criteria were used to identify patients with clinically defined constipation, while sarcopenia was defined by the Asian Working Group for Sarcopenia consensus. The coh…
Examining the life satisfaction, behavioural intentions, and well-being of scuba divers
Exploring trends and topics in hybrid intelligence using keyword co-occurrence networks and topic modelling
Medicine (6 works) · Artificial Intelligence (4 works) · Computer Science (4 works) · Population (4 works) · Artificial neural network (3 works) · Emergency Medicine (3 works) · Environmental health (3 works) · Internal Medicine (3 works) · Machine learning (3 works) · Traditional Chinese Medicine Studies (3 works)