ScholarWorks@Gachon: Kim, Chang Eop

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Kim, Chang Eop (김창업)

College of Korean Medicine (Premedical course of Oriental Medicine)

Research Area: 생리학

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network pharmacology:7||Korean medicine:6||Medical education:5||Network pharmacology:5||traditional Asian medicine:3||Centipeda minima:3||Obesity:3||Panax ginseng:3||Domainspecific LLM:3||pattern identification:2||Sasang constitutional medicine:2||nephrotoxicity:2||Cordyceps militaris:2||traditional Chinese medicine:2||MCF7:2||Gallic acid:2||Herbal medicine:2||Text mining:2||machine learning:2||text mining:2||apoptosis:2||acupuncture:2||DAMGO:1||DN106212:1||Danazol:1||Data science:1||Datadriven:1||Decisionmaking process:1||Deep learning:1||Diagnostic model:1||Domainspecific LLM language model:1||Domainspecific LLMlanguage model:1||Dongeuibogam:1||Drugcentered approach:1||Estrogen inhibition:1||Estrogen receptor:1||Extremely randomized trees:1||FK506:1||Feature importance:1||FluoroJade staining:1||Food intake:1||Fusarium solani:1||GABAergic interneurons:1||GERD:1||Geometrical Analysis:1||Ginsenosides:1||Hair growth:1||Herb usage:1||Herbal Medicine:1||Huangdi’s Internal Classic(黃帝內經):1||Hyangsayukgunjatang:1||Hypothalamicpituitarygonads axis (HPGA):1||Igf1:1||Insulin signaling pathway:1||Janus kinasesignal transducer and activator of transcription signaling pathway:1||Kilkyung:1||Knowledge extraction:1||Korean medicine clinical indicators:1||Korean medicine education:1||Korean medicine theory:1||Large Large language model:1||Large language model:1||LargeLarge language model:1||Lipolysis:1||Low back pain:1||MAPK:1||MAPKs:1||Machine Learning:1||Machine learning:1||Mechanoreceptors:1||Medical classics(原典):1||Menopause:1||Mitogenactivated protein kinase:1||Modernization of Traditional Medicine:1||Multicompound treatment for GERD:1||Nephrotoxicity:1||Network Topology:1||Network analysis:1||Network pharmacological analysis:1||Network pharmacology analysis:1||Network science:1||Neuropeptide:1||Neurotoxicity:1||Nonalcoholic fatty liver disease:1||Nonalcoholic fatty liver disease:1||Normal variability:1||Opioid:1||Oxyresveratrol:1||Pain:1||Pattern Identification:1||Pattern differentiation:1||Personalized herbal medicine:1||Phellodendri cortex:1||Platycodon grandiflorum:1||Precision Medicine:1||Precocious puberty:1||Primary somatosensory cortex:1||Puberty:1||Pueraria lobata:1||Python:1||Quality evaluation:1||Questionnaire:1||Random Forest:1||Registry:1||Repeated measurements:1||Representational Similarity:1||SREBP1c:1||Saamdoinchimgooyogyeol:1||Sasang Constitutional Medicine:1||Saussurea lappa:1||Shanghanlun:1||Sipjeondaebotang:1||Spatholobi Caulis:1||Substantia gelatinosa:1||Symptomsherbs relationships:1||Tacrolimus:1||Terminalia chebula:1||Theoretical utilization:1||Tissue clearing:1||Traditional Asian medicine:1||Traditional Korean medicine (TKM):1||Traditional Korean medicine research methodology:1||Traditional Medicine:1||Traditional Medicine Education:1||Traditional medicine:1||Twophoton imaging:1||Type II diabetes mellitus:1||VEGF:1||Vegfa:1||Vibrotactile:1||Wnt/betacatenin signaling:1||Zingiber officinale:1||acupuncture points:1||acupuncture style:1||anticancer:1||antioxidant:1||biological neural networks:1||brown rice:1||brushing:1||calcium oscillation:1||caspase:1||cerebellum:1||chronic pain:1||cisplatin:1||cordycepin:1||deep neural networks:1||descending pain modulation:1||design of experiments:1||diagnostic system:1||dimensionality reduction:1||dyslipidemia:1||endophyte:1||expansion recoding:1||flavonoid:1||flavonoids:1||gammapyrones:1||ginseng:1||ginsenosides:1||granule cell layer:1||hair growth:1||herbal medicine:1||homer1a:1||human hair follicle dermal papilla cells:1||human umbilical vein endothelial cells:1||immune response enhancement:1||indication:1||inflammation:1||informatics approach:1||intrinsic excitability:1||iodixanol:1||kernel machine:1||lipid metabolism:1||literature mining:1||menopause:1||menopauserelated metabolic diseases:1||mental disorders and pain:1||metabotropic glutamate receptor 5:1||methodological trend:1||network medicine:1||network pharmacological analysis:1||neural coding:1||neural feature:1||neural network:1||neurodegenerative diseases:1||neuropathic pain:1||neuroprotection:1||nitric oxide:1||nonalcoholic fatty liver disease:1||p53:1||pain:1||pain research trend analysis:1||painrelated brain networks:1||painrelated brain regions:1||periaqueductal gray:1||persistent activity:1||pinch:1||polypharmacology:1||prediction:1||primary somatosensory cortex:1||radial basis (RBF) neural network:1||respiratory tract disease:1||shortcut learning:1||stimulus feature:1||syndrome differentiation:1||synergistic effects:1||systems neuroscience:1||systemslevel mechanism:1||traditional Korean medicine:1||traditional herbal medicine:1||twophoton Cat(2+) imaging:1||vascular endothelial growth factor:1||wound healing:1||“KunShinChoaSa” theory:1||네트워크분석:1||원전(原典):1||텍스트마이닝:1||AMPK:1||황제내경(黃帝內經):1||Adipocytokine:1||Allergic Rhinitis:1||Anemarrhenae rhizome:1||Anmyungambi decoction:1||Anorexia:1||Apoptosis:1||Appetite:1||Artemisia argyi:1||Artificial Intelligence:1||Artificial intelligence (AI):1||Automated quantification:1||Breast cancer:1||Brevilin A:1||COVID19 complications:1||Characterization:1||Chemical characteristics:1||Chimgoogyeongheombang:1||ChungSangBoHaHwan:1||Complexity science:1||Compound information:1||Correlation analysis:1||

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1342, Seongnam-daero, Sujeong-gu, Seongnam-si, Gyeonggi-do, Republic of Korea(13120)031-750-5114

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