Objectives: We analyzed Sasang constitution case reports using text mining to derive network analysis results and designed a classification algorithm using machine learning to select a model suitable for classifying Sasang constitution based on text data.Methods: Case reports on Sasang constitution published from January 1, 2000, to December 31, 2022, were searched. As a result, 343 papers were selected, yielding 454 cases. Extracted texts were pretreated and tokenized with the Python-based KoNLPy package. Each morpheme was vectorized using TF-IDF values. Word cloud visualization and centrality analysis identified keywords mainly used for classifying Sasang constitution in clinical practice. To select the most suitable classification model for diagnosing Sasang constitution, the performance of five models—XGBoost, LightGBM, SVC, Logistic Regression, and Random Forest Classifier—was evaluated using accuracy and F1-Score.Results: Through word cloud visualization and centrality analysis, specific keywords for each constitution were identified. Logistic regression showed the highest accuracy (0.839416), while random forest classifier showed the lowest (0.773723). Based on F1-Score, XGBoost scored the highest (0.739811), and random forest classifier scored the lowest (0.643421).Conclusions: This is the first study to analyze constitution classification by applying text mining and machine learning to case reports, providing a concrete research model for follow-up research. The keywords selected through text mining were confirmed to effectively reflect the characteristics of each Sasang constitution type. Based on text data from case reports, the most suitable machine learning models for diagnosing Sasang constitution are logistic regression and XGBoost.

Objectives : We analyzed Sasang constitution case reports using text mining and designed a classification algorithm using machine learning to select a model suitable for determining Sasang constitution prescriptions based on text data.Methods: Case reports on Sasang constitution published from January 1, 2000, to December 31, 2023, were collected. A total of 360 papers and 483 cases were identified, from which text was extracted for 253 cases. The extracted texts were preprocessed and tokenized using the Python-based KoNLPy package, and each morpheme was vectorized using TF-IDF values. To select the most suitable classification model for diagnosing Sasang constitution, the performance of five models—Random Forest Classifier, XGBoost, LightGBM, SVM, and Logistic Regression—was evaluated based on accuracy and F1-Score.Results: The highest accuracy was achieved by Random Forest Classifier (0.57037), followed by SVM (0.544444), Logistic Regression (0.518519), LightGBM (0.481481), and XGBoost (0.474074). The F1 score was highest for Random Forest Classifier (0.528), followed by SVM (0.52039), Logistic Regression (0.500861), XGBoost (0.45866), and LightGBM (0.446349).Conclusions: This study is the first to analyze Sasang constitution prescription decisions by applying text mining and machine learning to case reports, providing a concrete research model for follow-up studies. Based on case reports and text data, the most suitable machine learning model for determining Sasang constitution prescriptions is Random Forest Classifier.

Cold hypersensitivity in hands and feet (CHHF) affects 20–52% of East Asian populations, is more prevalent in women, and is managed with vasodilators in Western medicine or herbal therapies in traditional East Asian medicine. This study was conducted to compare the pharmacological characteristics of two heat-clearing (HCHs, Scutellariae Radix and Coptidis Rhizoma) and two blood-tonifying herbs (BTHs, Angelicae Sinensis Radix and Paeoniae Radix Alba) used for CHHF. Candidate herbs were selected based on herbology classifications, PubMed searches, and the Korean Medicine Clinical Practice Guideline for CHHF. A total of 61 active compounds and 323 corresponding protein targets with CHHF were retrieved from the traditional Chinese medicine systems pharmacology database and analysis platform (TCMSP), standardized via UniProt, and intersected with CHHF-related genes from GeneCards. Protein–protein interaction networks were con-structed, core targets identified, and functional enrichment analyses performed using Gene Ontology and Reactome databases. A total of 166 herb–CHHF common targets were identified, including 24 shared across all four herbs. HCHs were primarily enriched in hemostasis-, immune-, and signaling-related pathways, whereas BTHs were associated with immune regulation, metabolism, and neuronal modulation. Notably, Scutellariae Radix and Paeoniae Radix Alba showed substantial overlap in enriched pathways. These findings suggest that HCHs and BTHs may act through distinct yet complementary mechanisms in CHHF, providing a mechanistic basis for combined traditional use.

Cold hypersensitivity in hands and feet (CHHF) affects 20–52% of East Asian populations, is more prevalent in women, and is managed with vasodilators in Western medicine or herbal therapies in traditional East Asian medicine. This study was conducted to compare the pharmacological characteristics of two heat-clearing (HCHs, Scutellariae Radix and Coptidis Rhizoma) and two blood-tonifying (BTHs, Angelicae Sinensis Radix and Paeoniae Radix Alba) herbs used for CHHF. Candidate herbs were selected based on herbology classifications, PubMed searches, and the Korean Medicine Clinical Practice Guideline for CHHF. A total of 61 active compounds and 323 corresponding protein targets with CHHF were retrieved from the traditional Chinese medicine systems pharmacology database and analysis platform (TCMSP), standardized via UniProt, and intersected with CHHF-related genes from GeneCards. Protein–protein interaction networks were constructed, core targets identified, and functional enrichment analyses performed using Reactome databases. A total of 166 herb–CHHF common targets were identified, including 24 shared across all four herbs. HCHs were primarily enriched in hemostasis-, immune-, and signaling-related pathways, whereas BTHs were associated with immune regulation, metabolism, and neuronal modulation. Notably, Scutellariae Radix and Paeoniae Radix Alba showed substantial overlap in enriched pathways. These findings suggest that HCHs and BTHs may be associated with distinct yet potentially relevant molecular mechanisms in CHHF. However, because the present analysis was conducted at the single-herb level, these findings cannot be directly generalized to the clinical use of multi-herb formulas and should be interpreted as hypothesis-generating.