This paper outlines the development of artificial intelligence （AI） and its applications in traditional Chinese medicine （TCM） research， and elucidates the roles and advantages of large language models， knowledge graphs， and natural language processing in advancing syndrome identification， prescription generation， and mechanism exploration. Using spleen-stomach diseases as an example， it demonstrates the empowering effects of AI in classical literature mining， precise clinical syndrome differentiation， efficacy and safety prediction， and intelligent education， highlighting an upgraded research paradigm that evolves from data-driven and knowledge-driven approaches to intelligence-driven models. To address challenges related to privacy protection and regulatory compliance in cross-institutional data collaboration， a "trusted federated evidence-based analysis platform for TCM spleen-stomach diseases" is proposed， integrating blockchain-based smart contracts， federated learning， and secure multi-party computation. The deep integration of AI with privacy-preserving computing is reshaping research and clinical practice in TCM spleen-stomach diseases， providing feasible pathways and a technical framework for building a high-quality， trustworthy TCM big-data ecosystem and achieving precision syndrome differentiation.

As a distinctive resource of Chinese civilization， traditional Chinese medicine （TCM） technology transfer faces significant opportunities under the background of digital and intelligent transformation， while also being constrained by unique challenges such as the complexity of its theoretical system， lengthy industrial chains， and multidimensional policy restrictions， resulting in a "high-value-high-threshold" paradox. At present， TCM technology transfer is deeply trapped in a "threefold reluctance" dilemma， i.e.， unwillingness to transfer， inability to transfer， and lack of capacity to transfer. Specifically， the disconnection between scientific research evaluation systems and market demand leads to low conversion rates of research achievements， unclear ownership and compliance risks suppress innovation incentives， and the absence of professional services intensifies supply-demand mismatches. This article systematically analyzes the specific characteristics of TCM technology transfer and proposes a breakthrough pathway centered on full-chain digital and intelligent transformation. By integrating technologies such as intelligent sorting systems， blockchain-based traceability， and AI diagnostic models， the TCM ecosystem spanning "cultivation-production-service" can be reconstructed. In terms of standardization， promoting the progression from "experience-based data conversion" to "data standardization" and further to "intelligent standardization" is advocated to resolve quality control challenges. For example， a "three-no-one-full" certification system can strengthen quality trust. Policy coordination should focus on optimizing mechanisms for the transformation of scientific and technological achievements， while exploring intellectual property securitization and risk-sharing models to stimulate research momentum. In terms of internationalization， reliance on the Belt and Road Initiative platform to promote the export of geo-authentic medicinal material brands and standards is recommended to build a dual-driven model of "technology plus culture". Looking ahead， through the construction of national-level databases， the cultivation of interdisciplinary talent， and the mutual recognition of international standards， a new paradigm of "scientific intelligent manufacturing" can be formed， providing systematic solutions for the modernization of TCM and global health governance.

Objective: Janus kinase (JAK) inhibitors are widely used to treat rheumatoid arthritis (RA); however, comparative analyses regarding their adverse events remain limited. This study aimed to compare the effects of different JAK inhibitors (tofacitinib, baricitinib, and upadacitinib) on hematological parameters in patients with RA in a real-world setting. Methods: This retrospective analysis included 552 patients with RA treated with JAK inhibitors between August 2015 and February 2024. Hematological parameters, including absolute neutrophil count (ANC) and platelet count, were assessed at baseline and after 6 months of treatment. Statistical analysis was performed to evaluate changes over time, and logistic regression analysis identified factors associated with hematologic alterations. Results: The 552 patients were divided into three groups: tofacitinib (n=264), baricitinib (n=143), and upadacitinib (n=145). No significant differences in baseline hematological parameters were observed across the groups. After 6 months, ANC decreased in all groups without significant differences among them (p=0.465). Patients receiving baricitinib had significantly higher platelet counts than those receiving tofacitinib (Pillai’s trace value of 0.063, p<0.001) or upadacitinib (Pillai’s trace value of 0.029, p<0.001).Multivariate analysis revealed that baricitinib was significantly associated with increased platelet counts (odds ratio, 2.009; 95% confidence interval, 1.212~3.331; p=0.007). Conclusion Although all three JAK inhibitors reduced ANC, baricitinib was associated with a substantial increase in platelet counts. These findings highlight the differences in adverse effect profiles among JAK inhibitors, emphasizing the importance of tailored monitoring in RA management.

Objective: To classify life stages for companion dogs and cats by identifying clusters in age-specific disease proportions derived from medical records, providing a data-driven foundation for health examination programs. Methods: We collected 505,667 medical records from 82 veterinary facilities in South Korea between 2020 and 2023. Diagnoses were standardized using GPT-4o and S-BioBERT. Following preprocessing, data from 27 facilities yielded 222,706 canine and 39,910 feline records for the final analysis. Principal component analysis and K-means clustering (K = 4) were applied to age-specific disease proportions to identify life stages.The 10 most highest-proportion diagnoses diseases were determined for each cluster. Results: Canine life stages were classified as ≤ 1 year, 2–5 years, 6–10 years, and 11–15+ years.Feline life stages were 1–2 years, 3–8 years, 9–12 years, and 13–15+ years. In dogs, developmental diseases were common in the youngest age group, while chronic diseases were more prevalent in older groups. In cats, oral and urinary diseases were high-ranking, conjunctivitis was most common in the early stage, and chronic diseases increased with age. Conclusions and Relevance: Age-specific diagnosis patterns support four practical life stages for dogs and cats in South Korea. These boundaries can inform evidence-based preventive examination schedules, animal health policy, and pet insurance product design.

Background/Aims: The incidence of steatotic liver disease (SLD) is increasing across all age groups as the incidence of obesity increases worldwide. The existing noninvasive prediction models for SLD require laboratory tests or imaging and perform poorly in the early diagnosis of infrequently screened populations such as young adults and individuals with healthcare disparities. We developed a machine learning-based point-of-care prediction model for SLD that is readily available to the broader population with the aim of facilitating early detection and timely intervention and ultimately reducing the burden of SLD. Methods: We retrospectively analyzed the clinical data of 28,506 adults who had routine health check-ups in South Korea from January to December 2022. A total of 229,162 individuals were included in the external validation study. Data were analyzed and predictions were made using a logistic regression model with machine learning algorithms. Results: A total of 20,094 individuals were categorized into SLD and non-SLD groups on the basis of the presence of fatty liver disease. We developed three prediction models: SLD model 1, which included age and body mass index (BMI); SLD model 2, which included BMI and body fat per muscle mass; and SLD model 3, which included BMI and visceral fat per muscle mass. In the derivation cohort, the area under the receiver operating characteristic curve (AUROC) was 0.817 for model 1, 0.821 for model 2, and 0.820 for model 3. In the internal validation cohort, 86.9% of individuals were correctly classified by the SLD models. The external validation study revealed an AUROC above 0.84 for all the models. Conclusions As our three novel SLD prediction models are cost-effective, noninvasive, and accessible, they could serve as validated clinical tools for mass screening of SLD.

Background/Aims: The study investigated the incidence, risk factors, and clinical outcomes of chronic antibiotic-refractory pouchitis (CARP) in Korean patients with ulcerative colitis (UC). Methods: This single-center retrospective study included patients with UC who underwent total proctocolectomy with ileal pouch-anal anastomosis at the Asan Medical Center in Korea between January 1987 and December 2022. The primary outcomes were endoscopic remission and pouch failure. The Cox’s proportional hazard model was used to identify the risk factors for CARP. Results: The clinical data of 232 patients were analyzed. The most common cause of surgery was steroid refractoriness (50.9%), followed by dysplasia/colorectal cancer (26.7%). Among 74 patients (31.9%) with chronic pouchitis (CP), 31 (13.4%) had CARP, and 43 (18.5%) had chronic antibiotic-dependent pouchitis (CADP). The most frequent endoscopic phenotype was focal inflammation of the pouch (CP, 47.3%; CARP, 35.5%; CADP, 55.8%). Patients with CARP were less likely to use concomitant probiotics than patients with CADP (29.0% vs 72.1%, p<0.01). The endoscopic remission rate of CP, CARP, and CADP was 14.9%, 9.7%, and 18.6%, respectively.The pouch failure rate associated with CP, CARP, and CADP was 13.5%, 16.1%, and 11.6%, respectively. Current smoking status (adjusted hazard ratio [aHR], 2.96; 95% confidence interval [CI], 1.27 to 6.90; p=0.01) and previous use of biologics/small molecules (aHR, 2.40; 95% CI, 1.05 to 5.53; p=0.04) were significantly associated with CARP development. Conclusions UC patients who were current smokers and previously used biologics/small molecules had a higher risk of developing CARP. Concomitant use of probiotics was less likely to be associated with CARP development.

We report a rare and diagnostically challenging case of a 39-year-old male patient who presented with symptoms of dizziness and headaches, without any focal neurological symptoms. Initial imaging studies suggested a germ cell tumor, and an endoscopic biopsy led to a preliminary diagnosis of a pineal parenchymal tumor of intermediate differentiation. However, histological evaluation following surgical resection revealed the final diagnosis to be an ectopic pituitary neuroendocrine tumor (PitNET), a condition that is exceedingly rare. Ectopic PitNETs are uncommon tumors that develop outside the normal anatomical location of the pituitary gland. Their atypical presentation often leads to misdiagnosis as other intracranial neoplasms. This case highlights the diagnostic challenges posed by ectopic PitNETs and contributes to the limited literature on this rare condition. It underscores the importance of maintaining a broad differential diagnosis in patients presenting with atypical intracranial neoplasms.

ObjectiveExploring the formula rules of commonly used traditional Chinese medicines（TCMs） for epidemic treatment from the Qin and Han dynasties to the Qing dynasty through data mining， providing reference for the prevention and control of contemporary epidemics. MethodsThe articles on epidemic treatment in the electronic database of Chinese Medical Code V5.0 were systematically searched， and the contents such as source， dynasty， author， diagnosis， formula name， therapeutic method and efficacy， and composition of medicines from each article that met the inclusion criteria were extracted. Then， an Excel standardized database was established， and Python programs were used for data mining to summarize the frequency of commonly used medicines and perform hierarchical cluster analysis， Pearson correlation analysis， and association rule analysis. ResultsA total of 1 595 formulas were included， involving 558 TCMs. The efficacy of these medicines could be classified into two categories， namely， expeling pathogenic factors and reinforcing healthy Qi. According to the frequency deconstruction analysis， high-frequency medicines were mainly detoxification， Fu-organ dredging， aromatization and promoting blood circulation， followed by the medicines with the effect of treating the lungs， such as clearing the lungs and resolving phlegm， clearing heat and purging the lungs， relieving cough and asthma， and purging the lungs and relieving asthma. And the proportions of acrid-warm herbs and acrid-cold herbs varied in different periods. Hierarchical clustering and correlation analysis both suggested TCMs for expeling pathogenic factors and reinforcing healthy Qi often formed stable combinations with high association degrees. Association rule analysis showed that the core acrid-warm herb was mainly Ephedrae Herba， and the core acrid-cold herb was mainly Forsythiae Fructus， resulting in the core formulas of Maxing Shigantang and Yinqiaosan. ConclusionThroughout history， the prevention and control of epidemics have been based on the principle of "preserving healthy Qi and avoiding toxic Qi"， focusing on the treatment of the causes and characteristics of epidemics through detoxification， Fu-organ dredging， and aromatization， emphasizing the use of Rhei Radix et Rhizoma and other herbs to dredge Fu-organ， eliminate toxins and pathogens， and playing the role of actively intervene with symptomatic medication. And based on the external manifestations of the body's struggle between evil and righteousness， diagnose and treatment according to syndrome differentiation was performed.

ObjectiveExploring the formula rules of commonly used traditional Chinese medicines（TCMs） for epidemic treatment from the Qin and Han dynasties to the Qing dynasty through data mining， providing reference for the prevention and control of contemporary epidemics. MethodsThe articles on epidemic treatment in the electronic database of Chinese Medical Code V5.0 were systematically searched， and the contents such as source， dynasty， author， diagnosis， formula name， therapeutic method and efficacy， and composition of medicines from each article that met the inclusion criteria were extracted. Then， an Excel standardized database was established， and Python programs were used for data mining to summarize the frequency of commonly used medicines and perform hierarchical cluster analysis， Pearson correlation analysis， and association rule analysis. ResultsA total of 1 595 formulas were included， involving 558 TCMs. The efficacy of these medicines could be classified into two categories， namely， expeling pathogenic factors and reinforcing healthy Qi. According to the frequency deconstruction analysis， high-frequency medicines were mainly detoxification， Fu-organ dredging， aromatization and promoting blood circulation， followed by the medicines with the effect of treating the lungs， such as clearing the lungs and resolving phlegm， clearing heat and purging the lungs， relieving cough and asthma， and purging the lungs and relieving asthma. And the proportions of acrid-warm herbs and acrid-cold herbs varied in different periods. Hierarchical clustering and correlation analysis both suggested TCMs for expeling pathogenic factors and reinforcing healthy Qi often formed stable combinations with high association degrees. Association rule analysis showed that the core acrid-warm herb was mainly Ephedrae Herba， and the core acrid-cold herb was mainly Forsythiae Fructus， resulting in the core formulas of Maxing Shigantang and Yinqiaosan. ConclusionThroughout history， the prevention and control of epidemics have been based on the principle of "preserving healthy Qi and avoiding toxic Qi"， focusing on the treatment of the causes and characteristics of epidemics through detoxification， Fu-organ dredging， and aromatization， emphasizing the use of Rhei Radix et Rhizoma and other herbs to dredge Fu-organ， eliminate toxins and pathogens， and playing the role of actively intervene with symptomatic medication. And based on the external manifestations of the body's struggle between evil and righteousness， diagnose and treatment according to syndrome differentiation was performed.

Background/Aims: Portal vein thrombosis (PVT) frequently occurs in patients with inflammatory bowel disease (IBD), particularly when influenced by factors such as abdominal infections, IBD flare-ups, or surgical procedures. The implications of PVT range from immediate issues such as intestinal ischemia to long-term concerns including portal hypertension and its complications. However, there is a notable gap in comprehensive studies on PVT in IBD, especially with the increasing incidence of IBD in Asia. This research aimed to evaluate the clinical features and outcomes of PVT in patients with IBD at a leading hospital in South Korea. Methods: This retrospective analysis reviewed adult patients diagnosed with both IBD and PVT from 1989 to 2021 at a renowned South Korean medical center. The study focused on patient characteristics, specifics of PVT, administered treatments, and outcomes, all confirmed through enhanced CT scans. Results: A total of 78 patients met the study’s criteria. Notably, only 20.5% (16/78) were treated with oral anticoagulants; however, a vast majority (96.2%; 75/78) achieved complete radiographic resolution (CRR). When comparing patients receiving anticoagulants to those who did not, a significant preference for anticoagulant use was observed in cases where the main portal vein was affected, as opposed to just the left or right veins (p = 0.006). However, multivariable analysis indicated that neither anticoagulant use nor previous surgeries significantly impacted CRR. Conclusions Patients with IBD and PVT generally had favorable outcomes, regardless of anticoagulant use.