The enlightenment of artificial intelligence large-scale model on the research of intelligent eye diagnosis in traditional Chinese medicine

Eye diagnosis is a method for inspecting systemic diseases and syndromes by observing the eyes.With the development of intelligent diagnosis in traditional Chinese medicine(TCM);artificial intelligence(AI)can improve the accuracy and efficiency of eye diagnosis.However;the research on intelligent eye diagnosis still faces many challenges;including the lack of standardized and precisely labeled data;multi-modal information analysis;and artificial in-telligence models for syndrome differentiation.The widespread application of AI models in medicine provides new insights and opportunities for the research of eye diagnosis intelli-gence.This study elaborates on the three key technologies of AI models in the intelligent ap-plication of TCM eye diagnosis;and explores the implications for the research of eye diagno-sis intelligence.First;a database concerning eye diagnosis was established based on self-su-pervised learning so as to solve the issues related to the lack of standardized and precisely la-beled data.Next;the cross-modal understanding and generation of deep neural network models to address the problem of lacking multi-modal information analysis.Last;the build-ing of data-driven models for eye diagnosis to tackle the issue of the absence of syndrome dif-ferentiation models.In summary;research on intelligent eye diagnosis has great potential to be applied the surge of AI model applications.

Integrative analysis of bone-formation associated genes and immune cell infiltration in osteoporosis, and the prediction of active ingredients in targeted traditional Chinese medicine

Objective To explore the differential expression and mechanisms of bone formation-related genes in osteoporosis(OP)leveraging bioinformatics and machine learning methodologies;and to predict the active ingredients of targeted traditional Chinese medicine(TCM)herbs.Methods The Gene Expression Omnibus(GEO)and GeneCards databases were employed to conduct a comprehensive screening of genes and disease-associated loci pertinent to the pathogenesis of OP.The R package was utilized as the analytical tool for the identification of differentially expressed genes.Least absolute shrinkage and selection operator(LASSO)logis-tic regression analysis and support vector machine-recursive feature elimination(SVM-RFE)algorithm were employed in defining the genetic signature specific to OP.Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment analyses for the selected pivotal genes were conducted.The cell-type identification by estimating rela-tive subsets of RNA transcripts(CIBERSORT)algorithm was leveraged to examine the infiltra-tion patterns of immune cells;with Spearman’s rank correlation analysis utilized to assess the relationship between the expression levels of the genes and the presence of immune cells.Coremine Medical Database was used to screen out potential TCM herbs for the treatment of OP.Comparative Toxicogenomics Database(CTD)was employed for forecasting the TCM ac-tive ingredients targeting the key genes.AutoDock Vina 1.2.2 and GROMACS 2020 softwares were employed to conclude analysis results;facilitating the exploration of binding affinity and conformational dynamics between the TCM active ingredients and their biological targets.Results Ten genes were identified by intersecting the results from the GEO and GeneCards databases.Through the application of LASSO regression and SVM-RFE algorithm;four piv-otal genes were selected:coat protein(CP);kallikrein 3(KLK3);polymeraseγ(POLG);and transient receptor potential vanilloid 4(TRPV4).GO and KEGG pathway enrichment analy-ses revealed that these trait genes were predominantly engaged in the regulation of defense response activation;maintenance of cellular metal ion balance;and the production of chemokine ligand 5.These genes were notably associated with signaling pathways such as ferroptosis;porphyrin metabolism;and base excision repair.Immune infiltration analysis showed that key genes were highly correlated with immune cells.Macrophage M0;M1;M2;and resting dendritic cell were significantly different between groups;and there were signifi-cant differences between different groups(P<0.05).The interaction counts of resveratrol;curcumin;and quercetin with KLK3 were 7;3;and 2;respectively.It shows that the interac-tions of resveratrol;curcumin;and quercetin with KLK3 were substantial.Molecular docking and molecular dynamics simulations further confirmed the robust binding affinity of these bioactive compounds to the target genes.Conclusion Pivotal genes including CP;KLK3;POLG;and TRPV4;exhibited commendable significant prognostic value;and played a crucial role in the diagnostic assessment of OP.Resveratrol;curcumin;and quercetin;natural compounds found in TCM;showed promise in their potential to effectively modulate the bone-forming gene KLK3.This study provides a sci-entific basis for the interpretation of the pathogenesis of OP and the development of clinical drugs.

Constitution identification model in traditional Chinese medicine based on multiple features

Objective To construct a precise model for identifying traditional Chinese medicine(TCM)constitutions;thereby offering optimized guidance for clinical diagnosis and treatment plan-ning;and ultimately enhancing medical efficiency and treatment outcomes.Methods First;TCM full-body inspection data acquisition equipment was employed to col-lect full-body standing images of healthy people;from which the constitutions were labelled and defined in accordance with the Constitution in Chinese Medicine Questionnaire(CCMQ);and a dataset encompassing labelled constitutions was constructed.Second;heat-suppres-sion valve(HSV)color space and improved local binary patterns(LBP)algorithm were lever-aged for the extraction of features such as facial complexion and body shape.In addition;a dual-branch deep network was employed to collect deep features from the full-body standing images.Last;the random forest(RF)algorithm was utilized to learn the extracted multifea-tures;which were subsequently employed to establish a TCM constitution identification mod-el.Accuracy;precision;and F1 score were the three measures selected to assess the perfor-mance of the model.Results It was found that the accuracy;precision;and F1 score of the proposed model based on multifeatures for identifying TCM constitutions were 0.842;0.868;and 0.790;respectively.In comparison with the identification models that encompass a single feature;either a single facial complexion feature;a body shape feature;or deep features;the accuracy of the model that incorporating all the aforementioned features was elevated by 0.105;0.105;and 0.079;the precision increased by 0.164;0.164;and 0.211;and the F1 score rose by 0.071;0.071;and 0.084;respectively.Conclusion The research findings affirmed the viability of the proposed model;which incor-porated multifeatures;including the facial complexion feature;the body shape feature;and the deep feature.In addition;by employing the proposed model;the objectification and intel-ligence of identifying constitutions in TCM practices could be optimized.

An interpretability model for syndrome differentiation of HBV-ACLF in traditional Chinese medicine using small-sample imbalanced data

Objective Clinical medical record data associated with hepatitis B-related acute-on-chronic liver failure(HBV-ACLF)generally have small sample sizes and a class imbalance.However,most machine learning models are designed based on balanced data and lack interpretability.This study aimed to propose a traditional Chinese medicine(TCM)diagnostic model for HBV-ACLF based on the TCM syndrome differentiation and treatment theory,which is clinically interpretable and highly accurate.Methods We collected medical records from 261 patients diagnosed with HBV-ACLF,including three syndromes:Yang jaundice(214 cases),Yang-Yin jaundice(41 cases),and Yin jaundice(6 cases).To avoid overfitting of the machine learning model,we excluded the cases of Yin jaundice.After data standardization and cleaning,we obtained 255 relevant medical records of Yang jaundice and Yang-Yin jaundice.To address the class imbalance issue,we employed the oversampling method and five machine learning methods,including logistic regression(LR),support vector machine(SVM),decision tree(DT),random forest(RF),and extreme gradient boosting(XGBoost)to construct the syndrome diagnosis models.This study used precision,F1 score,the area under the receiver operating characteristic(ROC)curve(AUC),and accuracy as model evaluation metrics.The model with the best classification performance was selected to extract the diagnostic rule,and its clinical significance was thoroughly analyzed.Furthermore,we proposed a novel multiple-round stable rule extraction(MRSRE)method to obtain a stable rule set of features that can exhibit the model’s clinical interpretability.Results The precision of the five machine learning models built using oversampled balanced data exceeded 0.90.Among these models,the accuracy of RF classification of syndrome types was 0.92,and the mean F1 scores of the two categories of Yang jaundice and Yang-Yin jaundice were 0.93 and 0.94,respectively.Additionally,the AUC was 0.98.The extraction rules of the RF syndrome differentiation model based on the MRSRE method revealed that the common features of Yang jaundice and Yang-Yin jaundice were wiry pulse,yellowing of the urine,skin,and eyes,normal tongue body,healthy sublingual vessel,nausea,oil loathing,and poor appetite.The main features of Yang jaundice were a red tongue body and thickened sublingual vessels,whereas those of Yang-Yin jaundice were a dark tongue body,pale white tongue body,white tongue coating,lack of strength,slippery pulse,light red tongue body,slimy tongue coating,and abdominal distension.This is aligned with the classifications made by TCM experts based on TCM syndrome differentiation and treatment theory.Conclusion Our model can be utilized for differentiating HBV-ACLF syndromes,which has the potential to be applied to generate other clinically interpretable models with high accuracy on clinical data characterized by small sample sizes and a class imbalance.

Machine learning models for stroke detection by observing the eye-movement features under five-color visual stimuli in traditional Chinese medicine

Objective:To develop a novel diagnostic modality to identify and diagnose stroke in daily life scenarios for improving the therapeutic effects and prognoses of patients.Methods:In this study,16 stroke patients and 24 age-matched healthy participants as controls were recruited for comparative analysis.Leveraging a portable eye-tracking device and integrating traditional Chinese medicine theory with modern color psychology principles,we recorded the eye movement signals and calculated eye movement features.Meanwhile,the stroke recognition models based on eye movement features were further trained by using random forest(RF),k-nearest neighbors(KNN),decision tree(DT),gradient boosting classifier(GBC),XGBoost,and CatBoost.Results:The stroke group and the healthy group showed significant differences in some eye movement features(P<.05).The models trained based on eye movement characteristics had good performances in recognizing stroke individuals,with accuracies ranging from 77.40%to 88.45%.Under the red stimulus,the eye movement model trained by RF became the best machine learning model with a recall of 84.65%,a precision of 86.48%,a F1 score of 85.47%.Among the six algorithms,RF and CatBoost performed better in classification.Conclusion:This study pioneers the application of traditional Chinese medicine's five-color stimuli to visual observation tasks.On the basis of the combined design,the eye-movement models can accurately identify stroke,and the developed high-performance models may be used in daily life scenarios.

Traditional Chinese Medicine Automated Diagnosis Based on Knowledge Graph Reasoning

Syndrome differentiation is the core diagnosis method of Traditional Chinese Medicine(TCM).We propose a method that simulates syndrome differentiation through deductive reasoning on a knowledge graph to achieve automated diagnosis in TCM.We analyze the reasoning path patterns from symptom to syndromes on the knowledge graph.There are two kinds of path patterns in the knowledge graph:one-hop and two-hop.The one-hop path pattern maps the symptom to syndromes immediately.The two-hop path pattern maps the symptom to syndromes through the nature of disease,etiology,and pathomechanism to support the diagnostic reasoning.Considering the different support strengths for the knowledge paths in reasoning,we design a dynamic weight mechanism.We utilize Naïve Bayes and TF-IDF to implement the reasoning method and the weighted score calculation.The proposed method reasons the syndrome results by calculating the possibility according to the weighted score of the path in the knowledge graph based on the reasoning path patterns.We evaluate the method with clinical records and clinical practice in hospitals.The preliminary results suggest that the method achieves high performance and can help TCM doctors make better diagnosis decisions in practice.Meanwhile,the method is robust and explainable under the guide of the knowledge graph.It could help TCM physicians,especially primary physicians in rural areas,and provide clinical decision support in clinical practice.

Investigation on the cognitive status and the infiltration path of Traditional Chinese Medicine among residents in Liaoning Province

To understand citizens’awareness,trust and attitude towards Tradition Chinese medicine(TCM),to seek the best penetration path of TCM products and culture,to analyze their influencing factors,and to provide suggestions and countermeasures,a non-probabilistic judgment sampling method was used to conduct a survey among 459 people online with the help of Questionnaire Star and 434 valid questionnaires were collected.The survey shows that residents have a high degree of recognition and identification of Chinese medicine;citizens are rational when choosing TCM products,and the recognition of the emerging TCM culture infiltration path is low.Different social and demographic factors affect citizens’awareness,trust and attitude towards TCM,as well as the choice of infiltration path(P<0.05).

Application of artificial intelligence in tongue diagnosis of traditional Chinese medicine:A review

Tongue diagnosis is an important process to non-invasively assess the condition of a patient’s internal organs in traditional Chinese medicine(TCM)and each part of the tongue is related to corresponding internal organs.Due to continuing computer technological advances,especially the artificial intelligence(AI)methods have achieved significant success in tackling tongue image acquisition,processing,and classification,novel AI methods are being introduced in traditional Chinese medicine tongue diagnosis medical practices.Traditional tongue diagnose depends on observations of tongue characteristics,such as color,shape,texture,moisture,etc.by traditional Chinese medicine physicians.The appearance of the tongue color,texture and coating reflects the improvement or deterioration of patient’s conditions.Moreover,AI can now distinguish patient’s condition through tongue images,texture or coating,which is all possible increasingly with help from traditional Chinese medicine physicians under the traditional Chinese medicine tongue theory.AI has enabled humans to do what was previously unimagined:traditional Chinese medicine tongue diagnosis with feeding a large amount of tongue image and tongue texture/coating data to train the AI modes.This review focuses on the research advances of AI in TCM tongue diagnosis thus far to identify the major scientific methods and prospects.In this article,we tried to review the AI application in resolving the tongue diagnosis of traditional Chinese medicine on color correction,tongue image extraction,tongue texture/coating segmentation.

Progress in diagnosis and treatment of small cell lung cancer with integrated traditional Chinese and Western medicine

Lung cancer is one of the most common major diseases that seriously threaten human health,lung cancer includes small cell lung cancer(SCLC)and non-small cell lung cancer(NSCLC).Although patients with SCLC account for about 20%of the total number of patients with lung cancer,the mortality rate is much higher than that of patients with NSCLC.Integrated traditional Chinese and Western medicine has obvious advantages in the treatment of patients with SCLC.According to the relevant literature reports on the treatment of SCLC in recent years,this article will summarize the research progress of integrated traditional Chinese and western medicine in the treatmentof SCLC from the aspects of traditional Chinese medicine(TCM)combined with surgery,chemotherapy,radiotherapy,and molecular targeted therapy.

Treatment of 140 cerebral palsied children with a combined method based on traditional Chinese medicine(TCM)and western medicine

Objective:To observe and evaluate a method that is effective and practical for treatment of cerebral palsied(CP)children in China.Method:The patient's age and disease type and individual specific conditions were considered in choosingtherapy methods accordingly:Chinese herbs,acupuncture,auricnlar seed pressure,point finger pressing,massage,orthopedichand manipulation,physiotherapy,occupational therapy,language therapy,etc.Meanwhile we created a new CP treatment modelthat combines hospitalized treatment with family therapy.Results:The majority of CP patients improved greatly in motor andsocial adaptation capacities after treatment.Wilcoxon paired rank sum test analysis showed that there were significant differencesbetween the data before and after treatment(P<0.01).Conclusion:This combined therapy method,based on traditional Chinesemedicine and western medicine plus family supplemental therapy,is an effective and practical treatment strategy for CP children inChina.

Analysis on medication rule of traditional Chinese medicine treating chemotherapy-induced diarrhea based on traditional Chinese medicine(TCM) inheritance computing platform system

Objective:To dig deeper into the traditional Chinese medicine treatment rules of chemotherapy-induced diarrhea with traditional Chinese medicine(TCM)inheritance computing platform system.Methods:Taking“traditional Chinese medicine”,“chemotherapy”and“diarrhea”as the theme words,comprehensive search of the database of CNKI,Wanfang and VIP from its inception to November 2020 was conduct-ed.The formulas of external treatment of traditional Chinese medicine for chemotherapy-induced diarrhea were included and the association rule,clustering and factor analysis were carried out.Results:A total of 145 papers,57 prescriptions meeting the inclusion criteria were collected,among which high-frequency drugs including Baizhu(Atractylodis macrocephalae rhizoma),Fuling(Poria),Dangshen(Codonopsisradix),Huanglian(Coptidis rhizoma),Zhigancao(Glycyrrhizae radix et rhizoma praeparata cum melle)were the most commonly used.The confidence level was set as 0.7 and the support level was set as 10,12 core compatibility groups were obtained,and 6 categories were cluster analyzed.Conclusion:The principle of external treatment of chemotherapy-induced diarrhea is mainly“restore deficiency and benefiting qi”,“benefiting water infiltration and dampness”,“clearing heat”and“inducing astringency”.Prescription combination and new prescription combination based on traditional Chinese medicine(TCM)inheritance computing platform system can be used as reference for clinicians and applied in primary hospitals.

Traditional Chinese Medicine and Standardization——Origin and development of TCM

Traditional Chinese Medicine (TCM) is the medical science based on theories and practicing experience of traditional Chinese medicine to study transferring principles of health and sickness,as well as prevention, diagnosis,treatment,rehabilitation and healthcare.TCM is marked with its long history of development,integrated theory system and abundant practicing experience.

Review: The vital role of traditional Chinese medicine (TCM) in the prevention and treatment of COVID-19 and the etiology and pathogenic mechanism of COVID-19 based on TCM theory

"Yi"is defined in traditional Chinese medicine theory as the general pathological conditions of epidemics.Throughout thousands of years of history,TCM has been playing an essential role in preventing and treating epidemics in China.Showing significant efficacy against severe acute respiratory syndrome(SARS)in 2002 and 2003,a medical intervention involving TCM was applied at the beginning of the pandemic of the corona virus disease 2019(COVID-19),and has been found with good preventive and curative value in clinical practice.In this study,the etiology and pathogenic mechanism of COVID-19 was discussed on a TCM theory basis,and the clinically effective prevention and treatment methods/prescriptions were summarized.It is suggested that TCM has been playing a unique and vital role in preventing and treating COVID-19,and thus contributes greatly to public health.

The Great Significance of Establishing Strategic Status of Traditional Chinese Medicine (TCM)

Traditional Chinese Medicine(TCM), based on the philosophic idea of “correlation between man and nature” and “balance of Yin and Yang” and characterized by “integrated concept” and “syndrome identification & treatment determination”, adjusts and activates the self-recuperating ability to rectify its differentiation from normality of human body to meet the goal of preventing and treating diseases mainly by means of traditional Chinese medicinal herbs, acupuncture and moxibustion, etc. The idea of “Human should be in harmony with Nature including bacterium, virus, etc., but not to exterminate microbe in a large scale”, held and promoted by TCM gives, rise to a delicate physiological equilibrium kept between man and microbe and this is just the development trend of medical science in future. For thousands years, TCM has made indelible contribution to the reproduction and prosperity of the Chinese nation, and under the countless attacks of pestilence has never made its people’s death in millions, not such as once occurred in Europe. TCM is also characterized by its “simple, convenient, cheap and effective”method of treatment” and is especially good at preventing and treating chronic diseases, complicate multi-system diseases and new-type virus diseases. Therefore, only when the sanitation and healthcare system is established can the health of 13 billion people in China and the problem of shortage of doctor and medicine for 900 million rural population and large number of poverty-stricken urban population be solved. It is strongly suggested that five promotion projects, namely: TCM policy and statute guarantee, TCM qualified personnel cultivation, TCM scientific research, development of TCM in rural areas and TCM administrative system reform should be carried out in real earnest to make TCM develop in a sustainable way.

A holistic strategy for quality and safety control of traditional Chinese medicines by the “iVarious” standard system

An effective quality control system is the key to ensuring the quality, safety and efficacy of traditional Chinese medicines(TCMs). However, the current quality standard research lacks top-level design and systematic design,mostly based on specific technologies or evaluation methods. To resolve the challenges and questions of quality control of TCMs, a brand-new quality standard system, named "iVarious", was proposed. The system comprises eight elements in a modular format. Meaning of every element was specifically illustrated via corresponding research instances. Furthermore, frankincense study was taken as an example for demonstrating standards and research process, based on the "i Various" system. This system highlighted a holistic strategy for effectiveness,security, integrity and systematization of quality and safety control standards of TCMs. The establishment of"i Various" integrates multi-disciplinary technologies and progressive methods, basis elements and key points of standard construction. The system provides a novel idea and technological demonstration for regulation establishment of TCMs quality standards.

Applications of HPLC/MS in the analysis of traditional Chinese medicines

In China, traditional Chinese medicines （TCMs） have been used in clinical applications for thousands of years. The successful hyphenation of high-performance liquid chromatography （HPLC） and mass spectrometry （MS） has been applied widely in TCMs and biological samples analysis. Undoubtedly, HPLC/MS technique has facilitated the understanding of the treatment mechanism of TCMs. We reviewed more than 350 published papers within the last 5 years on HPLC/MS in the analysis of TCMs. The present review focused on the applications of HPLC/MS in the component analysis, metabolites analysis, and pharmacokinetics of TCMs etc. 50% of the literature is related to the component analysis of TCMs, which show that this field is the most popular type of research. In the metabolites analysis, HPLC coupled with electrospray ionization quadrupole time-of-flight tandem mass spectrometry has been demonstrated to be the powerful tool for the characterization of structural features and fragmentation behavior patterns. This paper presented a brief overview of the applications of HPLC/MS in the analysis of TCMs. HPLC/MS in the fingerprint analysis is reviewed elsewhere.

Study progress in therapeutic effects of traditional Chinese medicine monomer in severe acute pancreatitis

Severe acute pancreatitis (SAP) is a common acute abdomen clinical problem characterized by high mortality, mul-tiple complications, complicated pathogenesis and difficult treatment. Recent studies found traditional Chinese medicine (TCM) monomers have markedly good effect for treating SAP. Many TCM monomers can inhibit pancreatin, resist inflammation, im-prove microcirculation and immunoloregulation, etc. to block the pathological progress of SAP in multiple ways, reduce com-plications and lower mortality with rapid effects. It is significant for enhancing SAP treatment to deeply understand the current situation in TCM monomers for treating SAP and take precious references therein. This article summarizes the treating effects and mechanisms of TCM monomers for SAP in recent years.

Early metabolism evaluation making traditional Chinese medicine effective and safe therapeutics

Increasing attention is being paid to the scientific evaluation of traditional Chinese medicine （TCM）. As many TCMs are capable of biotransformation in the gastrointestinal tract, attention to biotransforrnation of TCM in the gastrointestinal tract may lead to discovery of the active components and active mechanisms. In this article, we review reports that host metabolic enzymes and intestinal bacteria may be responsible for the metabolism of TCM. Good understanding of the in vivo course of TCM will help us to know how to conduct metabolism evaluation of TCM by using in vitro human-derived system. This evaluation system will create new views on TCM as effective and safe therapeutic agents.

A General Introduction of HIV/AIDS Treatment with Traditional Chinese Medicine in China

This paper gives a general introduction of HIV/AIDS treatment with Traditional Chinese Medicine (TCM) in China during the past 20 years. Although the role of TCM in treatment of HIV/AIDS is promising,there is still a long way to go.

Terahertz spectrum clustering of traditional Chinese medicine based on first derivative characteristics

In order to deal with the unclear absorption peak caused by the absorption peak overlap of traditional Chinese medicine(TCM)and other mixtures,a method of three unsupervised clustering algorithms as K-means,K-medoids and Fuzzy C-means(FCM)combined with the first derivative characteristics of terahertz absorption spectrum,is proposed to perform the terahertz spectra clustering of Sanchi and other three kinds of TCM compared with their easily-confused products(ECPs).These three unsupervised clustering methods complement the scope of the supervised learning classification method.The first derivative of the spectrum could amplify the difference in the absorption coefficient with different substances,so that the obvious absorption peak can be revealed.Experiments shows that these three clustering algorithms can achieve good results by combining the origin absorption coefficient with its first-order derivative as the characteristic data,and among which K-means does the best with the accuracy of95.32%.Compared with pure absorption coefficient data clustering,the accuracy in this study has been significantly improved,especially for the non-absorption-peak TCM classification.And the accuracy of K-means algorithm is improved by5.38%.Besides,clustering algorithms in this study have strong anti-interference ability to the error data.