Traditional Chinese Medicine Diagnosis Research Articles

Progress in traditional Chinese medicine diagnosis and treatment of hepatic myelopathy

Progress in traditional Chinese medicine diagnosis and treatment of hepatic myelopathy

[Expert consensus on integrated traditional Chinese and western medicine diagnosis and treatment for osteoporotic fractures].

Osteoporotic fractures represent the most severe complications of osteoporosis,characterized by insidious onset,high mortality and disability rates,and a steadily increasing incidence,imposing a significant socioeconomic burden. Western medicine has advantages in diagnosis and surgical interventions,while traditional Chinese medicine excels in holistic management and the restoration of bodily equilibrium. The integration of both traditional Chinese medicine (TCM) and western medicine emerges as an effective therapeutic strategy for osteoporotic fractures. In order to propagate the concept of integrated diagnosis and treatment,foster the advancement of integrated medical techniques for osteoporotic fractures,and establish standardized and normative protocols for disease prevention,diagnosis,and treatment,a consensus expert group,led by Geriatric Branch of Chinese Geriatrics Society,the Young Osteoporosis Group of Orthopedics Branch of Chinese Medical Association,Osteoporosis Group of Orthopedics Branch of Chinese Physician Association,and Osteoporosis Professional Committee of the Shanghai Society of Integrated Traditional Chinese and Western Medicine,was established. This group engaged in deliberations and formulated the "Expert Consensus on Integrated Traditional Chinese and Western Medicine Diagnosis and Treatment of Osteoporotic Fractures" elucidating the concept of integrated medicine and offering recommendations in the domains of prevention,diagnosis,and treatment,with the aspiration of ameliorating the prognosis of osteoporotic fractures and enhancing the quality of life for these patients.

Tongue feature dataset construction and real-time detection.

Tongue diagnosis in traditional Chinese medicine (TCM) provides clinically important, objective evidence from direct observation of specific features that assist with diagnosis. However, the current interpretation of tongue features requires a significant amount of manpower and time. TCM physicians may have different interpretations of features displayed by the same tongue. An automated interpretation system that interprets tongue features would expedite the interpretation process and yield more consistent results. This study applied deep learning visualization to tongue diagnosis. After collecting tongue images and corresponding interpretation reports by TCM physicians in a single teaching hospital, various tongue features such as fissures, tooth marks, and different types of coatings were annotated manually with rectangles. These annotated data and images were used to train a deep learning object detection model. Upon completion of training, the position of each tongue feature was dynamically marked. A large high-quality manually annotated tongue feature dataset was constructed and analyzed. A detection model was trained with average precision (AP) 47.67%, 58.94%, 71.25% and 59.78% for fissures, tooth marks, thick and yellow coatings, respectively. At over 40 frames per second on a NVIDIA GeForce GTX 1060, the model was capable of detecting tongue features from any viewpoint in real time. This study constructed a tongue feature dataset and trained a deep learning object detection model to locate tongue features in real time. The model provided interpretability and intuitiveness that are often lacking in general neural network models and implies good feasibility for clinical application.

ENHANCING TONGUE REGION SEGMENTATION THROUGH SELF-ATTENTION AND TRANSFORMER BASED

As an essential component of traditional Chinese medicine diagnosis, tongue diagnosis has faced limitations in clinical practice due to its subjectivity and reliance on the experience of physicians. Recent advancements in deep learning techniques have opened new possibilities for the automated analysis and diagnosis of tongue images. In this paper, we collected 500 tongue images from various patients. These images were initially preprocessed and annotated, resulting in the dataset used for this experiment. This project is based on the previously proposed segmentation method using Harnessing Self-Attention and Transformer, which is divided into three key stages: feature extraction, feature fusion, and segmentation prediction. By organically combining these three key stages, our tongue region segmentation model is better equipped to handle complex tongue images and provides accurate segmentation results. The segmentation DICE coefficient reaches 0.953, which is of significant importance for the automation and objectivity of tongue diagnosis in traditional Chinese medicine.

Guiding modern traditional Chinese medicine research using the theory of state‐target differentiation and treatment—Maintaining the validity of traditional Chinese medicine and creating new medical science

AbstractAs an important part of Chinese civilization, traditional Chinese medicine (TCM) has a long history and broad social foundation. In the development of modern medicine, TCM bears the responsibility of inheriting Chinese culture, while integrating with modern science and technology to continuously promote medical progress. The theory of “state‐target differentiation and treatment” is an innovative model combining Chinese and Western medicine that has provided a new mindset and method for modernizing TCM. This theory not only guides the reconstruction of modern TCM diagnosis and treatment systems, but also strongly promotes the reconstruction of the modern herbal system. As an emerging bioinformatics technology, phenomics research can reveal biological processes dynamically and quantitatively, which will help “open the black box” of TCM by providing technical methods to reveal the nature of “state” and the mechanism of “state modulation” in TCM. TCM can provide a valuable clinical reference from the perspective of disease cognition, sort out phenomics information parameters systematically and uniformly, and provide more accurate and meaningful data for phenomics research. The in‐depth combination of TCM and phenomics from the concept and technology will vigorously promote the development of human precision medicine. Modern TCM research guided by the theory of state‐target differentiation and treatment can effectively improve the scientific basis and targetability of clinical treatments and can also initiate a breakthrough in the integration of Chinese and Western medicine, further promoting the profound communication and cooperation between Chinese and Western medicine, so as to achieve better development of medicine in the future.

Construction and Application of a Traditional Chinese Medicine Syndrome Differentiation Model for Dysmenorrhea Based on Machine Learning.

Dysmenorrhea is one of the most common ailments affecting young and middle-aged women, significantly impacting their quality of life. Traditional Chinese Medicine (TCM) offers unique advantages in treating dysmenorrhea. However, an accurate diagnosis is essential to ensure correct treatment. This research integrates the age-old wisdom of TCM with modern Machine Learning (ML) techniques to enhance the precision and efficiency of dysmenorrhea syndrome differentiation, a pivotal process in TCM diagnostics and treatment planning. A total of 853 effective cases of dysmenorrhea were retrieved from the CNKI database, including patients' syndrome types, symptoms, and features, to establish the TCM information database of dysmenorrhea. Subsequently, 42 critical features were isolated from a potential set of 86 using a selection procedure augmented by Python's Scikit-Learn Library. Various machine learning models were employed, including Logistic Regression, Random Forest Classifier, Support Vector Machine (SVM), K-Nearest Neighbors (KNN), and Artificial Neural Networks (ANN), each chosen for their potential to unearth complex patterns within the data. Based on accuracy, precision, recall, and F1-score metrics, SVM emerged as the most effective model, showcasing an impressive precision of 98.29% and an accuracy of 98.24%. This model's analytical prowess not only highlighted the critical features pivotal to the syndrome differentiation process but also stands to significantly aid clinicians in formulating personalized treatment strategies by pinpointing nuanced symptoms with high precision. The study paves the way for a synergistic approach in TCM diagnostics, merging ancient wisdom with computational acuity, potentially innovating the diagnosis and treatment mode of TCM. Despite the promising outcomes, further research is needed to validate these models in real-world settings and extend this approach to other diseases addressed by TCM.

Research on the model of automatic recognition and natural language question-answer system for traditional Chinese medicine tongue images based on LLMs

Large Language Models (LLMs) have recently demonstrated their potential in clinical applications by providing valuable medical knowledge and recommendations. Traditional Chinese tongue diagnosis, one of the "Four Diagnoses," is an essential method for traditional Chinese medicine diagnosis. This paper builds upon tongue image classification technology and utilizes natural language processing and image recognition techniques to enhance the discrimination and analysis of traditional Chinese tongue images through learning and inference. We propose a method to integrate LLMs into the tongue image automatic recognition model and use them in interactive question-answering by summarizing and reorganizing information in natural language text format.

THE USE OF REFLEXOLOGY ACCORDING TO THE “BALANCING HEXAGRAMS” TECHNIQUE IN THE COMPLEX REHABILITATION OF ARTHROPATHIES

Abstract. Traditional Chinese medicine is half syndromes, not diseases. This is the identification of a wider range of problems than just individual nosologies: usually, this is a comorbidity, with regular involvement of other tissues, other systems. For example, the syndrome of traditional Chinese medicine "Congestion of the liver" includes the facilitated formation of various pain syndromes in a person, often their combination, and not just a liver disease such as hepatitis. Similarly, Bi syndrome includes more than just "pain in the knee" or osteoarthritis of the knee joint. The article describes the concept of Bi syndrome in traditional Chinese medicine, its classification. The article also presents the main theoretical principles of the "balancing hexagrams" method and its practical implementation. Also given is a clinical case: treatment of a patient with subacute postinfectious arthropathy of the right sphenoid and ankle joints. Purpose. To consider the peculiarities of the use of reflexotherapy by the method of "balancing hexagrams" in the complex rehabilitation of arthropathies. Scientific novelty. For the first time in our country, the technique of compiling acupuncture prescriptions and acupuncture using the method of "balancing hexagrams" was used in the complex rehabilitation of arthropathies. Methods. We consider one clinical case of the use of reflexology using the method of "balancing hexagrams" in complex rehabilitation of arthropathies. The methods of clinical objective neurological examination, the method of syndromic diagnosis of traditional Chinese medicine, the pulse diagnosis method, and the tongue diagnosis method were used. We consider one clinical case of the use of reflexotherapy using the method of "balancing hexagrams" in complex rehabilitation of arthropathies. The methods of clinical objective neurological examination, the method of syndromic diagnosis of traditional Chinese medicine, the pulse diagnosis method, and the tongue diagnosis method were used. Results. As a result of treatment using the method of "balancing hexagrams", the patient's condition improved: it was possible to balance him and achieve a pain-free period. Conclusions. 1. Patients with arthropathies are found in the practice of a reflexologist. 2. The use of the acupuncture method "balancing hexagrams" can be effective in the complex of treatment measures for arthropathies.

APPLICATION OF REFLEXOTHERAPY ACCORDING TO THE METHOD OF “BALANCING HEXAGRAMS” IN COMPLEX REHABILITATION OF NEUROPATHY OF THE RADIAL NERVE

Abstract. The article is devoted to one of the most pressing problems of neurology – neuropathy of peripheral nerves. Often, various diseases, especially those aggravated under the influence of psycho-emotional stress and other adverse psychosocial factors, are accompanied by long-term symptoms. Medicinal methods of treatment are not fully effective, so it is necessary to resort to non-medicinal technologies. Combined treatment of neuropathy of peripheral nerves by reflexotherapy methods has been used for a long time, mainly when there is a delay in the recovery of their functions, and first of all, their motor functions. Purpose. To consider the features of the use of reflexology by the method of "balancing hexagrams" in the complex rehabilitation of neuropathy of the radial nerve with a prolonged course. Scientific novelty. For the first time in our country, the method of making acupuncture prescriptions and acupuncture using the method of "balancing hexagrams" was used in the complex rehabilitation of neuropathy of the radial nerve with a prolonged course. Methods. We consider one clinical case of the use of reflexology using the method of "balancing hexagrams" in the complex rehabilitation of radial nerve neuropathy. The methods of clinical objective neurological examination, the method of syndromic diagnosis of traditional Chinese medicine, the pulse diagnosis method, and the tongue diagnosis method were used. Results. As a result of treatment using the "balancing hexagrams" method, the patient's condition improved: first of all, the functions of the radial nerve improved, the trophic and motor activity of the muscles it innervates has improved. Conclusions. 1. Patients with neuropathy of the radial nerve with a prolonged course are seen in the practice of a neurologist and a reflexologist. 2. The use of the acupuncture method "balancing hexagrams" can be effective in the complex of treatment measures for neuropathy of the radial nerve with a prolonged course.

REFLEXOTHERAPY ACCORDING TO THE “BALANCE OF HEXAGRAMS” METHOD IN THE COMPLEX REHABILITATION OF DISEASES WITH PAIN SYNDROME

Abstract. The article raises the following topical issues – complex treatment of diseases with pain syndrome: disorders of functions of the gastrointestinal tract abd cephalalgias. Various diseases, especially those that occur with a pain syndrome, and those that are aggravated adverse psychosocial factors, manifest themselves with a protracted course. Medicinal methods of treatment are not fully effective, so non-medicinal technologies should be resorted to. Combined treatment using reflexotherapy methods has been used for a various diseases, it is especially when other methods are insufficiently effective . The article as well presents the main theoretical principles of the "Balancing of Hexagrams" method and its practical implementation. A two clinical case is also presented: a patient with subacute gastritis with psychoemotional disorders and patient with cephalalgia of the occipital area with cervico-brachialgia. Summing up, it should be noted that patients with diseases of the gastrointestinal tract with psychoemotional disorders and patients with cephalalgia of the occipital region with cervico-brachialgia are seen in the practice of neurologists and reflexologists. In the complex of therapeutic measures for diseases of the gastrointestinal tract with psychoemotional disorders and cephalalgia of the occipital region with cervico-brachialgia, the use of the acupuncture method “balancing hexagrams” can be effective. Purpose. To consider the peculiarities of the use of reflexotherapy by the method of “balancing hexagrams” in the complex rehabilitation of patients with diseases of the gastrointestinal tract with pain syndrome, cephalgia of the occipital region. Scientific novelty. For the first time in our country, the technique of making acupuncture prescriptions and acupuncture using the method of “balancing hexagrams” was used in the complex rehabilitation of patients with diseases of the gastrointestinal tract with pain syndrome, cephalgia of the occipital region. Methods. We consider two clinical cases of the use of reflexology using the method of “balancing hexagrams” in the complex rehabilitation of patients with diseases of the gastrointestinal tract with pain syndrome, cephalgia of the occipital region. The methods of clinical objective neurological examination, the method of syndromic diagnosis of traditional Chinese medicine, the pulse diagnosis method, and the tongue diagnosis method were used. Results. As a result of treatment using the “balancing hexagrams” method, the condition of the patients improved: in the first case, the pathological manifestations of the gastrointestinal tract, back pain decreased, in the second case, the frequency and intensity of headaches in the back of the head, pain in the right arm decreased. Conclusions: 1. In the practice of a reflexologist, gastritis is encountered, and with this disease, reflexology methods are effective first of all for psycho-emotional disorders. 2. In the complex of treatment measures for gastritis, the use of the acupuncture method "balancing hexagrams" can be effective. 3. For headaches in the occipital region and cervicobrachialgia in complex rehabilitation, the use of the acupuncture method “balancing hexagrams” can also be effective.

Differential clinical characteristics across traditional Chinese medicine (TCM) Syndromes in patients with sickle cell disease.

Pain is a common, debilitating, and poorly understood complication of sickle cell disease (SCD). The need for clinical pain management of SCD is largely unmet and relies on opioids as the main therapeutic option, which leads to a decreased quality of life (QoL). According to the literature, acupuncture has shown certain therapeutic effects for pain management in SCD. However, these clinical studies lack the guidance of Traditional Chinese Medicine (TCM) Syndrome Differentiation principles for treatment. To characterize differences in clinical presentation amongst TCM diagnosed Syndromes in SCD patients. Fifty-two patients with SCD and 28 age- and sex-matched healthy controls (HCs) were enrolled in an ongoing trial of acupuncture. Each participant completed a series of questionnaires on pain, physical function, fatigue, sleep, anxiety, depression and QoL and underwent cold- and pressure-based quantitative sensory testing at baseline. Data on prescription opioid use over the 12 months prior to study enrollment was used to calculate mean daily morphine milligram equivalents (MME). Differences among the three TCM Syndromes were analyzed by one-way ANOVA followed by Tukey post hoc testing. Two-sample t-tests were used to compare SCD and HC groups. TCM diagnosis criteria classified SCD patients into one of three TCM Syndromes: (a) Equal; (b) Deficiency; and (c) Stagnation. The Stagnation group exhibited higher pain interference, physical dysfunction, nociplastic pain, fatigue, anxiety, depression, MME consumption and lower sleep quality and QoL compared to the Equal group. Few differences were observed between HCs and the Equal SCD group across outcomes. Deficiency and Stagnation groups were differentiated with observed- and patient-reported clinical manifestations. These findings suggest that TCM diagnosed Syndromes in SCD can be differentially characterized using validated objective and patient-reported outcomes. Because characteristics of pain and co-morbidities in each SCD patient are unique, targeting specific TCM "Syndromes" may facilitate treatment effectiveness with a Syndrome-based personalized treatment plan that conforms to TCM principles. These findings lay the foundation for the development of tailored acupuncture interventions based on TCM Syndromes for managing pain in SCD. Larger samples are required to further refine and validate TCM diagnostic criteria for SCD.

Progress in Traditional Chinese and Western Medicine Diagnosis and Treatment of Brucella Spondylitis

Progress in Traditional Chinese and Western Medicine Diagnosis and Treatment of Brucella Spondylitis

A serum metabolomics study of vascular cognitive impairment patients based on Traditional Chinese medicine syndrome differentiation.

Objective: Vascular cognitive impairment (VCI) accounts for approximately 50%-70% of all dementia cases and poses a significant burden on existing medical systems. Identifying an optimal strategy for preventing VCI and developing efficient symptomatic treatments remains a significant challenge. Syndrome differentiation represents a fundamental approach for personalized diagnosis and treatment in Traditional Chinese Medicine (TCM) and aligns with the principles of precision medicine. The objective of this study was to elucidate the metabolic characteristics of VCI based on TCM syndrome differentiation, thus providing novel insights into the diagnosis and treatment of VCI. Methods: A 2-year cross-sectional cognitive survey was conducted in four communities in Beijing between September 2020 and November 2022. The syndrome differentiation of participants was based on the Kidney-Yang Deficiency Syndrome Scale (KYDSS), which was originally developed by Delphi expert consultation. The identification of serum metabolites was performed by Ultra performance liquid chromatography (UPLC) analysis coupled with an electrospray ionization quadruple time-of-flight mass spectrometer (ESI-QTOF MS). Multivariate, univariate, and pathway analyses were used to investigate metabolic changes. Logistic regression models were also used to construct metabolite panels that were capable of discerning distinct groups. Phospholipase A2 (PLA2) levels were measured by a commercial ELISA kit. Results: A total of 2,337 residents completed the survey, and the prevalence of VCI was 9.84%. Of the patients with VCI, those with Kidney-Yang deficiency syndrome (VCIS) accounted for 70.87% of cases and exhibited more severe cognitive impairments. A total of 80 participants were included in metabolomics study, including 30 with VCIS, 20 without Kidney-Yang deficiency syndrome (VCINS), and 30 healthy control participants (C). Ultimately, 45 differential metabolites were identified when comparing the VCIS group with group C, 65 differential metabolites between the VCINS group and group C, and 27 differential metabolites between the VCIS group and the VCINS group. The downregulation of phosphatidylethanolamine (PE), and phosphatidylcholine (PC) along with the upregulation of lysophosphatidylethanolamine (LPE), lysophosphatidylcholine (LPC), phosphatidic acid (PA) and phospholipase A2 (PLA2) can be considered as the general metabolic characteristics associated with VCI. Dysfunction of glycerophospholipids, particularly LPEs and PCs, was identified as a key metabolic characteristic of VCIS. In particular Glycerophospho-N-Arachidonoyl Ethanolamine (GP-NArE) was discovered for the first time in VCI patients and is considered to represent a potential biomarker for VCIS. The upregulation of PLA2 expression was implicated in the induction of alterations in glycerophospholipid metabolism in both VCIS and VCINS. Moreover, robust diagnostic models were established based on these metabolites, achieving high AUC values of 0.9322, 0.9550, and 0.9450, respectively. Conclusion: These findings contribute valuable information relating to the intricate relationship between metabolic disorders in VCI, neurodegeneration and vascular/neuroinflammation. Our findings also provide a TCM perspective for the precise diagnosis and treatment of VCI in the context of precision medicine.

TLDA: A transfer learning based dual-augmentation strategy for traditional Chinese Medicine syndrome differentiation in rare disease

The Traditional Chinese Medicine (TCM) has demonstrated its significant medical value over the decades, particularly during the COVID-19 pandemic. TCM-AI interdisciplinary models have been proposed to model TCM knowledge, diagnosis, and treatment experiments in clinical practice. Among them, numerous models have been developed to simulate the syndrome differentiation process of human TCM doctors for automatic syndrome diagnosis. However, these models are designed for normal scenarios and trained using a supervised learning paradigm which needs tens of thousands of training samples. They fail to effectively differentiate syndromes in rare disease scenarios where the available TCM electronic medical records (EMRs) are very limited for each unique syndrome. To address the challenge of rare diseases, this study proposes a simple yet effective method called Transfer Learning based Dual-Augmentation (TLDA). TLDA aims to augment the limited EMRs at both the sample-level and feature-level, enriching the pathological and medical information during training. Extended experiments involving 11 comparison models, including the state-of-the-art model, demonstrate the effectiveness of TLDA. TLDA outperforms all comparison models by a significant margin. Furthermore, TLDA can also be extended to other medical tasks when the EMRs for diagnosis are limited in samples.

Application of Metabolomics and Traditional Chinese Medicine for Type 2 Diabetes Mellitus Treatment.

Diabetes is a major global public health problem with high incidence and case fatality rates. Traditional Chinese medicine (TCM) is used to help manage Type 2 Diabetes Mellitus (T2DM) and has steadily gained international acceptance. Despite being generally accepted in daily practice, the TCM methods and hypotheses for understanding diseases lack applicability in the current scientific characterization systems. To date, there is no systematic evaluation system for TCM in preventing and treating T2DM. Metabonomics is a powerful tool to predict the level of metabolites in vivo, reveal the potential mechanism, and diagnose the physiological state of patients in time to guide the follow-up intervention of T2DM. Notably, metabolomics is also effective in promoting TCM modernization and advancement in personalized medicine. This review provides updated knowledge on applying metabolomics to TCM syndrome differentiation, diagnosis, biomarker discovery, and treatment of T2DM by TCM. Its application in diabetic complications is discussed. The combination of multi-omics and microbiome to fully elucidate the use of TCM to treat T2DM is further envisioned.

[Review and prospect of traditional Chinese medicine in treatment of hypertension].

Hypertension, a primary cause of cardiovascular and cerebrovascular events, has become a major global public health problem and caused a heavy burden of health economics on the society. In "the 20 Most Important and Most Preventable Health Problems" released by the Chinese Academy of Engineering, hypertension was ranked the second. Due to the disease complexity, many hypertension patients need to take antihypertensive drugs for life. Although significant progress has been achieved in blood pressure lowering by western medicines, the problems including adverse reactions, poor compliance due to long-term medication, and ineffective mitigation in clinical symptoms related to hypertension remain to be addressed. In the last decade, the research on traditional Chinese medicine(TCM) treatment of hypertension has received much attention and achieved remarkable progress. The TCM treatment of hypertension is the most active area of research with integrated Chinese and western medicine in China. In addition to lowering blood pressure smoothly, TCM can alleviate clinical symptoms, reverse risk factors, improve the quality of life, and protect target organs from the damage caused by hypertension. This article systematically reviews the research progress of TCM in treating hypertension in the last decade from the following four aspects: consensus on guideline, clinical trial, experimental study, and systematic review/Meta-analysis. It summarized the evidence of TCM in reducing blood pressure and clarified the mechanism of TCM in reducing blood pressure, aiming to provide a reference for the TCM diagnosis and treatment of hypertension and the development of new drugs.

Strategy for Targeting Medical Diagnosis of Cerebral Ischemia Regions by Linking Gsk-3β Antibody and RVG29 to Magnetosomes

Background: In our previous studies, we have identified Gsk-3β as a crucial target molecule in response to Danhong injection for cerebral ischemia intervention. Furthermore, it can serve as a molecular imaging probe for medical diagnosis. Bacterial magnetic particles (BMPs), synthesized by magnetotactic bacteria, are regarded as excellent natural nanocarriers. Methods: In this study, we utilized biological modification and chemical crosslinking techniques to produce a multifunctional BMP known as "RVG29-BMP-FA-Gsk-3β-Ab", which exhibits both magnetic properties and brain-targeting capabilities. Then, a combination of analytical techniques was used to characterize the properties of the multifunctional BMPs. Finally, we evaluated the cell targeting ability of the RVG29-BMP-FA-Gsk-3β-Ab. Results: The multifunctional BMPs were observed to possess uniform size and shape using TEM analysis, with a particle size of 70.1±7.33 nm. Zeta potential analysis revealed that the nanoparticles exhibited a regular and non-aggregative distribution of particle sizes. Relative fluorescence intensity results demonstrated that the complex of 1mg of RVG29-BMP-FA-Gsk- 3β-Ab could bind to FITC-RVG29 polypeptide at a concentration of 2189.5 nM. Cell viability analysis indicated its high biocompatibility and minimal cytotoxicity. The RVG29-BMP-FAGsk- 3β-Ab was observed to possess active targeting towards neuronal cells and fluorescence imaging capabilities in vitro, as evidenced by fluorescence imaging assays. The complex of RVG29-BMP-FA-Gsk-3β-Ab exhibited favourable properties for early diagnosis and efficacy evaluation of traditional Chinese medicine in treating cerebral ischemia. Conclusion: This study establishes a fundamental basis for the prospective implementation of multimodal imaging in traditional Chinese medicine for cerebral ischemia.

Machine learning classification of polycystic ovary syndrome based on radial pulse wave analysis.

Patients with Polycystic ovary syndrome (PCOS) experienced endocrine disorders that may present vascular function changes. This study aimed to classify and predict PCOS by radial pulse wave parameters using machine learning (ML) methods and to provide evidence for objectifying pulse diagnosis in traditional Chinese medicine (TCM). A case-control study with 459 subjects divided into a PCOS group and a healthy (non-PCOS) group. The pulse wave parameters were measured and analyzed between the two groups. Seven supervised ML classification models were applied, including K-Nearest Neighbors (KNN), Support Vector Machine (SVM), Decision Trees, Random Forest, Logistic Regression, Voting, and Long Short Term Memory networks (LSTM). Parameters that were significantly different were selected as input features and stratified k-fold cross-validations training was applied to the models. There were 316 subjects in the PCOS group and 143 subjects in the healthy group. Compared to the healthy group, the pulse wave parameters h3/h1 and w/t from both left and right sides were increased while h4, t4, t, As, h4/h1 from both sides and right t1 were decreased in the PCOS group (P < 0.01). Among the ML models evaluated, both the Voting and LSTM with ensemble learning capabilities, demonstrated competitive performance. These models achieved the highest results across all evaluation metrics. Specifically, they both attained a testing accuracy of 72.174% and an F1 score of 0.818, their respective AUC values were 0.715 for the Voting and 0.722 for the LSTM. Radial pulse wave signal could identify most PCOS patients accurately (with a good F1 score) and is valuable for early detection and monitoring of PCOS with acceptable overall accuracy. This technique can stimulate the development of individualized PCOS risk assessment using mobile detection technology, furthermore, gives physicians an intuitive understanding of the objective pulse diagnosis of TCM. Not applicable.

Machine learning-based evaluation of application value of traditional Chinese medicine clinical index and pulse wave parameters in the diagnosis of polycystic ovary syndrome

IntroductionPolycystic ovary syndrome (PCOS) is a prevalent endocrine disorder in women that often leads to ovulatory infertility. This study aims to establish and validate an effective predictive model for PCOS and to explore the correlation of features between patients with irregular menstruation and those with PCOS, using pulse wave parameters and traditional Chinese medicine (TCM) clinical indices. MethodsFrom August 2018 to January 2022, women with irregular menstruation were enrolled in this study. Subjects who met the inclusion criteria were categorized into PCOS and non-PCOS groups based on diagnostic criteria. Pulse wave parameters and TCM clinical indices were collected by two medical professionals. After data cleaning, recursive feature elimination with cross-validation (RFECV) was used for feature selection. Four supervised machine learning classifiers were used to build PCOS prediction models, including Extra Trees (ET), Random Forest (RF), Extreme Gradient Boosting (XGB/XGBoost), and Support Vector Machine (SVM). The SHapley Additive exPlanation (SHAP) values based on the optimal model were visualized for further feature explanation. ResultsA total of 450 women with irregular periods were enrolled in the study, consisting of 294 patients with PCOS and 156 without PCOS. Based on RFECV, 31 features, including 12 pulse parameters and 19 TCM clinical indices, were selected for building prediction models. Using pulse and TCM clinical index was superior to using pulse parameters or TCM clinical index alone in prediction. SVM achieved the best PCOS prediction results (accuracy=0.837, AUC=0.878, F1 score=0.878). For pulse parameters, lower values of right As, right h4, left h1, left h3, left h5, left w/t, and higher right t5 showed an obvious positive PCOS predictive effect. Women with PCOS were more likely to experience delayed menstruation, negative emotions, a slightly jelly-like menstrual texture, higher BMI, and a TCM assessment of greasy tongue coating. ConclusionA PCOS prediction model based on the SVM algorithm was established and verified as the best model for distinguishing between patients with PCOS and patients without PCOS with irregular menstruation. The new prediction model that uses pulse wave parameters and TCM clinical indices offers a non-invasive and cost-effective way to diagnose PCOS, and the model provides objective evidence for TCM diagnosis.

[Expert consensus for diagnosis and treatment of post-cardiac arrest syndrome in adults by combining traditional Chinese and Western medicine in China (2023)].

Reperfusion injury occurs after return of spontaneous circulation (ROSC) in patients with cardiac arrest (CA), which leads to multiple organ dysfunction, called post-cardiac arrest syndrome (PCAS). PCAS is closely related to the prognosis of CA patients, and is an independent risk factor of survival. Integrated traditional Chinese and Western medicine diagnosis and treatment is critical for improving prognosis of PCAS. In order to guide and standardize integrated traditional Chinese and Western medicine diagnosis and treatment in PCAS among clinicians, nurses and research personnel in China, the Emergency Medicine Professional Committee of the Chinese Society of Integrated Chinese and Western Medicine has established an expert group to determine 14 clinical issues related to the diagnosis and treatment of PCAS with integrated traditional Chinese and Western medicine through clinical survey. The working group formulates a search strategy for each clinical issue according to the PICO principle. Chinese and English literature were searched from CNKI, Wanfang, VIP, SinoMed, PubMed, Embase, and Cochrane Library. The grade of recommendations assessment, development and evaluation (GRADE) were used to form the level of evidence and recommendation. When the literature evidence was insufficient, the recommendations and level of recommendation were formed after expert discussion. Combined with the aspects of generalizability, suitability, and resource utilization, the expert consensus developed 28 recommendations around the 14 aspects of three stages of PCAS, including early circulation, respiratory support and reversible cause relief, mid-term neuroprotection, improvement of coagulation, prevention and treatment of infection, kidney and gastrointestinal protection and blood sugar control, post rehabilitation treatment, providing references for the integrated traditional Chinese and Western medicine of the diagnosis and treatment for PCAS.