Theory of Dynamic Diagnosis Based on Integrated Maintenance Information

Based on the concept of an integrated maintenance information system and related information environment, this paper discusses the process of troubleshooting in modern maintenance in detail, and gives a model of dynamic diagnosis of faults, in which a reasoning program is designed through taking advantage of information fusion and time analysis. In the end, the authors present the logic process of dynamic diagnosis through a typical example, and proposes a dynamic diagnostic system based on information fusion.

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.

A Study on Integrated Wavelet Neural Networks in Fault Diagnosis Based on Information Fusion

The tight wavelet neural network was constituted by taking the nonlinear Morlet wavelet radices as the excitation function. The idiographic algorithm was presented. It combined the advantages of wavelet analysis and neural networks. The integrated wavelet neural network fault diagnosis system was set up based on both the information fusion technology and actual fault diagnosis, which took the sub-wavelet neural network as primary diagnosis from different sides, then came to the conclusions through decision-making fusion. The realizable policy of the diagnosis system and established principle of the sub-wavelet neural networks were given. It can be deduced from the examples that it takes full advantage of diversified characteristic information, and improves the diagnosis rate.

Fuzzy Integral Theory and Its Application in Fault Intelligent Integrated Diagnosis

In this paper, by employing the idea of 'dispersion first, then concentration'' adhering to the biological perceptual system, an idea of the multi-symptom-domain based fault consensus diagnosis is developed. From the point of group decision-making, the method based on neural networks to realize this diagnosis idea is studied, and a particular multi-symptom-domain based diagnosis strategy is proposed, which is based on fuzzy integral theory. Finally, a case study is given. The research results show that the proposed diagnosis strategy is available and more efficient than conventional methods.

A unified model for diagnosing energy usage abnormalities in regional integrated energy service systems

An integrated energy service company in an industrial park or commercial building is responsible for managing all energy sources in their local region, including electricity, water, gas, heating, and cooling. To reduce energy wastage and increase energy utilization, it is necessary to perform efficiency analyses and diagnoses on integrated energy systems(IESs). However, the integrated energy data necessary for energy efficiency analyses and diagnoses come from a wide variety of instruments, each of which uses different transmission protocols and data formats. This makes it challenging to handle energy-flow data in a unified manner. Thus, we have constructed a unified model for diagnosing energy usage abnormalities in IESs. Using this model, the data are divided into working days and non-working days, and benchmark values are calculated after the data have been weighted to enable unified analysis of several types of energy data. The energy-flow data may then be observed, managed, and compared in all aspects to monitor sudden changes in energy usage and energy wastage. The abnormal data identified and selected by the unified model are then subjected to big-data analysis using technical management tools, enabling the detection of user problems such as abnormalities pertaining to acquisition device, metering, and energy usage. This model facilitates accurate metering of energy data and improves energy efficiency. The study has significant implications in terms of fulfilling the energy saving.

Research on a Diagnosis Method Based on a Correlation Integral

For the first time, the diagnosis idea based on a correlation integral isproposed, which regard's the correlation integral as a feature set. The correlation dimension iscontained in the double-log curve of the correlation integral to scale, so extracting featuresdirectly from the correlation integral can avoid the bottleneck problem of determining the range ofnon-scale length. Several features extracted from the correlation integral are better than thesingle feature of the correlation dimension when describing the signal. It is obvious that thismethod utilizes more information of the signal than does the correlation dimension. The diagnosisexamples verify that this method is more accurate and more effective.

Research on Machine Tool Fault Diagnosis and Maintenance Optimization in Intelligent Manufacturing Environments

In the context of intelligent manufacturing,machine tools,as core equipment,directly influence production efficiency and product quality through their operational reliability.Traditional maintenance methods for machine tools,often characterized by low efficiency and high costs,fail to meet the demands of modern manufacturing industries.Therefore,leveraging intelligent manufacturing technologies,this paper proposes a solution optimized for the diagnosis and maintenance of machine tool faults.Initially,the paper introduces sensor-based data acquisition technologies combined with big data analytics and machine learning algorithms to achieve intelligent fault diagnosis of machine tools.Subsequently,it discusses predictive maintenance strategies by establishing an optimized model for maintenance strategy and resource allocation,thereby enhancing maintenance efficiency and reducing costs.Lastly,the paper explores the architectural design,integration,and testing evaluation methods of intelligent manufacturing systems.The study indicates that optimization of machine tool fault diagnosis and maintenance in an intelligent manufacturing environment not only enhances equipment reliability but also significantly reduces maintenance costs,offering broad application prospects.

Construction of an Artificial Intelligence Traditional Chinese Medicine Diagnosis and Treatment Model Based on Syndrome Elements and Small-Sample Data

1.Introduction The combination of traditional Chinese medicine(TCM)and Western medicine has advantages in the treatment of chronic and complex diseases,for example,the introduction and application of TCM during the coronavirus disease 2019(COVID-19)epidemic in Hubei Province,China,had a total effective rate of 90%,thus establishing the efficacy of integrating TCM and Western medicine.However,the integration of TCM diagnosis and treatment methods with modern medicine,as well as their further development,is limited due to several significant challenges.

Circulating and stool nucleic acid analysis for colorectal cancer diagnosis

In recent years, the need to identify molecular markers characterized by high sensitivity and specificity in detecting and monitoring early and colorectal cancer lesions has increased. Up to now, none of the markers or panels of markers analyzed have met the rigorous standards required of a screening program. The important discovery of circulating nucleic acids in biological fluids has aroused intense scientific interest because of their usefulness in malignant and non malignant diseases. Over time, their yield and stability have been identified and compared with other “standard” biomarkers. The analysis of circulating DNA from blood and stool is a relatively simple and non-invasive procedure, representing a very attractive marker to detect genetic and epigenetic mutations and to monitor disease progression. A correlation between blood and stool biomarkers could also help to enhance currently available diagnostic approaches. However, various processing and analytic problems need to be resolved before such an approach can be applied in clinical practice.

Classification,prevalence and integrated care for neurodevelopmental and child mental health disorders:A brief overview for paediatricians

‘Neurodevelopmental disorders’comprise a group of congenital or acquired longterm conditions that are attributed to disturbance of the brain and or neuromuscular system and create functional limitations,including autism spectrum disorder,attention deficit/hyperactivity disorder,tic disorder/Tourette’s syndrome,developmental language disorders and intellectual disability.Cerebral palsy and epilepsy are often associated with these conditions within the broader framework of paediatric neurodisability.Co-occurrence with each other and with other mental health disorders including anxiety and mood disorders and behavioural disturbance is often the norm.Together these are referred to as neurodevelopmental,emotional,behavioural,and intellectual disorders(NDEBIDs)in this paper.Varying prevalence rates for NDEBID have been reported in developed countries,up to 15%,based on varying methodologies and definitions.NDEBIDs are commonly managed by either child health paediatricians or child/adolescent mental health(CAMH)professionals,working within multidisciplinary teams alongside social care,education,allied healthcare practitioners and voluntary sector.Fragmented services are common problems for children and young people with multi-morbidity,and often complicated by subthreshold diagnoses.Despite repeated reviews,limited consensus among clinicians about classification of the various NDEBIDs may hamper service improvement based upon research.The recently developed“Mental,Behavioural and Neurodevelopmental disorder”chapter of the International Classification of Diseases-11 offers a way forward.In this narrative review we search the extant literature and discussed a brief overview of the aetiology and prevalence of NDEBID,enumerate common problems associated with current classification systems and provide recommendations for a more integrated approach to the nosology and clinical care of these related conditions.

Multiplex planar microarrays for disease prognosis, diagnosis and theranosis

Advanced diagnostic methods and algorithms for immune disorders provide qualitative and quantitative multiplex measurement for pre-clinical prognostic and clinical diagnostic biomarkers specific for diseases.Choice of therapy is confirmed by modulating diagnostic efficacy of companion, theranotic drug concentrations.Assay methods identify, monitor and manage autoimmune diseases, or risk thereof, in subjects who have,or who are related to individuals with autoimmune disease. These same diagnostic protocols also integratequalitative and quantitative assay test protocol designs for responder patient assessment, risk analysis and management of disease when integrating multiplex planar microarray diagnostic tests, patient theranostic companion diagnostic methods and test panels for simultaneous assessment and management of dysimmune and inflammatory disorders, autoimmunity, allergy and cancer. Proprietary assay methods are provided to identify, monitor and manage dysimmune conditions, or risk thereof, in subjects with pathological alterations in the immune system, or who are related to individuals with these conditions. The protocols can be used for confirmatory testing of subjects who exhibit symptoms of dysimmunity, as well as subjects who are apparently healthy and do not exhibit symptoms of altered immune function. The protocols also provide for methods of determining whether a subject has, is at risk for, or is a candidate for disease therapy, guided by companion diagnosis and immunosuppressive therapy, as well as therapeutic drug monitoring and theranostic testing of disease biomarkers in response to immunoabsorption therapy. The multiplex test panels provide the components that are integral for performing the methods to recognized clinical standards.

Integrated analysis of comorbidity, pregnant outcomes, and amniotic fluid cytogenetics of fetuses with persistent left superior vena cava

BACKGROUND Persistent left superior vena cava(PLSVC)is the most common venous system variant.The clinical characteristics and amniotic fluid cytogenetics of fetuses with PLSVC remain to be further explored.AIM To develop reliable prenatal diagnostic recommendations through integrated analysis of the clinical characteristics of fetuses with PLSVC.METHODS Cases of PLSVC diagnosed using prenatal ultrasonography between September 2019 and November 2022 were retrospectively studied.The clinical characteristics of the pregnant women,ultrasonic imaging information,gestational age at diagnosis,pregnancy outcomes,and amniocentesis results were summarized and analyzed using categorical statistics and the chi-square test or Fisher’s exact test.RESULTS Of the 97 cases diagnosed by prenatal ultrasound,49(50.5%)had isolated PLSVC and 48(49.5%)had other structural abnormalities.The differences in pregnancy outcomes and amniocentesis conditions between the two groups were statistically significant(P<0.05).No significant differences were identified between the two groups in terms of advanced maternal age and gestational age(P>0.05).According to the results of the classification statistics,the most common intrac-ardiac abnormality was a ventricular septal defect and the most common extrac-ardiac abnormality was a single umbilical artery.In the subgroup analysis,the concurrent combination of intra-and extracardiac structural abnormalities was a risk factor for adverse pregnancy outcomes(odds ratio>1,P<0.05).Additional-ly,all abnormal cytogenetic findings on amniocentesis were observed in the comorbidity group.One case was diagnosed with 21-trisomy and six cases was diagnosed with chromosome segment duplication.CONCLUSION Examination for other structural abnormalities is strongly recommended when PLSVC is diagnosed.Poorer pregnancy outcomes and increased amniocentesis were observed in PLSVC cases with other structural abnor-malities.Amniotic fluid cytogenetics of fetuses is recommended for PLSVC with other structural abnormalities.

An Expert Consensus of Integrated Chinese and Western Medicine Treatment on Lung Cancer

Lung cancer is a malignant tumor of the lung originating from the bronchial mucosa,glands or alveolar epithelium.With the population aging and environmental pollution getting increasingly severe,lung cancer has become the malignant tumor with the highest incidence and mortality rate in China,seriously endangering people’s life and health.However,there is no standardized guideline for the integrated Chinese and Western medicine treatment of lung cancer in China.In order to standardize and improve integrated Chinese and Western medicine diagnosis and treatment of lung cancer in China,the First Affiliated Hospital of Guangzhou University of Chinese Medicine,together with oncologists from the Sun Yat-sen University Cancer Center,compiled this consensus under the coordination of the Medical Policy Department of the National Administration of Traditional Chinese Medicine,taking into account the main results of the pilot project of Chinese and Western Medicine Clinical Collaboration for Major Difficult Diseases(lung cancer).

糖尿病前期中西医结合早期诊断的国内外进展与挑战

糖尿病前期是一种表现为空腹血糖受损、糖耐量异常或两者的混合状态的疾病,属于中医“脾瘅”范畴。随着现代生活模式的改变,糖尿病前期的患病率不断升高,具有和糖尿病相当的预后风险,及时诊断并早期干预至关重要。本文从中医学和现代医学两个角度梳理了糖尿病前期的起源与定义,发现早在《素问》成书时,中医学便已对“脾瘅”形成了一定的认识。随着循证医学的发展和规范化临床研究的实施,我国逐步构建了具有中医特色的规范化糖尿病前期临床实践指南。在诊断方面,血糖检测指标类型和阈值、中医证候诊断、中西医结合诊断模型、疾病风险评分模型、生物标志物、可穿戴设备等多种无创中西医结合诊断方法不断完善,但多针对糖尿病患者的预防而非糖尿病前期的早期诊断和筛查;餐后1 h血糖可能是未来诊断糖尿病前期或糖尿病高危人群的新指标,但需进一步研究证实以推广使用。针对糖尿病前期中西医结合早期诊断面临的诊断标准的动态性、筛查流程的复杂性、临床症状的不典型性、疾病的低知晓性等挑战,未来需不断更新和完善诊断标准,融合数字化健康管理和可穿戴设备,充分发挥中医优势,构建针对糖尿病前期人群的基于中医宏观表征与组学微观数据相结合的疾病诊断模型,开发更简便、快捷的中西医结合筛查方法,实现糖尿病前期的“早筛查、早诊断、早干预、早康复”。

基于互联网医院区域一体化就医模式的探索与实践

随着国内医疗体制改革的日益深化,逐步形成“以患者为中心”的服务理念,互联网医院的应用创新重构医疗服务模式。然而,居民在一体化就医过程中仍存在一系列问题,如信息一体化支撑不足、就医流程不畅、医疗资源浪费等。本文结合国内外互联网医院现状及北京胸科医院互联网医院的建设情况,从区域一体化就医服务模式的现状及难点进行分析,梳理全流程就医模式的关键环节,将三级公立医院和医联体单位作为支撑,以首都医科大学附属北京胸科医院区域互联网医院服务专区的理念、技术、流程为创新点探索实践路径,探索和实践基于互联网医院区域一体化就医模式。为实现优质医疗资源有效下沉、推动分级诊疗、搭建胸部疾病全程管理体系、推动医院高质量发展提供有利依据。

中西医结合诊治妊娠胚物残留专家共识(2024年版)

妊娠胚物残留(RPOC)是指流产或分娩后,胚胎组织或胎盘未能完全排出而残留子宫内,可引起出血、感染,甚至宫腔粘连等。目前RPOC的治疗策略主要分为药物治疗和手术治疗两类,但国内外对此尚未形成科学、规范的指导意见。中西医联合诊治一直是我国诊治RPOC的特色手段,为推广中西医结合协同诊疗理念,促进RPOC中西医结合诊疗技术发展,山东中医药学会妇科专业委员会、山东中西医结合学会生殖外科专业委员会、山东省疼痛医学会妇产科专业委员会共同牵头成立共识专家组,讨论形成《中西医结合诊治妊娠胚物残留专家共识(2024年版)》,从RPOC的高危因素、临床表现、诊断、治疗等方面阐述中西医结合协同诊疗理念,并提供专家共识,以改善RPOC患者预后,提高其生活质量。

A multimodal integration pipeline for accurate diagnosis, pathogen identification, and prognosis prediction of pulmonary infections

Pulmonary infections pose formidable challenges in clinical settings with high mortality rates across all age groups worldwide.Accurate diagnosis and early intervention are crucial to improve patient outcomes.Artificial intelligence(AI)has the capability to mine imaging features specific to different pathogens and fuse multimodal features to reach a synergistic diagnosis,enabling more precise investigation and individualized clinical management.In this study,we successfully developed a multimodal integration(MMI)pipeline to differentiate among bacterial,fungal,and viral pneumonia and pulmonary tuberculosis based on a real-world dataset of 24,107 patients.The area under the curve(AUC)of the MMI system comprising clinical text and computed tomography(CT)image scans yielded 0.910(95%confidence interval[CI]:0.904–0.916)and 0.887(95%CI:0.867–0.909)in the internal and external testing datasets respectively,which were comparable to those of experienced physicians.Furthermore,the MMI system was utilized to rapidly differentiate between viral subtypes with a mean AUC of 0.822(95%CI:0.805–0.837)and bacterial subtypes with a mean AUC of 0.803(95%CI:0.775–0.830).Here,the MMI system harbors the potential to guide tailored medication recommendations,thus mitigating the risk of antibiotic misuse.Additionally,the integration of multimodal factors in the AI-driven system also provided an evident advantage in predicting risks of developing critical illness,contributing to more informed clinical decision-making.To revolutionize medical care,embracing multimodal AI tools in pulmonary infections will pave the way to further facilitate early intervention and precise management in the foreseeable future.

中华双腔吸虫病的诊断和综合防制

中华双腔吸虫寄生于绵羊、山羊、牛、鹿、骆驼等反刍兽的肝管、胆管和胆囊内,常与肝片吸虫混合感染。感染牛、羊、鹿、骆驼表现为可视黏膜黄染、颌下和胸前水肿,剖检可见肝脏肿大硬化、胆管炎、胆管壁增厚。粪便沉淀法可检测到暗褐色椭圆形虫卵,根据流行病学、临床症状和虫卵形态特征可以初步诊断,病理剖检发现虫体和PCR检测可以确诊。中华双腔吸虫在我国西北地区危害严重,采用消灭中间宿主条纹蜗牛和枝小丽螺、加强终末宿主牛、羊、鹿、骆驼饮水和饲草管理等手段综合防制本病,降低畜牧业经济损失。

Guidelines for diagnosis and treatment of hepatic fibrosis with integrated traditional Chinese and Western medicine(2019 edition)

In 2006, the Hepatology Committee of Chinese Association of Integrative Medicine issued the "Guidelines for the Prevention and Treatment of Liver Fibrosis with Integrated Traditional Chinese and Western Medicine." In recent years, the fields of Chinese medicine, Western medicine, and integrative medicine have made rapid advances in basic and clinical research into chronic liver disease, and accumulated new evidence for the prevention and treatment of hepatic fibrosis. Therefore, in order to meet clinical needs, liver disease experts of integrated traditional Chinese and Western medicine were united to revise the previous guidelines in order to help physicians make correct and reasonable decisions in the diagnosis and treatment of hepatic fibrosis.

Integration of Fault Analysis and Interlock Controller Synthesis for Batch Processes

Integration amongst various decision-making processes, such as planning, design, and operation is necessary to dynamic and flexible batch production. To achieve a batch production integration, utilization of common models used for various decision-making processes is an effective approach. From this point of view, a batch system common model as described by a Petri net is proposed. In this article, a fault diagnosis technique for batch processes is presented using information about fault propagation and the possibilities of integration of fault analysis and controller synthesis are discussed on the basis of the Petri net based common models.