Re-Assessing Tuberculin Skin Test (TST) for the Diagnosis of Tuberculosis (TB) among African Migrants in Western Europe and USA

Background: Tuberculin skin test (TST)—is widely used for screening tuberculosis TB in migrants from high endemic countries of Africa and Asia. However, the cut-off point for clinical TB and Mtb infection is not well established in TB endemic countries of sub-Saharan Africa. In this study we compared the size of TST induration in smear positive pulmonary TB (PTB) patients, their house-hold contacts and community controls in high endemic setting in Ethiopia. Methods: In a health facility-based cross-sectional study, smear positive PTB patients were recruited. Their household contacts traced, and community controls were recruited from neighbourhoods. Sputum sample collected from patients were examined using smear microscopy. Participants were also tested by TST and QuantiFERON? -TB Gold In–Tube test (QFTGIT). Results: From a total of 224 study participants, skin test induration data were available for 48 PTB patients, 88 household contacts and 75 community controls. All 48 patients, 64 (72.2%) of the household contacts and 35 (46.7%) of the community controls had skin test induration ≥ 10 mm. Moreover, 44 (91.7%) PTB patients, 58 (65.9%) of the household contacts and 26 (34.7%) of the community controls had skin test induration ≥ 15 mm, respectively. The mean size of TST induration was significantly higher in TB patients (18.1mm) compared to that of household contacts (13.6 mm) and community controls (7.9 mm) (pMtb

Comparative evaluation of intragastric bile acids and hepatobiliary scintigraphy in the diagnosis of duodenogastric reflux

AIM:To assess the diagnostic value of a combination of intragastric bile acids and hepatobiliary scintigraphy in the detection of duodenogastric reflux(DGR).METHODS:The study contained 99 patients with DGR and 70 healthy volunteers who made up the control group.The diagnosis was based on the combination of several objective arguments:a long history of gastric symptoms(i.e.,nausea,epigastric pain,and/or bilious vomiting) poorly responsive to medical treatment,gastroesophageal reflux symptoms unresponsive to protonpump inhibitors,gastritis on upper gastrointestinal(GI) endoscopy and/or at histology,presence of a bilious gastric lake at > 1 upper GI endoscopy,pathologic 24-h intragastric bile monitoring with the Bilitec device.Gas-tric juice was aspirated in the GI endoscopy and total bile acid(TBA),total bilirubin(TBIL) and direct bilirubin(DBIL) were tested in the clinical laboratory.Continuous data of gastric juice were compared between each group using the independent-samples Mann-Whitney U-test and their relationship was analysed by Spearman's rank correlation test and Fisher's linear discriminant analysis.Histopathology of DGR patients and 23 patients with chronic atrophic gastritis was compared by clinical pathologists.Using the Independent-samples Mann-Whitney U-test,DGR index(DGRi) was calculated in 28 patients of DGR group and 19 persons of control group who were subjected to hepatobiliary scintigraphy.Receiver operating characteristic curve was made to determine the sensitivity and specificity of these two methods in the diagnosis of DGR.RESULTS:The group of patients with DGR showed a statistically higher prevalence of epigastric pain in comparison with control group.There was no significant difference between the histology of gastric mucosa with atrophic gastritis and duodenogastric reflux.The bile acid levels of DGR patients were significantly higher than the control values(Z:TBA:-8.916,DBIL:-3.914,TBIL:-6.197,all P < 0.001).Two of three in the DGR group have a significantly associated with each other(r:TBA/DBIL:0.362,TBA/TBIL:0.470,DBIL/TBIL:0.737,all P < 0.001).The Fisher's discriminant function is followed:Con:Y = 0.002TBA + 0.048DBIL + 0.032TBIL 0.986;Reflux:Y = 0.012TBA + 0.076DBIL + 0.089TBIL-2.614.Eighty-four point zero five percent of original grouped cases were correctly classified by this method.With respect to the DGR group,DGRi were higher than those in the control group with statistically significant differences(Z =-5.224,P < 0.001).Twenty eight patients(59.6%) were deemed to be duodenogastric reflux positive by endoscopy,as compared to 37 patients(78.7%) by hepatobiliary scintigraphy.CONCLUSION:The integrated use of intragastric bile acid examination and scintigraphy can greatly improve the sensitivity and specificity of the diagnosis of DGR.

IGIgram:An Improved Gini Index-Based Envelope Analysis for Rolling Bearing Fault Diagnosis

The transient impulse features caused by rolling bearing faults are often present in the resonance frequency band which is closely related to the dynamic characteristics of the machine structure.Informative frequency band identification is a crucial prerequisite for envelope analysis and thereby accurate fault diagnosis of rolling bearings.In this paper,based on the ratio of quasi-arithmetic means and Gini index,improved Gini indices(IGIs)are proposed to quantify the transient impulse features of a signal,and their effectiveness and advantages in sparse quantification are confirmed by simulation analysis and comparisons with traditional sparsity measures.Furthermore,an IGI-based envelope analysis method named IGIgram is developed for fault diagnosis of rolling bearings.In the new method,an IGI-based indicator is constructed to evaluate the impulsiveness and cyclostationarity of the narrow-band filtered signal simultaneously,and then a frequency band with abundant fault information is adaptively determined for extracting bearing fault features.The performance of the IGIgram method is verified on the simulation signal and railway bearing experimental signals and compared with typical sparsity measures-based envelope analysis methods and log-cycligram.The results demonstrate that the proposed IGIs are efficient in quantifying bearing fault-induced transient features and the IGIgram method with appropriate power exponent can effectively achieve the diagnostics of different axle-box bearing faults.

Tumor Suppressor miR-637 Is Associated with Cellular Migration, Invasion, and Glioma Diagnosis

Objective: Abnormal miRNA expression is observed in several human tumors;moreover, normal cell regulation can be disrupted by tumor-suppressive or oncogenic miRNAs. We aimed to investigate the role of miR-637 in gliomas. Methods: We assessed miR-637 expression in 98 and 16 gliomas and non-tumoral brain tissues, respectively, using in situ hybridization. We calculated receiver operating characteristic curves to determine the specificity and sensitivity of miR-637 biomarkers. Next, the effects of miR-637 on glioma cell migration and invasion were determined by using the transwell assay. Candidate target genes were identified through Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis. Results: There was significant miR-637 downregulation in glioma tissues (P < 0.001). Further, it showed potential as a diagnostic biomarker for gliomas. In addition, miR-637 suppressed glioma cell migration and invasion. Conclusions: Our findings suggest that miR-637 inhibits glioma invasion and migration and could be a potential diagnostic marker for gliomas. Future studies should examine the potential mechanisms underlying miR-637 as a diagnostic marker and therapeutic target for gliomas.

Delayed diagnosis in inflammatory bowel disease:Time to consider solutions

In this editorial,we discuss a recently published manuscript by Blüthner et al in the World Journal of Gastroenterology,with a specific focus on the delayed diagnosis of inflammatory bowel disease(IBD).IBD,which includes Crohn's disease and ulcerative colitis,is a chronic intestinal disorder.A time lag may exist between the onset of inflammation and the appearance of signs and symptoms,potentially leading to an incorrect or delayed diagnosis,a situation referred to as the delayed diagnosis of IBD.Early diagnosis is crucial for effective patient treatment and prognosis,yet delayed diagnosis remains common.The reasons for delayed diagnosis of IBD are numerous and not yet fully understood.One key factor is the nonspecific nature of IBD symptoms,which can easily be mistaken for other conditions.Additionally,the lack of specific diagnostic methods for IBD contributes to these delays.Delayed diagnosis of IBD can result in numerous adverse consequences,including increased intestinal damage,fibrosis,a higher risk of colorectal cancer,and a decrease in the quality of life of the patient.Therefore,it is essential to diagnose IBD promptly by raising physician awareness,enhancing patient education,and developing new diagnostic methods.

Differentiation and diagnosis of migrating cerebral sparganosis: 2 case reports from China

Human cerebral sparganosis is a rare but neglected parasitic disease. We present details of the diagnosis of two cases of migrating cerebral sparganosis from China based on computed tomography and magnetic resonance imaging combined with epidemiological information and serology. Its differentiatial diagnosis from other parasitic diseases, tuberculoma and brain tumor by neuroimaging is briefly discribed.

Artificial intelligence for characterization of diminutive colorectal polyps:A feasibility study comparing two computer-aided diagnosis systems

BACKGROUND Artificial intelligence(AI)has potential in the optical diagnosis of colorectal polyps.AIM To evaluate the feasibility of the real-time use of the computer-aided diagnosis system(CADx)AI for ColoRectal Polyps(AI4CRP)for the optical diagnosis of diminutive colorectal polyps and to compare the performance with CAD EYE^(TM)(Fujifilm,Tokyo,Japan).CADx influence on the optical diagnosis of an expert endoscopist was also investigated.METHODS AI4CRP was developed in-house and CAD EYE was proprietary software provided by Fujifilm.Both CADxsystems exploit convolutional neural networks.Colorectal polyps were characterized as benign or premalignant and histopathology was used as gold standard.AI4CRP provided an objective assessment of its characterization by presenting a calibrated confidence characterization value(range 0.0-1.0).A predefined cut-off value of 0.6 was set with values<0.6 indicating benign and values≥0.6 indicating premalignant colorectal polyps.Low confidence characterizations were defined as values 40%around the cut-off value of 0.6(<0.36 and>0.76).Self-critical AI4CRP’s diagnostic performances excluded low confidence characterizations.RESULTS AI4CRP use was feasible and performed on 30 patients with 51 colorectal polyps.Self-critical AI4CRP,excluding 14 low confidence characterizations[27.5%(14/51)],had a diagnostic accuracy of 89.2%,sensitivity of 89.7%,and specificity of 87.5%,which was higher compared to AI4CRP.CAD EYE had a 83.7%diagnostic accuracy,74.2%sensitivity,and 100.0%specificity.Diagnostic performances of the endoscopist alone(before AI)increased nonsignificantly after reviewing the CADx characterizations of both AI4CRP and CAD EYE(AI-assisted endoscopist).Diagnostic performances of the AI-assisted endoscopist were higher compared to both CADx-systems,except for specificity for which CAD EYE performed best.CONCLUSION Real-time use of AI4CRP was feasible.Objective confidence values provided by a CADx is novel and self-critical AI4CRP showed higher diagnostic performances compared to AI4CRP.

Stage at diagnosis of colorectal cancer through diagnostic route:Who should be screened?

BACKGROUND Colorectal cancer(CRC)is a global health concern,with advanced-stage diagnoses contributing to poor prognoses.The efficacy of CRC screening has been well-established;nevertheless,a significant proportion of patients remain unscreened,with>70%of cases diagnosed outside screening.Although identifying specific subgroups for whom CRC screening should be particularly recommended is crucial owing to limited resources,the association between the diagnostic routes and identification of these subgroups has been less appreciated.In the Japanese cancer registry,the diagnostic routes for groups discovered outside of screening are primarily categorized into those with comorbidities found during hospital visits and those with CRC-related symptoms.AIM To clarify the stage at CRC diagnosis based on diagnostic routes.METHODS We conducted a retrospective observational study using a cancer registry of patients with CRC between January 2016 and December 2019 at two hospitals.The diagnostic routes were primarily classified into three groups:Cancer screening,follow-up,and symptomatic.The early-stage was defined as Stages 0 or I.Multivariate and univariate logistic regressions were exploited to determine the odds of early-stage diagnosis in the symptomatic and cancer screening groups,referencing the follow-up group.The adjusted covariates were age,sex,and tumor location.RESULTS Of the 2083 patients,715(34.4%),1064(51.1%),and 304(14.6%)belonged to the follow-up,symptomatic,and cancer screening groups,respectively.Among the 2083 patients,CRCs diagnosed at an early stage were 57.3%(410 of 715),23.9%(254 of 1064),and 59.5%(181 of 304)in the follow-up,symptomatic,and cancer screening groups,respectively.The symptomatic group exhibited a lower likelihood of early-stage diagnosis than the follow-up group[P<0.001,adjusted odds ratio(aOR),0.23;95%confidence interval(95%CI):0.19-0.29].The likelihood of diagnosis at an early stage was similar between the follow-up and cancer screening groups(P=0.493,aOR for early-stage diagnosis in the cancer screening group vs follow-up group=1.11;95%CI=0.82-1.49).CONCLUSION CRCs detected during hospital visits for comorbidities were diagnosed earlier,similar to cancer screening.CRC screening should be recommended,particularly for patients without periodical hospital visits for comorbidities.

Laser spectroscopy imaging technique coupled withnanomaterials for cancer diagnosis: A review

Laser spectroscopic imaging techniques have received tremendous attention in the-eld of cancer diagnosis due to their high sensitivity,high temporal resolution,and short acquisition time.However,the limited tissue penetration of the laser is still a challenge for the in vivo diagnosis of deep-seated lesions.Nanomaterials have been universally integrated with spectroscopic imaging techniques for deeper cancer diagnosis in vivo.The components,morphology,and sizes of nanomaterials are delicately designed,which could realize cancer diagnosis in vivo or in situ.Considering the enhanced signal emitting from the nanomaterials,we emphasized their combination with spectroscopic imaging techniques for cancer diagnosis,like the surface-enhanced Raman scattering(SERS),photoacoustic,fluorescence,and laser-induced breakdown spectroscopy(LIBS).Applications ofthe above spectroscopic techniques offer new prospectsfor cancer diagnosis.

Exploring impedance spectrum for lithium-ion batteries diagnosis and prognosis:A comprehensive review

Lithium-ion batteries have extensive usage in various energy storage needs,owing to their notable benefits of high energy density and long lifespan.The monitoring of battery states and failure identification are indispensable for guaranteeing the secure and optimal functionality of the batteries.The impedance spectrum has garnered growing interest due to its ability to provide a valuable understanding of material characteristics and electrochemical processes.To inspire further progress in the investigation and application of the battery impedance spectrum,this paper provides a comprehensive review of the determination and utilization of the impedance spectrum.The sources of impedance inaccuracies are systematically analyzed in terms of frequency response characteristics.The applicability of utilizing diverse impedance features for the diagnosis and prognosis of batteries is further elaborated.Finally,challenges and prospects for future research are discussed.

Expert Experience and Data-Driven Based Hybrid Fault Diagnosis for High-SpeedWire Rod Finishing Mills

The reliable operation of high-speed wire rod finishing mills is crucial in the steel production enterprise.As complex system-level equipment,it is difficult for high-speed wire rod finishing mills to realize fault location and real-time monitoring.To solve the above problems,an expert experience and data-driven-based hybrid fault diagnosis method for high-speed wire rod finishing mills is proposed in this paper.First,based on its mechanical structure,time and frequency domain analysis are improved in fault feature extraction.The approach of combining virtual value,peak value with kurtosis value index,is adopted in time domain analysis.Speed adjustment and side frequency analysis are proposed in frequency domain analysis to obtain accurate component characteristic frequency and its corresponding sideband.Then,according to time and frequency domain characteristics,fault location based on expert experience is proposed to get an accurate fault result.Finally,the proposed method is implemented in the equipment intelligent diagnosis system.By taking an equipment fault on site,for example,the effectiveness of the proposed method is illustrated in the system.

Non-participation of asymptomatic candidates in screening protocols reduces early diagnosis and worsens prognosis of colorectal cancer

The Agatsuma et al’s study shows that despite the evidence of the benefits of an early colorectal cancer(CRC)diagnosis,through screening in asymptomatic subjects,up to 50%of candidates reject this option and many of those affected are diagnosed later,in advanced stages.The efficacy of screening programs has been well-established for several years,which reduces the risk of CRC morbidity and mortality,without taking into account the test used for screening,or other tools.Nevertheless,a significant proportion of patients remain unscreened,so understanding the factors involved,as well as the barriers of the population to adherence is the first step to possibly modify the participation rate.These barriers could include a full range of social and political aspects,especially the type of financial provision of each health service.In Japan,health services are universal,and this advantageous situation makes it easier for citizens to access to these services,contributing to the detection of various diseases,including CRC.Interestingly,the symptomatic CRC group had a lower early-stage diagnosis rate than the patients detected during follow-up for other comorbidities,and symptomatic and cancer screening groups showed similar early-stage diagnosis.

Label Recovery and Trajectory Designable Network for Transfer Fault Diagnosis of Machines With Incorrect Annotation

The success of deep transfer learning in fault diagnosis is attributed to the collection of high-quality labeled data from the source domain.However,in engineering scenarios,achieving such high-quality label annotation is difficult and expensive.The incorrect label annotation produces two negative effects:1)the complex decision boundary of diagnosis models lowers the generalization performance on the target domain,and2)the distribution of target domain samples becomes misaligned with the false-labeled samples.To overcome these negative effects,this article proposes a solution called the label recovery and trajectory designable network(LRTDN).LRTDN consists of three parts.First,a residual network with dual classifiers is to learn features from cross-domain samples.Second,an annotation check module is constructed to generate a label anomaly indicator that could modify the abnormal labels of false-labeled samples in the source domain.With the training of relabeled samples,the complexity of diagnosis model is reduced via semi-supervised learning.Third,the adaptation trajectories are designed for sample distributions across domains.This ensures that the target domain samples are only adapted with the pure-labeled samples.The LRTDN is verified by two case studies,in which the diagnosis knowledge of bearings is transferred across different working conditions as well as different yet related machines.The results show that LRTDN offers a high diagnosis accuracy even in the presence of incorrect annotation.

Differential diagnosis of Crohn’s disease and intestinal tuberculosis based on ATR-FTIR spectroscopy combined with machine learning

BACKGROUND Crohn’s disease(CD)is often misdiagnosed as intestinal tuberculosis(ITB).However,the treatment and prognosis of these two diseases are dramatically different.Therefore,it is important to develop a method to identify CD and ITB with high accuracy,specificity,and speed.AIM To develop a method to identify CD and ITB with high accuracy,specificity,and speed.METHODS A total of 72 paraffin wax-embedded tissue sections were pathologically and clinically diagnosed as CD or ITB.Paraffin wax-embedded tissue sections were attached to a metal coating and measured using attenuated total reflectance fourier transform infrared spectroscopy at mid-infrared wavelengths combined with XGBoost for differential diagnosis.RESULTS The results showed that the paraffin wax-embedded specimens of CD and ITB were significantly different in their spectral signals at 1074 cm^(-1) and 1234 cm^(-1) bands,and the differential diagnosis model based on spectral characteristics combined with machine learning showed accuracy,specificity,and sensitivity of 91.84%,92.59%,and 90.90%,respectively,for the differential diagnosis of CD and ITB.CONCLUSION Information on the mid-infrared region can reveal the different histological components of CD and ITB at the molecular level,and spectral analysis combined with machine learning to establish a diagnostic model is expected to become a new method for the differential diagnosis of CD and ITB.

Exploring the Pathways of Leprosy Patients from Their Communities to a Diagnosis in the Districts of Mayuge, Yumbe and Kasese-Uganda

Background: Leprosy is known to cause disability that leads to severe outcomes like stigma, discrimination, mental health problems and participation restriction. Furthermore, in cases of infectious leprosy, longer delays increase the risk for the spread of the disease. Despite being preventable and curable, a significant proportion of new leprosy patients (39%) in 2019 had grade 2 (Described as Visible disability) at the time of diagnosis signifying late presentation. The aim of this study was to describe patient journeys from first symptoms suggestive of leprosy to a diagnosis and individual and community level factors associated with health seeking behavior of leprosy patients. Methods: This was a cross-sectional explorative study implemented in Kasese, Mayuge and Yumbe districts .A structured questionnaire was used to collect quantitative data. Qualitative assessment included patients, family members, health workers, voluntary health teams and the district health team. Descriptive statistics were presented in terms of percentages, frequency tables, pie Charts and graphs for easy interpretation and discussion. Results: The results indicate that 53% of the respondents identified as female. The median age of the respondents being 34 years, with a range of 1 to 76 years (Mean: 44.7, Mode: 65, Standard-Deviation: 19.6, Kurtosis: 0.6). The most common first symptom noticed by respondents was skin lesions (65%) followed by deformities (18%) (P value = 0.05%) occurring mostly in the feet (P-value = 0.48). Majority (52%) of the patients had taken more than 24 months (SD 18.72 OR 2.75) for a diagnosis to be made with a maximum delay of over 60 months. The most common cause of delay in seeking health care was lack of knowledge on leprosy (P value=Conclusions: There was a delay of 2 years in seeking health care for the majority of the patients. Key barriers to early diagnosis were lack of knowledge and infrastructure. Community sensitization and strengthening capacity building are needed to achieve early diagnosis of leprosy and proper management.

Interferon-gamma release assays as a tool for differential diagnosis of gastrointestinal tuberculosis

In this editorial,we comment on an article published in a recent issue of the World Journal of Clinical Cases.There is a pressing need for reliable tools for diagnosing tuberculosis(TB)of the gastrointestinal tract.Despite advancements in the diagnosis and treatment,TB remains a global health challenge.Ali et al demon-strated that TB may mimic gastrointestinal conditions,such as gastric outlet obstruction,causing a delay in the diagnosis.Furthermore,the latter complication is frequently observed during infections,including Helicobacter pylori,and rarely is related to TB,as in the presented case.In line with this,we think that laboratory tests based on interferon-gamma release assays can be a helpful tool for diagnosing latent TB paced in the gastrointestinal tract.Innovative strategies and approaches for diagnosing latent/active extra pulmonary TB are crucial for establishing the diagnosis early and enhancing treatment strategies to mitigate the global burden of TB.

Real-Time Intelligent Diagnosis of Co-frequency Vibration Faults in Rotating Machinery Based on Lightweight-Convolutional Neural Networks

The co-frequency vibration fault is one of the common faults in the operation of rotating equipment,and realizing the real-time diagnosis of the co-frequency vibration fault is of great significance for monitoring the health state and carrying out vibration suppression of the equipment.In engineering scenarios,co-frequency vibration faults are highlighted by rotational frequency and are difficult to identify,and existing intelligent methods require more hardware conditions and are exclusively time-consuming.Therefore,Lightweight-convolutional neural networks(LW-CNN)algorithm is proposed in this paper to achieve real-time fault diagnosis.The critical parameters are discussed and verified by simulated and experimental signals for the sliding window data augmentation method.Based on LW-CNN and data augmentation,the real-time intelligent diagnosis of co-frequency is realized.Moreover,a real-time detection method of fault diagnosis algorithm is proposed for data acquisition to fault diagnosis.It is verified by experiments that the LW-CNN and sliding window methods are used with high accuracy and real-time performance.

EDSUCh:A robust ensemble data summarization method for effective medical diagnosis

Identifying rare patterns for medical diagnosis is a challenging task due to heterogeneity and the volume of data.Data summarization can create a concise version of the original data that can be used for effective diagnosis.In this paper,we propose an ensemble summarization method that combines clustering and sampling to create a summary of the original data to ensure the inclusion of rare patterns.To the best of our knowledge,there has been no such technique available to augment the performance of anomaly detection techniques and simultaneously increase the efficiency of medical diagnosis.The performance of popular anomaly detection algorithms increases significantly in terms of accuracy and computational complexity when the summaries are used.Therefore,the medical diagnosis becomes more effective,and our experimental results reflect that the combination of the proposed summarization scheme and all underlying algorithms used in this paper outperforms the most popular anomaly detection techniques.

Hierarchical multihead self-attention for time-series-based fault diagnosis

Fault diagnosis is important for maintaining the safety and effectiveness of chemical process.Considering the multivariate,nonlinear,and dynamic characteristic of chemical process,many time-series-based data-driven fault diagnosis methods have been developed in recent years.However,the existing methods have the problem of long-term dependency and are difficult to train due to the sequential way of training.To overcome these problems,a novel fault diagnosis method based on time-series and the hierarchical multihead self-attention(HMSAN)is proposed for chemical process.First,a sliding window strategy is adopted to construct the normalized time-series dataset.Second,the HMSAN is developed to extract the time-relevant features from the time-series process data.It improves the basic self-attention model in both width and depth.With the multihead structure,the HMSAN can pay attention to different aspects of the complicated chemical process and obtain the global dynamic features.However,the multiple heads in parallel lead to redundant information,which cannot improve the diagnosis performance.With the hierarchical structure,the redundant information is reduced and the deep local time-related features are further extracted.Besides,a novel many-to-one training strategy is introduced for HMSAN to simplify the training procedure and capture the long-term dependency.Finally,the effectiveness of the proposed method is demonstrated by two chemical cases.The experimental results show that the proposed method achieves a great performance on time-series industrial data and outperforms the state-of-the-art approaches.

Causal temporal graph attention network for fault diagnosis of chemical processes

Fault detection and diagnosis(FDD)plays a significant role in ensuring the safety and stability of chemical processes.With the development of artificial intelligence(AI)and big data technologies,data-driven approaches with excellent performance are widely used for FDD in chemical processes.However,improved predictive accuracy has often been achieved through increased model complexity,which turns models into black-box methods and causes uncertainty regarding their decisions.In this study,a causal temporal graph attention network(CTGAN)is proposed for fault diagnosis of chemical processes.A chemical causal graph is built by causal inference to represent the propagation path of faults.The attention mechanism and chemical causal graph were combined to help us notice the key variables relating to fault fluctuations.Experiments in the Tennessee Eastman(TE)process and the green ammonia(GA)process showed that CTGAN achieved high performance and good explainability.