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.

Movement analysis in the diagnosis and management of Parkinson’s disease

Challenges in the diagnosis and treatment of Parkinson’s disease:Parkinson’s disease(PD)is an increasingly prevalent neurodegenerative disease,at first sight primarily characterized by motor symptoms,although non-motor symptoms also constitute a major part of the overall phenotype.Clinically,this disease cannot be diagnosed reliably until a large part of the vulnerable dopaminergic neurons has been irretrievably lost,and the disease progresses inexorably.New biological criteria for PD have been proposed recently and might eventually improve early diagnosis,but they require further validation,and their use will initially be restricted to a research environment(Darweesh et al.,2024).

Visualizing traumatic brain injury:ocular clues for diagnosis and assessment

Traumatic brain injury (TBI) is defined as damage to the brain resulting from an external sudden physical force or shock to the head.It is considered a silent public health epidemic causing significant death and disability globally.There were 64,000 TBI related deaths reported in the USA in 2020,with about US$76 billion in direct and indirect medical costs annually.

Pathogenesis, diagnosis, and treatment of epilepsy: electromagnetic stimulation-mediated neuromodulation therapy and new technologies

Epilepsy is a severe,relapsing,and multifactorial neurological disorder.Studies regarding the accurate diagnosis,prognosis,and in-depth pathogenesis are crucial for the precise and effective treatment of epilepsy.The pathogenesis of epilepsy is complex and involves alterations in variables such as gene expression,protein expression,ion channel activity,energy metabolites,and gut microbiota composition.Satisfactory results are lacking for conventional treatments for epilepsy.Surgical resection of lesions,drug therapy,and non-drug interventions are mainly used in clinical practice to treat pain associated with epilepsy.Non-pharmacological treatments,such as a ketogenic diet,gene therapy for nerve regeneration,and neural regulation,are currently areas of research focus.This review provides a comprehensive overview of the pathogenesis,diagnostic methods,and treatments of epilepsy.It also elaborates on the theoretical basis,treatment modes,and effects of invasive nerve stimulation in neurotherapy,including percutaneous vagus nerve stimulation,deep brain electrical stimulation,repetitive nerve electrical stimulation,in addition to non-invasive transcranial magnetic stimulation and transcranial direct current stimulation.Numerous studies have shown that electromagnetic stimulation-mediated neuromodulation therapy can markedly improve neurological function and reduce the frequency of epileptic seizures.Additionally,many new technologies for the diagnosis and treatment of epilepsy are being explored.However,current research is mainly focused on analyzing patients’clinical manifestations and exploring relevant diagnostic and treatment methods to study the pathogenesis at a molecular level,which has led to a lack of consensus regarding the mechanisms related to the disease.

MicroRNAs as potential biomarkers for diagnosis of post-traumatic stress disorder

Post-traumatic stress disorder is a mental disorder caused by exposure to severe traumatic life events.Currently,there are no validated biomarkers or laboratory tests that can distinguish between trauma survivors with and without post-traumatic stress disorder.In addition,the heterogeneity of clinical presentations of post-traumatic stress disorder and the overlap of symptoms with other conditions can lead to misdiagnosis and inappropriate treatment.Evidence suggests that this condition is a multisystem disorder that affects many biological systems,raising the possibility that peripheral markers of disease may be used to diagnose post-traumatic stress disorder.We performed a PubMed search for microRNAs(miRNAs)in post-traumatic stress disorder(PTSD)that could serve as diagnostic biomarkers and found 18 original research articles on studies performed with human patients and published January 2012 to December 2023.These included four studies with whole blood,seven with peripheral blood mononuclear cells,four with plasma extracellular vesicles/exosomes,and one with serum exosomes.One of these studies had also used whole plasma.Two studies were excluded as they did not involve microRNA biomarkers.Most of the studies had collected samples from adult male Veterans who had returned from deployment and been exposed to combat,and only two were from recently traumatized adult subjects.In measuring miRNA expression levels,many of the studies had used microarray miRNA analysis,miRNA Seq analysis,or NanoString panels.Only six studies had used real time polymerase chain reaction assay to determine/validate miRNA expression in PTSD subjects compared to controls.The miRNAs that were found/validated in these studies may be considered as potential candidate biomarkers for PTSD and include miR-3130-5p in whole blood;miR-193a-5p,-7113-5p,-125a,-181c,and-671-5p in peripheral blood mononuclear cells;miR-10b-5p,-203a-3p,-4488,-502-3p,-874-3p,-5100,and-7641 in plasma extracellular vesicles/exosomes;and miR-18a-3p and-7-1-5p in blood plasma.Several important limitations identified in the studies need to be taken into account in future studies.Further studies are warranted with war veterans and recently traumatized children,adolescents,and adults having PTSD and use of animal models subjected to various stressors and the effects of suppressing or overexpressing specific microRNAs.

Autism spectrum disorder:difficulties in diagnosis and microRNA biomarkers

We performed a PubMed search for microRNAs in autism spectrum disorder that could serve as diagnostic biomarkers in patients and selected 17 articles published from January 2008 to December 2023,of which 4 studies were performed with whole blood,4 with blood plasma,5 with blood serum,1 with serum neural cell adhesion molecule L1-captured extracellular vesicles,1 with blood cells,and 2 with peripheral blood mononuclear cells.Most of the studies involved children and the study cohorts were largely males.Many of the studies had performed microRNA sequencing or quantitative polymerase chain reaction assays to measure microRNA expression.Only five studies had used real-time polymerase chain reaction assay to validate microRNA expression in autism spectrum disorder subjects compared to controls.The microRNAs that were validated in these studies may be considered as potential candidate biomarkers for autism spectrum disorder and include miR-500a-5p,-197-5p,-424-5p,-664a-3p,-365a-3p,-619-5p,-664a-3p,-3135a,-328-3p,and-500a-5p in blood plasma and miR-151a-3p,-181b-5p,-320a,-328,-433,-489,-572,-663a,-101-3p,-106b-5p,-19b-3p,-195-5p,and-130a-3p in blood serum of children,and miR-15b-5p and-6126 in whole blood of adults.Several important limitations were identified in the studies reviewed,and need to be taken into account in future studies.Further studies are warranted with children and adults having different levels of autism spectrum disorder severity and consideration should be given to using animal models of autism spectrum disorder to investigate the effects of suppressing or overexpressing specific microRNAs as a novel therapy.

Clinical significance and influencing factors of linked color imaging technique in real-time diagnosis of active Helicobacter pylori infection

Background:Determining the Helicobacter pylori (H. pylori) infection state during the gastroscopic process is important but still challenging. The linked color imaging (LCI) technique might emphasize the mucosal color change after H. pylori infection, which might help the diagnosis. In the present study, we aimed to compare the LCI technique with traditional white light imaging (WLI) endoscopy for diagnosing active H. pylori infection.Methods:We collected and analyzed gastroscopic images from 103 patients in our hospital from November 2017 to March 2018, including both LCI and WLI modes. All images were randomly disordered and independently evaluated by four endoscopists who were blinded to the H. pylori status of patients. In addition, the H. pylori state was determined by both rapid urease test and pathology staining. The sensitivity, specificity, positive prediction value (PPV), and negative prediction value (NPV) were calculated for the detection of H. pylori infection. Moreover, the kappa value and interclass correlation coefficient (ICC) were used to evaluate the inter-observer variety by SPSS 24.0 software.Results:Of the 103 enrolled patients, 27 of them were positive for H. pylori infection, while the 76 patients were negative. In total, 388 endoscopic images were selected, including 197 WLI and 191 LCI. The accuracy rate for H. pylori evaluation in the corpus LCI group was significantly higher than other groups (81.2% vs. 64.3%-76.5%, χ2 = 34.852, P < 0.001). Moreover, the corpus LCI group had the optimal diagnostic power with the sensitivity of 85.41% (95% confidence interval [CI]: 76.40%-91.51%), the specificity of 79.71% (95% CI: 74.38%-84.19%), the PPV of 59.42% (95% CI: 50.72%-67.59%), and the NPV of 94.02% (95% CI: 89.95%-96.56%), respectively. The kappa values between different endoscopists were higher with LCI than with WLI (0.433-0.554 vs. 0.331-0.554). Consistently, the ICC value was also higher with LCI than with WLI (0.501 [95% CI: 0.429-0.574] vs. 0.397 [95% CI: 0.323-0.474]). We further analyzed the factors that might lead to misjudgment, revealing that active inflammation might disturb WLI judgment (accuracy rate: 58.70% vs. 76.16%, χ2 = 21.373, P < 0.001). Atrophy and intestinal metaplasia might affect the accuracy of the LCI results (accuracy rate: 66.96% vs. 73.47%, χ2 = 2.027;68.42% vs. 73.53 %, χ2 = 1.594, respectively);however, without statistical significance (P = 0.154 and 0.207, respectively).Conclusions:The application of LCI at the corpus to identify H. pylori infection is reliable and superior to WLI. The inter-observer variability is lower with LCI than with WLI.

Least Squares Support Vector Machine Based Real-Time Fault Diagnosis Model for Gas Path Parameters of Aero Engines

Least squares support vector machine （LS-SVM） is applied in gas path fault diagnosis for aero engines. Firstly, the deviation data of engine cruise are analyzed. Then, model selection is conducted using pattern search method. Finally, by decoding aircraft communication addressing and reporting system （ACARS） report, a real-time cruise data set is acquired, and the diagnosis model is adopted to process data. In contrast to the radial basis function （RBF） neutral network, LS-SVM is more suitable for real-time diagnosis of gas turbine engine.

Real-time polymerase chain reaction for the diagnosis of necrotizing herpes stromal keratitis

AIM： To design, optimize and validate a rapid,internally controlled real-time polymerase chain reaction（RT-PCR） test for herpes simplex virus（HSV） in the diagnosis of necrotizing herpes stromal keratitis.· METHODS： Tears alone or together with corneal epithelium scrapings from 30 patients（30 eyes）suspected of necrotizing herpes stromal keratitis were tested for HSV DNA by RT-PCR. The samples were collected during the first visit and then on the subsequent 7, 14, 28, 42, and 56 d. The symptoms of the patients were scored before treatment to determine the correlation between HSV concentration in the corneal epithelium scrapings and clinical scores.·RESULTS： The positive rate（46.4%） in the corneal epithelium group before the therapy was significantly higher than that（13.3%） in the tears group（P =0.006）.There were 13 positive HSV patients before the therapy,the concentration of HSV DNA in corneal epithelium scrapings group was significantly higher than that in the tears group（paired t-test, P =0.0397）. Multilevel mixedeffects model analysis showed that the difference between the corneal epithelium scrapings group and the tears group was statistically significant（P =0.0049）. The Spearman rank correlation analysis indicated a positive correlation between the HSV concentration in the corneal epithelium scrapings and clinical scores before the treatment（r =0.844, P〈 0.0001）.· CONCLUSION： RT-PCR appears to be a powerful molecular tool for the diagnosis of necrotizing herpes stromal keratitis.

Raman spectroscopy for early real-time endoscopic optical diagnosis based on biochemical changes during the carcinogenesis of Barrett's esophagus

Raman spectroscopy is a spectroscopic technique based on the inelastic scattering of monochromatic light that represents the molecular composition of the interrogated volume to provide a direct molecular fingerprint. Several investigations have revealed that confocal Raman spectroscopy can differentiate non-dysplastic Barrett&rsquo;s esophagus from esophageal high-grade dysplasia and adenocarcinoma with high sensitivity and specificity. An automated on-line Raman spectral diagnostic system has made it possible to use Raman spectroscopy to guide accurate target biopsy instead of multiple random forceps-biopsies, this novel system is expected to improve in vivo precancerous diagnosis and tissue characterization of Barrett&rsquo;s esophagus.

Real-Time Automatic ECG Diagnosis Method Dedicated to Pervasive Cardiac Care

Recent developments of the wireless sensor network will revolutionize the way of remote monitoring in dif-ferent domains such as smart home and smart care, particularly remote cardiac care. Thus, it is challenging to propose an energy efficient technique for automatic ECG diagnosis (AED) to be embedded into the wireless sensor. Due to the high resource requirements, classical AED methods are unsuitable for pervasive cardiac care (PCC) applications. This paper proposes an embedded real-time AED algorithm dedicated to PCC sys-tems. This AED algorithm consists of a QRS detector and a rhythm classifier. The QRS detector adopts the linear time-domain statistical and syntactic analysis method and the geometric feature extraction modeling technique. The rhythm classifier employs the self-learning expert system and the confidence interval method. Currently, this AED algorithm has been implemented and evaluated on the PCC system for 30 patients in the Gabriel Monpied hospital (CHRU of Clermont-Ferrand, France) and the MIT-BIH cardiac arrhythmias da-tabase. The overall results show that this energy efficient algorithm provides the same performance as the classical ones.

A Study on FMS's Real-time Fault Diagnosis Expert System

ＡＳｔｕｄｙｏｎＦＭＳ＇ｓＲｅａｌ－ｔｉｍｅＦａｕｌｔＤｉａｇｎｏｓｉｓＥｘｐｅｒｔＳｙｓｔｅｍＸＩＡＯＸｉａｎｇｓｈｅｎｇ；ＬＩＵＷｅｎｊｉａｎ；ＳＵＢａｏｈｕａ；ＭＡＹｕｌｉｎ（肖祥胜，刘文剑，苏宝华，马玉林）（ＦＭＳＲｅｓｅａｒｃｈＣｅｎｔｅｒ...

Molecular diagnosis and direct quantification of cereal cyst nematode(Heterodera filipjevi) from field soil using TaqMan real-time PCR

Heterodera filipjevi continues to be a major threat to wheat production worldwide.Rapid detection and quantification of cyst nematodes are essential for more effective control against this nematode disease.In the present study,a TaqManminor groove binder(TaqMan-MGB)probe-based fluorescence quantitative real-time PCR(qPCR)was successfully developed and used for quantifying H.filipjevi from DNA extracts of soil.The primers and probe designed from the obtained RAPD-SCAR marker fragments of H.filipjevi showed high specificity to H.filipjevi using DNA from isolatesconfirmed species of 23 Heterodera spp.,1 Globodera spp.and 3 Pratylenchus spp.The qPCR assay is highly sensitive and provides improved H.filipjevi detection sensitivity of as low as 4^(-3) single second-stage juvenile(J2)DNAs,10^(-3) female DNAs,and 0.01μgμL^(-1) genomic DNAs.A standard curve relating to the threshold cycle and log values of nematode numbers was generated and validated from artificially infested soils and was used to quantify H.filipjevi in naturally infested field soils.There was a high correlation between the H.filipjevi numbers estimated from 32 naturally infested field soils by both conventional methods and the numbers quantified using the qPCR assay.qPCR potentially provides a useful platform for the efficient detection and quantification of H.filipjevi directly from field soils and to quantify this species directly from DNA extracts of field soils.

STUDY OF REAL-TIME EXPERT SYSTEM TOOL FOR INDUSTRIAL FAULT MONITORING AND DIAGNOSIS

From the requirements of industrial production,an integrated fault monitoring,diagnosis and repairing system is suggested in this paper. This new scheme of fault monitoring and diagnosis system is realized by a master-slave real-time expert system,and a real-time expert system tool for this system is also developed accordingly. As an example of application of this tool ,a realtime expert system for fault monitoring and diagnosis on DC mine hoist is developed. Experiments show that this tool possesses better supporting environment, strong knowledge acquisition ability, and convenience for use. The system developed by this tool not only meets the real-time requirement of DC hoist,but also can give correct diagnosis results.

Value of Real-Time Bedside Ultrasonography in the Etiologic Diagnosis of Acute Dyspnea

Objective: To explore the value of real-time bedside ultrasonography in the etiologic diagnosis of acute dyspnea. Methods: Sixty-two patients with acute dyspnea who were treated in our hospital from January 2016 to December 2020 were randomly selected and their clinical data were retrospectively analyzed. All patients were randomly divided into a control group for routine examinations (n = 31) and an observation group for real-time beside ultrasonography (n = 31). The costs of medical examinations, examination duration, and diagnostic results of severe pneumonia, acute cardiogenic pulmonary edema, pulmonary embolism, chronic obstructive pulmonary disease, and pneumothorax (including sensitivity, specificity, positive predictive value, negative predictive value, and diagnostic accuracy) of the two groups of patients were compared and analyzed. Results: Compared with the control group, the observation group had significantly shorter examinations (P < 0.05). Although the cost of medical examinations of the observation group tended to be higher, the difference between groups was not significant (P > 0.05). Moreover, there were no significant differences in left ventricular ejection fraction, left ventricular end-diastolic diameter, or brain natriuretic peptide between the two groups (P > 0.05). Comparison of the etiologic diagnosis results between the two groups showed that the observation group had significantly higher diagnostic sensitivity, specificity, positive and negative predictive values, and diagnostic accuracy for various causes compared with the control group (P < 0.05). Conclusion: Real-time bedside ultrasonography for the etiologic diagnosis of patients with acute dyspnea was quicker and had higher diagnostic accuracy;thus providing accurate guidance for the disease treatment, and having a higher promotional value in clinical practice compared with routine examinations.

Long-term fundus fluorescence angiography and real-time diagnosis of retinal diseases in non-human primate-animal models

Fluorescein angiography(FA)is a standard imaging modality for evaluating vascular abnormalities in retina-related diseases,which is recognized as the major cause of vision loss.Long-term and real-time fundus angiography is of great importance in preclinical research,nevertheless remaining big challenges up to present.In this study,we demonstrate that long-term fluorescence imaging of retinal vessels is enabled through a kind of fluorescent nanoagents,which is made of small-sized(hydrodynamic diameter:∼3 nm)silicon nanoparticles(SiNPs)featuring strong fluorescence,robust photostability,lengthened blood residency and negligible toxicity.In particular,the presented SiNPs-based nanoagents are capable of imaging retinal capillaries in∼10 min,which is around 10-fold longer than that(∼1 min)of fluorescein sodium(FS,known as the most widely used contrast agents for FA in clinic).Taking cynomolgus macaques as non-human primate-animal model,we further demonstrate the feasibility of real-time diagnosis of retinal diseases(e.g.,age-related macular degeneration(AMD))through dynamic monitoring of vascular dysfunction.

Machine learning for parameters diagnosis of spark discharge by electro-acoustic signal

Discharge plasma parameter measurement is a key focus in low-temperature plasma research.Traditional diagnostics often require costly equipment,whereas electro-acoustic signals provide a rich,non-invasive,and less complex source of discharge information.This study harnesses machine learning to decode these signals.It establishes links between electro-acoustic signals and gas discharge parameters,such as power and distance,thus streamlining the prediction process.By building a spark discharge platform to collect electro-acoustic signals and implementing a series of acoustic signal processing techniques,the Mel-Frequency Cepstral Coefficients(MFCCs)of the acoustic signals are extracted to construct the predictors.Three machine learning models(Linear Regression,k-Nearest Neighbors,and Random Forest)are introduced and applied to the predictors to achieve real-time rapid diagnostic measurement of typical spark discharge power and discharge distance.All models display impressive performance in prediction precision and fitting abilities.Among them,the k-Nearest Neighbors model shows the best performance on discharge power prediction with the lowest mean square error(MSE=0.00571)and the highest R-squared value(R^(2)=0.93877).The experimental results show that the relationship between the electro-acoustic signal and the gas discharge power and distance can be effectively constructed based on the machine learning algorithm,which provides a new idea and basis for the online monitoring and real-time diagnosis of plasma parameters.

Correlation analysis of real-time three-dimensional ultrasound in diagnosis of left ventricular function, portal hemodynamics and severity of liver function in patients with liver cirrhosis

Objective:To analyze the correlation between real-time three-dimensional ultrasound in diagnosis of left ventricular function, portal hemodynamics and severity of liver function in patients with liver cirrhosis.Methods: 90 patients with cirrhosis admitted to our hospital from January 2017 to December 2018 were enrolled in the cirrhosis group, and the cirrhosis components were group A, B and C according to the Child-Pauh classification criteria. During the same period, 90 healthy subjects who underwent physical examination were selected as the control group;real-time three-dimensional ultrasonography was performed to examine left ventricular function and portal hemodynamic parameters;Pearson correlation was used to analyze left ventricular function, portal hemodynamics and liver. Functional severity relationship.Results: The left heart E and E/A levels in the cirrhosis group were significantly lower than those in the control group (P<0.05), and the A level was significantly higher than the control group (P<0.05). The Dpv and Q levels in the cirrhosis group were significantly higher than those in the healthy control group. The difference was statistically significant (P<0.05), and the level of Vpv was significantly lower than that of healthy controls (P<0.05). There were significant differences in E, A and E/A levels between different Child-Paugh patients (P<0.05). There were significant differences in portal hemodynamics Dpv, Vpv and Q between the different Child-Paugh grades, and the difference was statistically significant (P<0.05);left heart function E and E/A and liver function severity There was a significant negative correlation (P<0.05). There was a significant positive correlation between left cardiac function A and liver function severity (P<0.05). Portal vein hemodynamics Dpv, Vpv and QE were significantly associated with liver function severity. Positive correlation (P<0.05). Conclusion: Real-time three-dimensional ultrasound can effectively detect left ventricular function and portal hemodynamics changes in patients with cirrhosis, and left heart function, portal hemodynamics and liver function severity are significantly correlated.

Evaluation of Clinical Application of Chemiluminescence and Real-time,Fluorescence-based Quantitative PCR in Diagnosis of Epstein-Barr Virus lnfection

Objective:To compare the effects of clinical application of chemiluminescence and real-time,fluorescence-based quantitative PCR in the detection Epstein-Barr virus(EBV).Methods:The data of chemiluminescence and real-time fluorescent quantitative PCR.fromipaEsfwo were suspected of being infectea w1tn rito1 roro January 2016 to January 2019 in our hospital were analyzed.The specific stage of EBV infection was analyzed,and the differences in results of the two detection methods were compared.Results:Chemiluminescence method was used to detect EBV infection during the active phase.The sensitivity of the chemiluminescence method was 76.7%(56/73)and the real-time quantitative PCRmethod was 90.4%(66/73).There was a statistical difference between the two detection methods(P<0.05).Conclusion:There was no statistical difference in positive predictive values between the chemiluminescence method and the real-time,fluorescence-based quantitative PCR method in the detection of EBV infection,but the sensitivity of chemiluminescence method is slightly lower than the real-time quantitative PCRmethod.It is noteworthy that chemiluminescence method is convenient and fast while the real-time,fluorescence-based quantitative PCR method is more accurate,which can provide a more accurate reference for clinical treatment.

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.