Detachable string magnetically controlled capsule endoscopy for the noninvasive diagnosis of esophageal diseases:A prospective,blind clinical study

BACKGROUND Traditional esophagogastroduodenoscopy(EGD),an invasive examination method,can cause discomfort and pain in patients.In contrast,magnetically controlled capsule endoscopy(MCE),a noninvasive method,is being applied for the detection of stomach and small intestinal diseases,but its application in treating esophageal diseases is not widespread.AIM To evaluate the safety and efficacy of detachable string MCE(ds-MCE)for the diagnosis of esophageal diseases.METHODS Fifty patients who had been diagnosed with esophageal diseases were pros-pectively recruited for this clinical study and underwent ds-MCE and conven-tional EGD.The primary endpoints included the sensitivity,specificity,positive predictive value,negative predictive value,and diagnostic accuracy of ds-MCE for patients with esophageal diseases.The secondary endpoints consisted of visualizing the esophageal and dentate lines,as well as the subjects'tolerance of the procedure.RESULTS Using EGD as the gold standard,the sensitivity,specificity,positive predictive value,negative predictive value,and diagnostic accuracy of ds-MCE for esophageal disease detection were 85.71%,86.21%,81.82%,89.29%,and 86%,respectively.ds-MCE was more comfortable and convenient than EGD was,with 80%of patients feeling that ds-MCE examination was very comfortable or comfortable and 50%of patients believing that detachable string v examination was very convenient.CONCLUSION This study revealed that ds-MCE has the same diagnostic effects as traditional EGD for esophageal diseases and is more comfortable and convenient than EGD,providing a novel noninvasive method for treating esophageal diseases.

Association of age at diagnosis of diabetes with subsequent risk of age-related ocular diseases and vision acuity

BACKGROUND The importance of age on the development of ocular conditions has been reported by numerous studies.Diabetes may have different associations with different stages of ocular conditions,and the duration of diabetes may affect the development of diabetic eye disease.While there is a dose-response relationship between the age at diagnosis of diabetes and the risk of cardiovascular disease and mortality,whether the age at diagnosis of diabetes is associated with incident ocular conditions remains to be explored.It is unclear which types of diabetes are more predictive of ocular conditions.AIM To examine associations between the age of diabetes diagnosis and the incidence of cataract,glaucoma,age-related macular degeneration(AMD),and vision acuity.METHODS Our analysis was using the UK Biobank.The cohort included 8709 diabetic participants and 17418 controls for ocular condition analysis,and 6689 diabetic participants and 13378 controls for vision analysis.Ocular diseases were identified using inpatient records until January 2021.Vision acuity was assessed using a chart.RESULTS During a median follow-up of 11.0 years,3874,665,and 616 new cases of cataract,glaucoma,and AMD,respectively,were identified.A stronger association between diabetes and incident ocular conditions was observed where diabetes was diagnosed at a younger age.Individuals with type 2 diabetes(T2D)diagnosed at<45 years[HR(95%CI):2.71(1.49-4.93)],45-49 years[2.57(1.17-5.65)],50-54 years[1.85(1.13-3.04)],or 50-59 years of age[1.53(1.00-2.34)]had a higher risk of AMD independent of glycated haemoglobin.T2D diagnosed<45 years[HR(95%CI):2.18(1.71-2.79)],45-49 years[1.54(1.19-2.01)],50-54 years[1.60(1.31-1.96)],or 55-59 years of age[1.21(1.02-1.43)]was associated with an increased cataract risk.T2D diagnosed<45 years of age only was associated with an increased risk of glaucoma[HR(95%CI):1.76(1.00-3.12)].HRs(95%CIs)for AMD,cataract,and glaucoma associated with type 1 diabetes(T1D)were 4.12(1.99-8.53),2.95(2.17-4.02),and 2.40(1.09-5.31),respectively.In multivariable-adjusted analysis,individuals with T2D diagnosed<45 years of age[β95%CI:0.025(0.009,0.040)]had a larger increase in LogMAR.Theβ(95%CI)for LogMAR associated with T1D was 0.044(0.014,0.073).CONCLUSION The younger age at the diagnosis of diabetes is associated with a larger relative risk of incident ocular diseases and greater vision loss.

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.

Application of artificial intelligence in the diagnosis and treatment of Kawasaki disease

This editorial provides commentary on an article titled"Potential and limitationsof ChatGPT and generative artificial intelligence(AI)in medical safety education"recently published in the World Journal of Clinical Cases.AI has enormous potentialfor various applications in the field of Kawasaki disease(KD).One is machinelearning(ML)to assist in the diagnosis of KD,and clinical prediction models havebeen constructed worldwide using ML;the second is using a gene signalcalculation toolbox to identify KD,which can be used to monitor key clinicalfeatures and laboratory parameters of disease severity;and the third is using deeplearning(DL)to assist in cardiac ultrasound detection.The performance of the DLalgorithm is similar to that of experienced cardiac experts in detecting coronaryartery lesions to promoting the diagnosis of KD.To effectively utilize AI in thediagnosis and treatment process of KD,it is crucial to improve the accuracy of AIdecision-making using more medical data,while addressing issues related topatient personal information protection and AI decision-making responsibility.AIprogress is expected to provide patients with accurate and effective medicalservices that will positively impact the diagnosis and treatment of KD in thefuture.

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.

Physician-dependent diagnosis delay in Crohn's disease:A pseudoproposition or not?

The challenge of diagnosis delay in inflammatory bowel disease(IBD)has emerged as a significant concern for both patients and healthcare professionals.The widely accepted notion that there is an extended time frame from the onset of symptoms to the definitive diagnosis is often attributed to the heterogeneity of IBD and the non-specificity of clinical manifestations.Specific to patients with Crohn’s disease,the issue of delayed diagnosis appears to be more pronounced across different regions globally.The intricate interplay of real-world factors has led to debates regarding the primary contributors to these diagnostic delays.Drawing a comparison solely between patients and physicians and implicating the latter as the predominant influence factor may fall into a simplistic either-or logical trap that may obscure the truth.This letter,grounded in published evidence,explores areas for improvement in a forthcoming paper within the field,hoping to pinpoint the culprit behind the diagnosis delay issue for IBD patients rather than simply attributing it to so-called“physician-dependent factors”.Our objective is to motivate healthcare providers and policymakers in relevant fields to reflect on strategies for addressing this problem to reduce diagnostic delays and enhance patient outcomes.

Soluble ST2:A Novel Biomarker for Diagnosis and Prognosis of Cardiovascular Disease

The increasing incidence of cardiovascular disease(CVD)is a significant global health concern,affecting millions of individuals each year.Accurate diagnosis of acute CVD poses a formidable challenge,as misdiagnosis can significantly decrease patient survival rates.Traditional biomarkers have played a vital role in the diagnosis and prognosis of CVDs,but they can be influenced by various factors,such as age,sex,and renal function.Soluble ST2(sST2)is a novel biomarker that is closely associated with different CVDs.Its low reference change value makes it suitable for continuous measurement,unaffected by age,kidney function,and other confounding factors,facilitating risk stratification of CVDs.Furthermore,the combination of sST2 with other biomarkers can enhance diagnostic accuracy and prognostic value.This review aims to provide a comprehensive overview of sST2,focusing on its diagnostic and prognostic value as a myocardial marker for different types of CVDs and discussing the current limitations of sST2.

Mean nocturnal baseline impedance in gastro-esophageal reflux disease diagnosis:Should we strictly follow the Lyon 2 Consensus?

Clinical practice guidelines drive clinical practice and clinicians rely to them when trying to answer their most common questions.One of the most important position papers in the field of gastro-esophageal reflux disease(GERD)is the one produced by the Lyon Consensus.Recently an updated second version has been released.Mean nocturnal baseline impedance(MNBI)was proposed by the first Consensus to act as supportive evidence for GERD diagnosis.Originally a cut-off of 2292 Ohms was proposed,a value revised in the second edition.The updated Consensus recommended that an MNBI<1500 Ohms strongly suggests GERD while a value>2500 Ohms can be used to refute GERD.The proposed cut-offs move in the correct direction by diminishing the original cut-off,nevertheless they arise from a study of normal subjects where cut-offs were provided by measuring the mean value±2SD and not in symptomatic patients.However,data exist that even symptomatic patients with inconclusive disease or reflux hypersensitivity(RH)show lower MNBI values in comparison to normal subjects or patients with functional heartburn(FH).Moreover,according to the data,MNBI,even among symptomatic patients,is affected by age and body mass index.Also,various studies have proposed different cut-offs by using receiver operating characteristic curve analysis even lower than the one proposed.Finally,no information is given for patients submitted to on-proton pump inhibitors pH-impedance studies even if new and extremely important data now exist.Therefore,even if MNBI is an extremely important tool when trying to approach patients with reflux symptoms and could distinguish conclusive GERD from RH or FH,its values should be interpreted with caution.

Association of autoimmune thyroid disease with type 1 diabetes mellitus and its ultrasonic diagnosis and management

As a common hyperglycemic disease,type 1 diabetes mellitus(T1DM)is a complicated disorder that requires a lifelong insulin supply due to the immunemediated destruction of pancreaticβcells.Although it is an organ-specific autoimmune disorder,T1DM is often associated with multiple other autoimmune disorders.The most prevalent concomitant autoimmune disorder occurring in T1DM is autoimmune thyroid disease(AITD),which mainly exhibits two extremes of phenotypes:hyperthyroidism[Graves'disease(GD)]and hypothyroidism[Hashimoto's thyroiditis,(HT)].However,the presence of comorbid AITD may negatively affect metabolic management in T1DM patients and thereby may increase the risk for potential diabetes-related complications.Thus,routine screening of thyroid function has been recommended when T1DM is diagnosed.Here,first,we summarize current knowledge regarding the etiology and pathogenesis mechanisms of both diseases.Subsequently,an updated review of the association between T1DM and AITD is offered.Finally,we provide a relatively detailed review focusing on the application of thyroid ultrasonography in diagnosing and managing HT and GD,suggesting its critical role in the timely and accurate diagnosis of AITD in T1DM.

Light-Activated Virtual Sensor Array with Machine Learning for Non-Invasive Diagnosis of Coronary Heart Disease

Early non-invasive diagnosis of coronary heart disease(CHD)is critical.However,it is challenging to achieve accurate CHD diagnosis via detecting breath.In this work,heterostructured complexes of black phosphorus(BP)and two-dimensional carbide and nitride(MXene)with high gas sensitivity and photo responsiveness were formulated using a self-assembly strategy.A light-activated virtual sensor array(LAVSA)based on BP/Ti_(3)C_(2)Tx was prepared under photomodulation and further assembled into an instant gas sensing platform(IGSP).In addition,a machine learning(ML)algorithm was introduced to help the IGSP detect and recognize the signals of breath samples to diagnose CHD.Due to the synergistic effect of BP and Ti_(3)C_(2)Tx as well as photo excitation,the synthesized heterostructured complexes exhibited higher performance than pristine Ti_(3)C_(2)Tx,with a response value 26%higher than that of pristine Ti_(3)C_(2)Tx.In addition,with the help of a pattern recognition algorithm,LAVSA successfully detected and identified 15 odor molecules affiliated with alcohols,ketones,aldehydes,esters,and acids.Meanwhile,with the assistance of ML,the IGSP achieved 69.2%accuracy in detecting the breath odor of 45 volunteers from healthy people and CHD patients.In conclusion,an immediate,low-cost,and accurate prototype was designed and fabricated for the noninvasive diagnosis of CHD,which provided a generalized solution for diagnosing other diseases and other more complex application scenarios.

Intestinal Behçet's disease: A review of clinical diagnosis and treatment

Behçet's disease(BD)is a chronic inflammatory disorder prone to frequent re-currences,with a high predilection for intestinal involvement.However,the ef-ficacy and long-term effects of surgical treatment for intestinal BD are unknown.In the current issue of World J Gastrointest Surg,Park et al conducted a retrospec-tive analysis of 31 patients with intestinal BD who received surgical treatment.They found that elevated C-reactive protein levels and emergency surgery were poor prognostic factors for postoperative recurrence,emphasizing the adverse impact of severe inflammation on the prognosis of patients with intestinal BD.This work has clinical significance for evaluating the postoperative condition of intestinal BD.The editorial attempts to summarize the clinical diagnosis and treatment of intestinal BD,focusing on the impact of adverse factors on surgical outcomes.We hope this review will facilitate more precise postoperative management of patients with intestinal BD by clinicians.

Extracellular vesicles in the diagnosis and treatment of central nervous system diseases

Extracellular vesicles,including exosomes and microvesicles,play a fundamental role in the activity of the nervous system,participating in signal transmission between neurons and providing the interaction of central nervous system with all body systems.In many neurodegenerative diseases,neurons pack toxic substances into vesicles and release them into the extracellular space,which leads to the spread of misfolded neurotoxic proteins.The contents of neuron-derived extracellular vesicles may indicate pathological changes in the central nervous system,and the analysis of extracellular vesicle molecular content contributes to the development of non-invasive methods for the diagnosis of many central nervous system diseases.Extracellular vesicles of neuronal origin can be isolated from various biological fluids due to their ability to cross the blood-brain barrier.Today,the diagnostic potential of almost all toxic proteins involved in nervous system disease pathogenesis,specificallyα-synuclein,tau protein,superoxide dismutase 1,FUS,leucine-rich repeat kinase 2,as well as some synaptic proteins,has been well evidenced.Special attention is paid to extracellular RNAs mostly associated with extracellular vesicles,which are important in the onset and development of many neurodegenerative diseases.Depending on parental cell type,extracellular vesicles may have different therapeutic properties,including neuroprotective,regenerative,and anti-inflammatory.Due to nano size,biosafety,ability to cross the blood-brain barrier,possibility of targeted delivery and the lack of an immune response,extracellular vesicles are a promising vehicle for the delivery of therapeutic substances for the treatment of neurodegenerative diseases and drug delivery to the brain.This review describes modern approaches of diagnosis and treatment of central nervous system diseases using extracellular vesicles.

Saliva in the diagnosis of diseases

Saliva is secreted from the salivary glands and has multiple functions, including mouth cleaning and protection, antibacterial effects and digestion. With the rapid advancement in salivaomics, saliva is well recognized as a pool of biological markers. Saliva, as a non-invasive and safe source, could be a substitute for blood in the diagnosis and prognosis of diseases. This review summarizes the latest advancements in saliva-related studies and addresses the potential value of saliva in the early diagnosis of oral diseases, such as dental caries and periodontal disease, as well as cancer, diabetes and other systemic disorders. Saliva biomarkers range from changes in the biochemical indices of DNA, RNA and proteins to the diversification of microbiota structures. This study integrates data reported in the recent literature and discusses the clinical significance and prospects for the application of saliva in the early diagnosis of diseases, translational medicine and precision medicine.

Usefulness of fecal lactoferrin and hemoglobin in diagnosis of colorectal diseases

AIM:To evaluate prospectively usefulness of fecal lactoferrin(Lf)and fecal hemoglobin(Hb)in the diagnosis of colorectal diseases.METHODS:Fecal Lf and Hb were measured using ELISA in 872 patients before they underwent colorectal endoscopy.RESULTS:Lf was positive in 18(50%)of 36 patients with colorectal cancer,25(15.9%)of 157 with colorectal polyps,29(46.8%)of 62 with ulcerative colitis,and 25(62.5%)of 40(62.5%)with Crohn's disease.The Hb-positive rates were 50%,12.1%,41.9% and 32.5%,respectively.Of the 318 patients free of abnormalities by colorectal endoscopy,Lf was positive in 29(9.1%)and Hb was positive in 15(4.7%).Among patients with Crohn's disease,the Lf-positive rate was significantly higher than the Hb-positive rate.If either high Lf or Hb levels were considered positive,the positive rates rose to 61.1%,51.6%,and 67.5% in the colorectal cancer group,ulcerative colitis group,and Crohn's disease group,respectively.If both high Lf and Hb levels were rated positive,the positive predictive values(PPV)were 21% for colorectal cancer,33% for ulcerative colitis,and 17% for Crohn's disease,and PPV of high Hb level alone was 18%,25% and 13%,respectively.CONCLUSION:Fecal Lf and Hb were found useful in the detection of colorectal diseases,and the combination of the two measurements appears to increase the sensitivity and efficacy of diagnosis.

Innovative Artificial Neural Networks-Based Decision Support System for Heart Diseases Diagnosis

Heart diagnosis is not always possible at every medical center, especially in the rural areas where less support and care, due to lack of advanced heart diagnosis equipment. Also, physician intuition and experience are not always sufficient to achieve high quality medical procedures results. Therefore, medical errors and undesirable results are reasons for a need for unconventional computer-based diagnosis systems, which in turns reduce medical fatal errors, increasing the patient safety and save lives. The proposed solution, which is based on an Artificial Neural Networks (ANNs), provides a decision support system to identify three main heart diseases: mitral stenosis, aortic stenosis and ventricular septal defect. Furthermore, the system deals with an encouraging opportunity to develop an operational screening and testing device for heart disease diagnosis and can deliver great assistance for clinicians to make advanced heart diagnosis. Using real medical data, series of experiments have been conducted to examine the performance and accuracy of the proposed solution. Compared results revealed that the system performance and accuracy are acceptable, with a heart diseases classification accuracy of 92%.

Six cases report of differential diagnosis of periapical diseases

The distinction of some particular forms of periapical area, involving diseases from regular periapical disease, is a matter of considerable importance when choosing a correct treatment. The aim of this study is to describe the differential diagnosis of F,eriapical diseases from six rare cases in clinical practice. The six rare cases are examples of situations where it is difficult to make a differential diagnosis in clinical practice. By retrospective surveys on the clinical examination, radiographs and pathological results, six patients referred to endodontic treatment in our department were analyzed for the accuracy of diagnosis and therapy. The pathoses of the six cases included two atypical radical cysts, periapical cemental dysplasia, cemento-ossifying fibroma, thymus cancer metastasis in the periapical site and tuberculosis. This report indicates that endodontists should be cognizant of a few particular circumstances when clinically treating periapical diseases.

Deep Learning Based Automated Diagnosis of Skin Diseases Using Dermoscopy

Biomedical image analysis has been exploited considerably by recent technology involvements,carrying about a pattern shift towards‘automation’and‘error free diagnosis’classification methods with markedly improved accurate diagnosis productivity and cost effectiveness.This paper proposes an automated deep learning model to diagnose skin disease at an early stage by using Dermoscopy images.The proposed model has four convolutional layers,two maxpool layers,one fully connected layer and three dense layers.All the convolutional layers are using the kernel size of 3∗3 whereas the maxpool layer is using the kernel size of 2∗2.The dermoscopy images are taken from the HAM10000 dataset.The proposed model is compared with the three different models of ResNet that are ResNet18,ResNet50 and ResNet101.The models are simulated with 32 batch size and Adadelta optimizer.The proposed model has obtained the best accuracy value of 0.96 whereas the ResNet101 model has obtained 0.90,the ResNet50 has obtained 0.89 and the ResNet18 model has obtained value as 0.86.Therefore,features obtained from the proposed model are more capable for improving the classification performance of multiple skin disease classes.This model can be used for early diagnosis of skin disease and can also act as a second opinion tool for dermatologists.

Classification Methods Based on Pattern Discrimination Models for Web-Based Diagnosis of Rice Diseases

Two classification and identification methods based on pattern discrimination models and the majority-vote technique were investigated for implementing a World Wide Web-based system for the identification of rice diseases. The experiment was carried out using color and shape patterns in 425 images of three rice diseases, which were classified into four classes： two classes of leaf blast, and one class each of sheath blight and brown spot. A method consisting of two discrimination steps involving application of multiple discrimination models of a support vector machine gave the best result because of its capacity to evaluate the similarity of disease types. This accuracy of the method was 88% for leaf blast （A-type）, 94% for sheath blight, and 80% for leaf blast （B-type） and brown spot; on average, the accuracy of this method was 5% greater than that of the other method when three classes were used in the model. Although the accuracy of both methods was inadequate, the results of this study show that it is possible to estimate the least number of possible or similar diseases from a large number of diseases. Therefore, we conclude that there is merit in grouping classes into subgroups rather than attempting to discriminate between all classes simultaneously and that these methods are effective in identifying diseases for web-based diagnosis.

Clinical Application Value of Combined Detection of CG and TBA in Differential Diagnosis of Hepatobiliary System Diseases

Objective: To understand the clinical value of combined detection of cholyglycine CG and TBA in differential diagnosis of hepatobiliary diseases. Methods: Serum samples from 50 healthy people were collected as healthy control group. According to the latest disease diagnosis and treatment plan, 58 cases of HBV asymptomatic carrier group, 17 cases of viral hepatitis group, 49 cases of cirrhosis group, 50 cases of primary liver cancer group and 50 cases of other hepatobiliary diseases groups were collected respectively. The concentration levels of cholyglycine and total bile acid in each group were detected, and the differences among each group were compared. Results: By statistical analysis, serum CG concentration in viral hepatitis group, cirrhosis group, primary liver cancer group and other hepatobiliary diseases group was significantly higher than that in asymptomatic HEPATITIS B carriers and healthy control group, the differences were statistically significant (p 0.05). There was no significant difference in CG concentration among viral hepatitis group, liver cirrhosis group, primary liver cancer group and other hepatobiliary diseases group (p > 0.05). The serum TBA levels of asymptomatic carriers, viral hepatitis group, cirrhosis group, primary liver cancer group and other hepatobiliary system diseases group were significantly higher than those of healthy control group, the difference was statistically significant, p 0.05. Conclusion: Serum CG expression can not only detect liver lesions, but also distinguish different liver lesions. The positive rate of CG combined with TBA detection in patients with hepatobiliary diseases is significantly higher than that of single CG index detection. CG combined with TBA detection can significantly improve the sensitivity and accuracy of the diagnosis of hepatobiliary diseases, which is worthy of popularization and application.

A New Method for Cardiac Diseases Diagnosis

The objective of this work is to perform automatic diagnosis using a non invasive method which consists on the bioimpedance signal processing. Bioimpedance signal (BIS) represents the aorta impedance variation during the heart cycle activity. BIS is detected by mean of two electrodes located at the level of the ascendant aorta. Automatic diagnosis method consists on preparing, first, a data base with a set of cepstral parameters of different BIS according to normal case and different cardiac diseases. This data base is composed from n classes Yk corresponding to n diseases. The classification of anonymous individuals is based on the determination of Fisher distance between anonymous disease and class Yk using Fischer formula. Our method permits to calculate seven relevant cepstral parameters. The application of Fisher method has allowed us to perform the diagnosis of five anonymous cases. The major interest of this method is its especially useful for the exploration of cardiovascular system anomalies for emergency cases, children, elderly and pregnant women who can’t support surgical operations especially at the level of the heart.