ZIZ-2 Vibration monitoring and diagnosing system for turbine generator units

ZJZ-2 system has the following functions: (1) Real-time on-line sampling and FFT analysis (32 channel); (2) Data aquisition, analysis and storage during start-up and shut-down; (3) Alarming, emergency recognition and fault retrieval; (4) Data aquisition, analysis and storage during daily operation; (5) Recall of historic data; (6) Output of routine reports and tables; (7) Analysis of vibration behaviour: Bode plot, polar plot, spectrum, cascade, waveform, shaft orbit, trend, etc;

Fault Diagnosing System of Steam Generator for Nuclear Power Plant Based on Fuzzy Neural Networks

All kinds of reasons are analysed in theory and a fault repository combined with local expert experiences is establishedaccording to the structure and the operation characteristic of steam generator in this paper. At the same time, Kohonen algo-rithm is used for fault diagnoses system based on fuzzy neural networks. Fuzzy arithmetic is inducted into neural networks tosolve uncertain diagnosis induced by uncertain knowledge. According to its self-association in the course of default diagnosis. thesystem is provided with non-supervise, self-organizing, self-learning, and has strong cluster ability and fast cluster velocity.

Prediction System for Diagnosis and Detection of Coronavirus Disease-2019(COVID-19):A Fuzzy-Soft Expert System

In early December 2019,a new virus named“2019 novel coronavirus(2019-nCoV)”appeared in Wuhan,China.The disease quickly spread worldwide,resulting in the COVID-19 pandemic.In the currentwork,we will propose a novel fuzzy softmodal(i.e.,fuzzy-soft expert system)for early detection of COVID-19.Themain construction of the fuzzy-soft expert systemconsists of five portions.The exploratory study includes sixty patients(i.e.,fortymales and twenty females)with symptoms similar to COVID-19 in(Nanjing Chest Hospital,Department of Respiratory,China).The proposed fuzzy-soft expert systemdepended on five symptoms of COVID-19(i.e.,shortness of breath,sore throat,cough,fever,and age).We will use the algorithm proposed by Kong et al.to detect these patients who may suffer from COVID-19.In this way,the present system is beneficial to help the physician decide if there is any patient who has COVID-19 or not.Finally,we present the comparison between the present system and the fuzzy expert system.

COVID TCL:A Joint Metric Loss Function for Diagnosing COVID-19 Patient in the Early and Incubation Period

Convolution Neural Networks(CNN)can quickly diagnose COVID-19 patients by analyzing computed tomography(CT)images of the lung,thereby effectively preventing the spread of COVID-19.However,the existing CNN-based COVID-19 diagnosis models do consider the problem that the lung images of COVID-19 patients in the early stage and incubation period are extremely similar to those of the non-COVID-19 population.Which reduces the model’s classification sensitivity,resulting in a higher probability of the model misdiagnosing COVID-19 patients as non-COVID-19 people.To solve the problem,this paper first attempts to apply triplet loss and center loss to the field of COVID-19 image classification,combining softmax loss to design a jointly supervised metric loss function COVID Triplet-Center Loss(COVID-TCL).Triplet loss can increase inter-class discreteness,and center loss can improve intra-class compactness.Therefore,COVID-TCL can help the CNN-based model to extract more discriminative features and strengthen the diagnostic capacity of COVID-19 patients in the early stage and incubation period.Meanwhile,we use the extreme gradient boosting(XGBoost)as a classifier to design a COVID-19 images classification model of CNN-XGBoost architecture,to further improve the CNN-based model’s classification effect and operation efficiency.The experiment shows that the classification accuracy of the model proposed in this paper is 97.41%,and the sensitivity is 97.61%,which is higher than the other 7 reference models.The COVID-TCL can effectively improve the classification sensitivity of the CNN-based model,the CNN-XGBoost architecture can further improve the CNN-based model’s classification effect.

DEBRIS MONITORING AND ANALYZING SYSTEM (DMAS) AND ITS APPLICATION IN AEROENGINE

By inspecting and analyzing the debris, which is the most direct and important information units in the lubricating oil, we can monitor the machine condition to predict its failure. The debris monitoring and analyzing system (DMAS) is developed from the traditional iron spectrum technology, and has such characteristics as ease for debris separating, forecasting machine failure automatically and accurately in time and so on. The fundamental theory, components and its application in aeroengine health monitoring of DMAS are presented.

Reliability Assessment of a New General Matching Composed Network

The reliability of a network is an important indicator for maintaining communication and ensuring its stable operation. Therefore, the assessment of reliability in underlying interconnection networks has become an increasingly important research issue. However, at present, the reliability assessment of many interconnected networks is not yet accurate,which inevitably weakens their fault tolerance and diagnostic capabilities. To improve network reliability,researchers have proposed various methods and strategies for precise assessment. This paper introduces a novel family of interconnection networks called general matching composed networks(gMCNs), which is based on the common characteristics of network topology structure. After analyzing the topological properties of gMCNs, we establish a relationship between super connectivity and conditional diagnosability of gMCNs. Furthermore, we assess the reliability of g MCNs, and determine the conditional diagnosability of many interconnection networks.

Non-coding RNA as future target for diagnose and treatment of perineural invasion in cancers

Perineural invasion(PNI),a particularly insidious form of tumor metastasis distinct from hematogenous or lymphatic spread,has the capacity to extend well beyond the primary tumor site,infiltrating distant regions devoid of lymphatic or vascular structures.PNI often heralds a decrease in patient survival rates and is recognized as an indicator of an unfavorable prognosis across a variety of cancers.Despite its clinical significance,the underlying molecular mechanisms of PNI remain elusive,complicating the development of specific and efficacious diagnostic and therapeutic strategies.In the realm of cancer research,non-coding RNAs(ncRNAs)have attracted considerable attention due to their multifaceted roles and cancer-specific expression profiles,positioning them as promising candidates for applications in cancer diagnostics,prognostics,and treatment.Among the various types of ncRNAs,microRNAs(miRNAs),long non-coding RNAs(lncRNAs),and circular RNAs(circRNAs)have emerged as influential players in PNI.Their involvement is increasingly recognized as a contributing factor to tumor progression and therapeutic resistance.Our study synthesizes and explores the diverse functions and mechanisms of ncRNAs in relation to PNI in cancer.This comprehensive review aims to shed light on cutting-edge perspectives that could pave the way for innovative diagnostic and therapeutic approaches to address the challenges posed by PNI in oncology.

Intra-thyroid esophageal duplication cyst:A case report

BACKGROUND Esophageal cysts are relatively rare in clinical practice,with most of the literature comprising case reports.Esophageal cysts protruding into the thyroid gland are easily misdiagnosed as thyroid tumors.No such cases have been reported so far.CASE SUMMARY This article reports the case of a 31-year-old adult male diagnosed with thyroid nodules before admission.The patient underwent left thyroidectomy and isthmusectomy.During the surgery,esophageal cysts were identified in the esophageal muscle and thyroid glands.The pathology results confirmed a nodular goiter combined with esophageal cysts.Postoperatively,the patient developed a neck infection and underwent another operation and broad-spectrum antibiotic treatment for recovery.CONCLUSION We report the first clinical case of an esophageal cyst located within the thyroid gland that was successfully treated surgically.Esophageal cyst located within the thyroid gland cause difficulties in diagnosis.In the present study,the contents of the esophageal cysts were calcified foci,and a small amount of fluid mixture,which were easily misdiagnosed as thyroid nodules and misled the surgical methods.

Construction of the underlying circRNA-miRNA-mRNA regulatory network and a new diagnostic model in ulcerative colitis by bioinformatics analysis

BACKGROUND Circular RNAs(circRNAs)are involved in the pathogenesis of many diseases through competing endogenous RNA(ceRNA)regulatory mechanisms.AIM To investigate a circRNA-related ceRNA regulatory network and a new predictive model by circRNA to understand the diagnostic mechanism of circRNAs in ulcerative colitis(UC).METHODS We obtained gene expression profiles of circRNAs,miRNAs,and mRNAs in UC from the Gene Expression Omnibus dataset.The circRNA-miRNA-mRNA network was constructed based on circRNA-miRNA and miRNA-mRNA interactions.Functional enrichment analysis was performed to identify the biological mechanisms involved in circRNAs.We identified the most relevant differential circRNAs for diagnosing UC and constructed a new predictive nomogram,whose efficacy was tested with the C-index,receiver operating characteristic curve(ROC),and decision curve analysis(DCA).RESULTS A circRNA-miRNA-mRNA regulatory network was obtained,containing 12 circRNAs,three miRNAs,and 38 mRNAs.Two optimal prognostic-related differentially expressed circRNAs,hsa_circ_0085323 and hsa_circ_0036906,were included to construct a predictive nomogram.The model showed good discrimination,with a C-index of 1(>0.9,high accuracy).ROC and DCA suggested that the nomogram had a beneficial diagnostic ability.CONCLUSION This novel predictive nomogram incorporating hsa_circ_0085323 and hsa_circ_0036906 can be conveniently used to predict the risk of UC.The circRNa-miRNA-mRNA network in UC could be more clinically significant.

Detecting Lumbar Implant and Diagnosing Scoliosis from Vietnamese X-Ray Imaging Using the Pre-Trained API Models and Transfer Learning

With the rapid growth of the autonomous system,deep learning has become integral parts to enumerate applications especially in the case of healthcare systems.Human body vertebrae are the longest and complex parts of the human body.There are numerous kinds of conditions such as scoliosis,vertebra degeneration,and vertebrate disc spacing that are related to the human body vertebrae or spine or backbone.Early detection of these problems is very important otherwise patients will suffer from a disease for a lifetime.In this proposed system,we developed an autonomous system that detects lumbar implants and diagnoses scoliosis from the modified Vietnamese x-ray imaging.We applied two different approaches including pre-trained APIs and transfer learning with their pre-trained models due to the unavailability of sufficient x-ray medical imaging.The results show that transfer learning is suitable for the modified Vietnamese x-ray imaging data as compared to the pre-trained API models.Moreover,we also explored and analyzed four transfer learning models and two pre-trained API models with our datasets in terms of accuracy,sensitivity,and specificity.

Evaluation of fault diagnosability for nonlinear uncertain systems with multiple faults occurring simultaneously

Up to present,the problem of the evaluation of fault diagnosability for nonlinear systems has been investigated by many researchers.However,no attempt has been done to evaluate the diagnosability of multiple faults occurring simultaneously for nonlinear systems.This paper proposes a method based on differential geometry theories to solve this problem.Then the evaluation of fault diagnosability for affine nonlinear systems with multiple faults occurring simultaneously is achieved.To deal with the effect of control laws on the evaluation results of fault diagnosability,a design scheme of the evaluation of fault diagnosability is proposed.Then the influence of uncertainties on the evaluation results of fault diagnosability for affine nonlinear systems with multiple faults occurring simultaneously is analyzed.The numerical simulation results are obtained to show the effectiveness of the proposed evaluation scheme of fault diagnosability.

Progress in the Treatment of Fungal Infections of the Central Nervous System

HThe incidence of fungal infections of the central nervous system(CNS) has gradually increased in recent years. Intracranial fungal infection can be classified as diffuse and focal infections. The clinical manifestations of these infections include fever and cranial pressure caused by meningitis or meningoencephalitis, and focal neurological defects caused by lesions in the intracranial space. Diagnosing fungal infections of the CNS requires the comprehensive analysis of the patient's medical history, epidemiology, underlying disease, clinical manifestation, imaging manifestations, and various laboratory test results. The identification of fungal bodies or structures in brain tissue or cerebrospinal fluid specimens is the golden standard of diagnosis. The principles for the treatment of the fungal infections of the CNS are the effective control of pathogenic risk factors, use of effective antifungal drugs, and the active implementation of surgical intervention for fungal abscesses and granuloma. In the meantime, new diagnoses and treatments should be actively explored to improve the prognosis of patients.

Some Properties of the g-Good-Neighbor (g-Extra) Diagnosability of a Multiprocessor System

Diagnosability of a multiprocessor system is one important study topic. In 2012, Peng et al. proposed a measure for fault tolerance of the system, which is called the g-good-neighbor diagnosability that restrains every fault-free node containing at least g fault-free neighbors. In 2015, Zhang et al. proposed a measure for fault diagnosis of the system, namely, g-extra diagnosability, which restrains that every fault-free component has at least g+1 fault-free nodes. In this paper, we obtain some properties of the g-good-neighbor (g-extra) diagnosability of the system and give the g-good-neighbor (g-extra) diagnosability of some graphs under the PMC model and MM* model.

Application of ^(18) F-FDG PET/CT Imaging in Diagnosing Bladder Tumor Metastasis Lesions

Bladder tumor is the most common malignant tumor in urinary system and always com- panied with lymph node metastasis. The accurate staging plays a significant role in treatment for bladder tumor and prognostic evaluation, and the distant metastasis predicts worse prognosis. The objective of this study was to assess the clinical significance of 18F-FDG PET/CT imaging in diagnosing bladder tumor metastasis lesions. A retrospective analysis of 60 patients with bladder tumor from October 2008 to May 2010 was done. The patients were stratified based on the imaging technique. Among all 60 cases, besides the primary lesion, 81 suspected lesions were spotted and 73 confirmed as metastasis, including 50 lymph node metastases, 22 distant metastases, and 1 bone metastasis. For PET/CT imaging, its sensitivity was 94.5%, specificity 87.5%, positive predictive value 98.6%, negative predictive value 63.6% and accuracy 93.8% respectively. For CT, its sensitivity was 82.2%, specificity 50%, positive predictive value 93.8%, negative predictive value 23.5% and accuracy 79% respectively. PET/CT im- aging was superior to CT in sensitivity, specificity and accuracy. In conclusion, 18F-FDG PET/CT imaging is more significant in diagnosing bladder tumor metastasis lesions.

Petri net model for diagnosis of permanent faults of a hydraulic system

Petri net model is applied to diagnose the permanent fault of hydraulic system within the framework of interpreted Petri net. The permanent fault is described as redundant structure of the model. A definition and a theorem are proposed to determine the diagnosability of the hydraulic system. The relations bwtween the diagnosability and other structure properties are also discussed. An example of actual hydraulic system is presented and its permanent fault can be diagnosed by the proposed method efficiently.

Carotid Doppler and transcranial Doppler in diagnosing transient ischemic attack: A healthy control

BACKGROUND： If changes of hemodynamics in internal or external cranial artery and stenosis of atherosclerosis are found eady, patients with transient ischemic attack （TIA） may be treated at an eady phase so as to prevent and decrease the onset of cerebral infarction. Carotid Doppler can analyze carotid canal wall, hemodynamic properties and stenosis, and changes of plaque morphology; however, transcranial Doppler （TCD） can evaluate vascular stenosis and occlusion and judge collateral circulation in cranium through detecting velocity and direction of blood flow. Can the association of them increase the diagnostic rate of TIA？ OB3ECTIVE： To evaluate the effect of the association of carotid Doppler and TCD on TIA in internal carotid artery. DESIGN： Contrast observational study SETTING： Department of Neuroelectrophysiology, Central People＇s Hospital of Huizhou PARTICIPANTS： A total of 54 patients with TIA in internal carotid artery were selected from the Department of Neurology of Huizhou Central People＇s Hospital from May 2004 to June 2005. There were 35 males and 24 females aged 46-81 years. The clinical situation was asthenia of single limb, hemiplegia, anaesthesia of single upper or lower limb, hemianesthesia, sensory disorder and aphasia. The symptoms lasted for less than 2 hours. All cases were diagnosed with CT, and those who had pathological changes of acute cerebral infarction and history of cardiac disease were excluded. Additionally, 50 healthy subjects who were regarded as control group were selected from the Department of Neurology of Huizhou Central People＇s Hospital. There were 30 males and 20 females aged 45-80 years. All subjects were consent. METHODS： HD15000 color Doppler ultrasound （Philips Company, USA） and Muliti-DopX2 TCD （DWL Company, Germany） were used to detect hemodynamics, stenosis and distribution of atherosclerosis in carotid artery and internal carotid artery. Evaluation of marker： Stenosis was calculated by the ratio between the minimal cavity and vascular sectional area at the maximal site of plaque （mild： stenosis 〈 50%; moderate and severe： stenosis t〉 50%）. With TCD, the following results were regarded as stenosis： blood velocity of average envelope 〉 120 cm/s （diagnostic criteria of vascular stenosis of basilar artery： blood velocity of average envelope 〉 80 cm/s）, increase and segmental property of blood flow, and murmu of turbulent flow and vessel. MAIN OUTCOME MEASURES： Positive rate of atherosclerosis and incidence of stenosis with carotid Doppler and TCD. RESULTS： All 54 TIA patients and 50 healthy subjects were involved in the final analysis. ① Results of carotid Doppler： Atherosclerosis and stenosis were obvious in experimental group. Positive rate of atherosclerosis was 85% （46/54） and incidence of stenosis of carotid artery was 41% （22/54）, which were higher than those in control group [52% （26/54）, 41% （22/54）, x^2 = 13.42, 10.90, P 〈 0.01]. ② Results of TCD： In experimental group, positive rate of atherosclerosis at base of skull was 89% （48/54） and incidence of stenosis of internal cranial artery was 48% （26/54）, which were higher than those in control group [62% （31/50）, 0, x^2 = 10.28, 32.00, P 〈 0.01]. Stenosis of artery was mainly involved in middle cerebral artery, initial segment and crotch of carotid artery. CONCLUSION： The association of carotid Doppler and TCD can increase clinically diagnostic rate of TIA and provide bases for apposition and intensity of TIA lesion.

Auditory steady-state evoked response in diagnosing and evaluating hearing in infants

BACKGROUND: Auditory steady-state evoked response (ASSR) is one of the new objective electrophysiological methods to test hearing in infants. It can provide a reliable and complete audiogram with specific frequency to help the hearing diagnosis and rehabilitation of hearing and languaging following auditory screening. OBJECTIVE: To compare the response threshold of ASSR with auditory threshold of visual reinforcement audiometry (VRA) in infants failed in the hearing screening for investigating their hearing loss. DESIGN: A comparative observation. SETTINGS: Maternal and child health care hospitals of Guangdong province, Shunde city, Nanhai city and Huadu district. PARTICIPANTS: Totally 321 infants of 0-3 years undergoing ASSR test were selected from the Hearing Center of Guangdong Maternal and Child Health Care Hospital from January 2002 to December 2004. Informed consents were obtained from their guardians. There were 193 cases (60.2%) of 0-6 months, 31 cases (9.7%) of 7-12 months, 17 cases (5.3%) of 13-18 months, 14 cases (4.4%) of 19-24 months, 33 cases of 25-30 months, and 33 cases (10.2%) of 31-36 months. METHODS: ① The 321 infants failed in the hearing screening were tested under sleeping status, the ranges of response threshold distribution in ASSR of different frequencies were analyzed in each age group. ② The infants above 2 years old were also tested with VRA, and their response thresholds were compared between VRA and ASSR. ③ Evaluative standards: The response threshold was < 30 dB for normal hearing, 31-50 dB for mild hearing loss, 51-70 dB for moderate hearing loss, 71-90 dB for severe hearing loss, and > 91 dB for extremely severe hearing loss. MAIN OUTCOME MEASURES: ① ASSR results of the infants failed in the screening; ② Proportion of cases of each response threshold in each age group; ③ Comparison of ASSR response thresholds and VRA auditory thresholds in the infants of 2-3 years old. RESULTS: ①The response threshold was < 30 dB in 47.4% of the 321 infants failed in the initial hearing screening and secondary screening after 42 days. ② Severe to extremely severe hearing loss was detected in only 16 cases (8.3%) of the 193 infants of 0-6 months, in 9 cases (27.3%) of the 33 infants of 25-30 months, and 13 cases (39.4%) of the 33 infants of 31-36 months. Of the 193 infants of 0-6 months old who failed in the initial screening and the second screening after 42 days, the ASSR auditory threshold was < 30 dB in 97 cases (50.26%), 31-50 dB in 63 cases (32.6%), 51-70 dB in 17 cases (8.8%), 71-90 dB in 7 cases (3.6%), and > 91 dB in 9 cases (4.7%). ③ Among the 321 infants failed in the screening, the auditory threshold in the 6 age groups was < 30 dB in 47.4%, 31-50 dB in 27.1%, 51-70 dB in 8.4%, 71-90 dB in 6.2%, and > 91 dB in 10.9%. ④ The difference between ASSR response threshold and VRA auditory thresholds was 6-18 dB in the normal hearing group, mild and moderate hearing loss groups, and there was high correlation between them. The difference of ASSR and VRA thresholds was less than 5 dB between extremely severe and severe hearing loss groups, 5-13 dB between extremely severe and moderate-to-severe hearing loss groups (P < 0.05), and there was no significant differences between severe and moderate-to-severe hearing loss groups (P > 0.05). CONCLUSION: ① The hearing was normal in about half of the infants, although they failed in the primary screening and secondary screening. ② The proportion of the severity of hearing loss was increased along with aging. ③ Mild and moderate hearing losses are dominant in infants. ④ ASSR is reliable to evaluate the hearing of infants.

Diagnosing Dysfunctional Coping in HIV-Infected Persons

Introduction: Dysfunctional coping may negatively affect the effectiveness of highly active anti-retro-viral therapy (HAART) to achieve viral suppression. Despite its negative effects on health outcomes, dysfunctional coping remains undiagnosed and untreated in HIV patients. Therefore, it would seem important to diagnose dysfunctional coping in HIV-patients in order to enable health care providers’ plan and execute intervention and treatment strategies in a population of HIV-patients/HIV-infected persons, to reduce health problems that may be associated with it. Aims/Objectives: 1) To identify elements of dysfunctional coping in HIV-patients. 2) To screen HIV-infective persons for dysfunctional coping. 3) To assess prevalence of dysfunctional coping among HIV-patients. 4) To assess association of duration of HIV-infection (survivability) with dysfunctional coping in HIV-infected persons. Methods: A cross-sectional descriptive study was carried out, to diagnose dysfunctional coping in HIV-infected patients. Subjects were HIV patients receiving HAART at Ahmadu Bello University Teaching Hospital (ABUTH), Zaria, Nigeria. Over 110 HIV-infected persons were screened for dysfunctional coping, using 28-item Brief Cope Questionnaire. Results: After various forms of statistical analyses were performed on the data, results indicate differing prevalent rates for the four key dimensions of dysfunctional coping derived from the Brief-cope questionnaire, used to measure dysfunctional coping in this study;Denial Coping, 68 (61.8 percent), Behavioral Disengagement Coping, 46 (41.8 percent), Substance Use Coping, 24 (21.8 percent), Self-Blame Coping, 61 (55.5 percent);and composite (Integrated/Combined) dysfunctional coping, 49 (44.5 percent). A total prevalence rate of 44.5 percent was reported. Altogether more than 60 percent of the HIV patients screened positive for one dimension of dysfunctional coping or the other. The qui-square analyses revealed an association of denial coping with duration of HIV-infection/survivability. Conclusion/Recommendation: Overall, the study was able to demonstrate that dysfunctional coping was quite common among HIV patients. Dysfunctional coping may be a determinant of health in HIV patients and significantly affect health outcome. It was therefore recommended that interventions focused on coping strategies be integrated into management of HIV patients in order to improve their psychological and physical wellbeing.

Teaching Strategy on Diagnosing and Removing Automobile’s Failure

:This article first analyzes the problems existing in the teaching about diagnosing and removing automobile’s failure,and then discusses some specific teaching strategies on diagnosing and removing automobile’s failure to provide some effective reference for the related staff.

Infrastructure of Synchrotronic Biosensor Based on Semiconductor Device Fabrication for Tracking, Monitoring, Imaging, Measuring, Diagnosing and Detecting Cancer Cells

Copper Zinc Antimony Sulfide(CZAS)is derived from Copper Antimony Sulfide(CAS),a famatinite class of compound.In the current paper,the first step for using Copper,Zinc,Antimony and Sulfide as materials in manufacturing synchrotronic biosensor-namely increasing the sensitivity of biosensor through creating Copper Zinc Antimony Sulfide,CZAS(Cu1.18Zn0.40Sb1.90S7.2)semiconductor and using it instead of Copper Tin Sulfide,CTS(Cu2SnS3)for tracking,monitoring,imaging,measuring,diagnosing and detecting cancer cells,is evaluated.Further,optimization of tris(2,2'-bipyridyl)ruthenium(II)(Ru(bpy)32+)concentrations and Copper Zinc Antimony Sulfide,CZAS(Cu1.18Zn0.40Sb1.90S7.2)semiconductor as two main and effective materials in the intensity of synchrotron for tracking,monitoring,imaging,measuring,diagnosing and detecting cancer cells are considered so that the highest sensitivity obtains.In this regard,various concentrations of two materials were prepared and photon emission was investigated in the absence of cancer cells.On the other hand,ccancer diagnosis requires the analysis of images and attributes as well as collecting many clinical and mammography variables.In diagnosis of cancer,it is important to determine whether a tumor is benign or malignant.The information about cancer risk prediction along with the type of tumor are crucial for patients and effective medical decision making.An ideal diagnostic system could effectively distinguish between benign and malignant cells;however,such a system has not been created yet.In this study,a model is developed to improve the prediction probability of cancer.It is necessary to have such a prediction model as the survival probability of cancer is high when patients are diagnosed at early stages.