International Journal of Statistics in Medical Research最新文献

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Automatic Diagnosis of Lung Diseases (Pneumonia, Cancer) with given Reliabilities on the Basis of an Irradiation Images of Patients 根据患者的照射图像自动诊断肺部疾病（肺炎、癌症）并给出可靠的诊断结果

International Journal of Statistics in Medical Research Pub Date : 2024-06-10 DOI: 10.6000/1929-6029.2024.13.07

Kartlos Kachiashvili, J. K. Kachiashvili, V.V. Kvaratskhelia

{"title":"Automatic Diagnosis of Lung Diseases (Pneumonia, Cancer) with given Reliabilities on the Basis of an Irradiation Images of Patients","authors":"Kartlos Kachiashvili, J. K. Kachiashvili, V.V. Kvaratskhelia","doi":"10.6000/1929-6029.2024.13.07","DOIUrl":"https://doi.org/10.6000/1929-6029.2024.13.07","url":null,"abstract":"The article proposes algorithms for the automatic diagnosis of human lung diseases pneumonia and cancer, based on images obtained by radiation irradiation, which allow us to make decisions with the necessary reliability, that is, to restrict the probabilities of making possible errors to a pre-planned level. Since the information obtained from the observation is random, Wald’s sequential analysis method and Constrained Bayesian Method (CBM) of statistical hypothesis testing are used for making a decision, which allow us to restrict both types of possible errors. Both methods have been investigated using statistical simulation and real data, which fully confirmed the correctness of theoretical reasoning and the ability to make decisions with the required reliability using artificial intelligence. The advantage of CBM compared to Wald’s method is shown, which is expressed in the relative scarcity of observation results needed to make a decision with the same reliability. The possibility of implementing the proposed method in modern computerized X-ray equipment due to its simplicity and promptness of decision-making is also shown.","PeriodicalId":509590,"journal":{"name":"International Journal of Statistics in Medical Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141362255","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Analysis of Wide Modified Rankin Score Dataset using Markov Chain Monte Carlo Simulation 利用马尔可夫链蒙特卡洛模拟分析广义修正朗肯评分数据集

International Journal of Statistics in Medical Research Pub Date : 2024-01-18 DOI: 10.6000/1929-6029.2024.13.02

Pranjal Kumar Pandey, P. Dev, Akanksha Gupta, Abhishek Pathak, V.K. Shukla, S.K. Upadhyay

引用次数: 0

A Double Truncated Binomial Model to Assess Psychiatric Health through Brief Psychiatric Rating Scale: When is Intervention Useful? 通过简明精神病评定量表评估精神病健康状况的双截二项式模型：干预何时有用？

International Journal of Statistics in Medical Research Pub Date : 2024-01-11 DOI: 10.6000/1929-6029.2024.13.01

A. Sabharwal, B. Goyal, Vinit Singh

{"title":"A Double Truncated Binomial Model to Assess Psychiatric Health through Brief Psychiatric Rating Scale: When is Intervention Useful?","authors":"A. Sabharwal, B. Goyal, Vinit Singh","doi":"10.6000/1929-6029.2024.13.01","DOIUrl":"https://doi.org/10.6000/1929-6029.2024.13.01","url":null,"abstract":"A double truncated binomial distribution model with ‘u’ classes truncated on left and ‘v’ classes truncated on right is introduced. Its characteristics, namely, generating functions; and the measures of skewness and kurtosis have been obtained. The unknown parameter has been estimated using the method of maximum likelihood and the method of moments. The confidence interval of the estimate has been obtained through Fisher’s information matrix. \u0000The model is applied on cross sectional data obtained through Brief Psychiatric Rating Scale (BPRS) administered on a group of school going adolescent students; and the above-mentioned characteristics have been evaluated. An expert, on the basis of the BPRS score values, suggested an intervention program. The BPRS scores of the students who could be administered the intervention program lied in a range (which was above the lowest and below the highest possible values) suggested by the expert. Whereas the complete data suggested the average number of problem areas is four (which was not in consonance with the observations given by the expert), the double truncated model suggested the number of such areas as five which was consistent with the observations made by the expert. This establishes the usefulness of double truncated models in such scenarios.","PeriodicalId":509590,"journal":{"name":"International Journal of Statistics in Medical Research","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139625999","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0