Use of improved memory type control charts for monitoring cancer patients recovery time censored data
Abstract Control charts are a statistical approach for monitoring cancer data that can assist discover patterns, trends, and unusual deviations in cancer-related data across time. To detect deviations from predicted patterns, control charts are extensively used in quality control and process managem...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2024-03-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-024-55731-0 |
| _version_ | 1797266754279309312 |
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| author | Syed Muhammad Muslim Raza Maqbool Hussain Sial Najam ul Hassan Getachew Tekle Mekiso Yusra A. Tashkandy M. E. Bakr Anoop Kumar |
| author_facet | Syed Muhammad Muslim Raza Maqbool Hussain Sial Najam ul Hassan Getachew Tekle Mekiso Yusra A. Tashkandy M. E. Bakr Anoop Kumar |
| author_sort | Syed Muhammad Muslim Raza |
| collection | DOAJ |
| description | Abstract Control charts are a statistical approach for monitoring cancer data that can assist discover patterns, trends, and unusual deviations in cancer-related data across time. To detect deviations from predicted patterns, control charts are extensively used in quality control and process management. Control charts may be used to track numerous parameters in cancer data, such as incidence rates, death rates, survival time, recovery time, and other related indicators. In this study, CDEC chart is proposed to monitor the cancer patients recovery time censored data. This paper presents a composite dual exponentially weighted moving average Cumulative sum (CDEC) control chart for monitoring cancer patients recovery time censored data. This approach seeks to detect changes in the mean recovery time of cancer patients which usually follows Weibull lifetimes. The results are calculated using type I censored data under known and estimated parameter conditions. We combine the conditional expected value (CEV) and conditional median (CM) approaches, which are extensively used in statistical analysis to determine the central tendency of a dataset, to create an efficient control chart. The suggested chart's performance is assessed using the average run length (ARL), which evaluates how efficiently the chart can detect a change in the process mean. The CDEC chart is compared to existing control charts. A simulation study and a real-world data set related to cancer patients recovery time censored data is used for results illustration. The proposed CDEC control chart is developed for the data monitoring when complete information about the patients are not available. So, instead of doping the patients information we can used the proposed chart to monitor the patients information even if it is censored. The authors conclude that the suggested CDEC chart is more efficient than competitor control charts for monitoring cancer patients recovery time censored data. Overall, this study introduces an efficient new approach for cancer patients recovery time censored data, which might have significant effect on quality control and process improvement across a wide range of healthcare and medical studies. |
| first_indexed | 2024-04-25T01:05:43Z |
| format | Article |
| id | doaj.art-2fa55378056e4d7aba78a8e7d8e50911 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-04-25T01:05:43Z |
| publishDate | 2024-03-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-2fa55378056e4d7aba78a8e7d8e509112024-03-10T12:12:24ZengNature PortfolioScientific Reports2045-23222024-03-0114111510.1038/s41598-024-55731-0Use of improved memory type control charts for monitoring cancer patients recovery time censored dataSyed Muhammad Muslim Raza0Maqbool Hussain Sial1Najam ul Hassan2Getachew Tekle Mekiso3Yusra A. Tashkandy4M. E. Bakr5Anoop Kumar6Department of Economics and Statistics, Dr Hasan Murad School of Management, University of Management and TechnologyDepartment of Economics and Statistics, Dr Hasan Murad School of Management, University of Management and TechnologyDepartment of Economics, Thal UniversityDepartment of Statistics, Wachemo UniversityDepartment of Statistics and Operations Research, College of Science, King Saud UniversityDepartment of Statistics and Operations Research, College of Science, King Saud UniversityDepartment of Statistics, Faculty of Applied Sciences, Amity University Uttar PradeshAbstract Control charts are a statistical approach for monitoring cancer data that can assist discover patterns, trends, and unusual deviations in cancer-related data across time. To detect deviations from predicted patterns, control charts are extensively used in quality control and process management. Control charts may be used to track numerous parameters in cancer data, such as incidence rates, death rates, survival time, recovery time, and other related indicators. In this study, CDEC chart is proposed to monitor the cancer patients recovery time censored data. This paper presents a composite dual exponentially weighted moving average Cumulative sum (CDEC) control chart for monitoring cancer patients recovery time censored data. This approach seeks to detect changes in the mean recovery time of cancer patients which usually follows Weibull lifetimes. The results are calculated using type I censored data under known and estimated parameter conditions. We combine the conditional expected value (CEV) and conditional median (CM) approaches, which are extensively used in statistical analysis to determine the central tendency of a dataset, to create an efficient control chart. The suggested chart's performance is assessed using the average run length (ARL), which evaluates how efficiently the chart can detect a change in the process mean. The CDEC chart is compared to existing control charts. A simulation study and a real-world data set related to cancer patients recovery time censored data is used for results illustration. The proposed CDEC control chart is developed for the data monitoring when complete information about the patients are not available. So, instead of doping the patients information we can used the proposed chart to monitor the patients information even if it is censored. The authors conclude that the suggested CDEC chart is more efficient than competitor control charts for monitoring cancer patients recovery time censored data. Overall, this study introduces an efficient new approach for cancer patients recovery time censored data, which might have significant effect on quality control and process improvement across a wide range of healthcare and medical studies.https://doi.org/10.1038/s41598-024-55731-0CDECAverage run length (ARL)Cumulative sumControl chartsConditional expected valuesConditional median |
| spellingShingle | Syed Muhammad Muslim Raza Maqbool Hussain Sial Najam ul Hassan Getachew Tekle Mekiso Yusra A. Tashkandy M. E. Bakr Anoop Kumar Use of improved memory type control charts for monitoring cancer patients recovery time censored data Scientific Reports CDEC Average run length (ARL) Cumulative sum Control charts Conditional expected values Conditional median |
| title | Use of improved memory type control charts for monitoring cancer patients recovery time censored data |
| title_full | Use of improved memory type control charts for monitoring cancer patients recovery time censored data |
| title_fullStr | Use of improved memory type control charts for monitoring cancer patients recovery time censored data |
| title_full_unstemmed | Use of improved memory type control charts for monitoring cancer patients recovery time censored data |
| title_short | Use of improved memory type control charts for monitoring cancer patients recovery time censored data |
| title_sort | use of improved memory type control charts for monitoring cancer patients recovery time censored data |
| topic | CDEC Average run length (ARL) Cumulative sum Control charts Conditional expected values Conditional median |
| url | https://doi.org/10.1038/s41598-024-55731-0 |
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