Razy: A String Matching Algorithm for Automatic Analysis of Pathological Reports
Pathology reports are necessary for specialists to make an appropriate diagnosis of diseases in general and blood diseases in particular. Therefore, specialists check blood cells and other blood details. Thus, to diagnose a disease, specialists must analyze the factors of the patient’s blood and med...
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MDPI AG
2022-10-01
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| Series: | Axioms |
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| Online Access: | https://www.mdpi.com/2075-1680/11/10/547 |
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| author | Safa S. Abdul-Jabbar Alaa K. Farhan Abdelaziz A. Abdelhamid Mohamed E. Ghoneim |
| author_facet | Safa S. Abdul-Jabbar Alaa K. Farhan Abdelaziz A. Abdelhamid Mohamed E. Ghoneim |
| author_sort | Safa S. Abdul-Jabbar |
| collection | DOAJ |
| description | Pathology reports are necessary for specialists to make an appropriate diagnosis of diseases in general and blood diseases in particular. Therefore, specialists check blood cells and other blood details. Thus, to diagnose a disease, specialists must analyze the factors of the patient’s blood and medical history. Generally, doctors have tended to use intelligent agents to help them with CBC analysis. However, these agents need analytical tools to extract the parameters (CBC parameters) employed in the prediction of the development of life-threatening bacteremia and offer prognostic data. Therefore, this paper proposes an enhancement to the Rabin–Karp algorithm and then mixes it with the fuzzy ratio to make this algorithm suitable for working with CBC test data. The selection of these algorithms was performed after evaluating the utility of various string matching algorithms in order to choose the best ones to establish an accurate text collection tool to be a baseline for building a general report on patient information. The proposed method includes several basic steps: Firstly, the CBC-driven parameters are extracted using an efficient method for retrieving data information from pdf files or images of the CBC tests. This will be performed by implementing 12 traditional string matching algorithms, then finding the most effective ways based on the implementation results, and, subsequently, introducing a hybrid approach to address the shortcomings or issues in those methods to discover a more effective and faster algorithm to perform the analysis of the pathological tests. The proposed algorithm (Razy) was implemented using the Rabin algorithm and the fuzzy ratio method. The results show that the proposed algorithm is fast and efficient, with an average accuracy of 99.94% when retrieving the results. Moreover, we can conclude that the string matching algorithm is a crucial tool in the report analysis process that directly affects the efficiency of the analytical system. |
| first_indexed | 2024-03-09T20:43:04Z |
| format | Article |
| id | doaj.art-bc0aba262ef84c6e842335fe9de71136 |
| institution | Directory Open Access Journal |
| issn | 2075-1680 |
| language | English |
| last_indexed | 2024-03-09T20:43:04Z |
| publishDate | 2022-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Axioms |
| spelling | doaj.art-bc0aba262ef84c6e842335fe9de711362023-11-23T22:54:07ZengMDPI AGAxioms2075-16802022-10-01111054710.3390/axioms11100547Razy: A String Matching Algorithm for Automatic Analysis of Pathological ReportsSafa S. Abdul-Jabbar0Alaa K. Farhan1Abdelaziz A. Abdelhamid2Mohamed E. Ghoneim3Computer Science Department, College of Science for Women, University of Baghdad, Baghdad 10011, IraqComputer Science Department, University of Technology, Baghdad 10030, IraqDepartment of Computer Science, Faculty of Computer and Information Sciences, Ain Shams University, Cairo 11566, EgyptDepartment of Mathematical Sciences, Faculty of Applied Science, Umm Al-Qura University, Makkah 21955, Saudi ArabiaPathology reports are necessary for specialists to make an appropriate diagnosis of diseases in general and blood diseases in particular. Therefore, specialists check blood cells and other blood details. Thus, to diagnose a disease, specialists must analyze the factors of the patient’s blood and medical history. Generally, doctors have tended to use intelligent agents to help them with CBC analysis. However, these agents need analytical tools to extract the parameters (CBC parameters) employed in the prediction of the development of life-threatening bacteremia and offer prognostic data. Therefore, this paper proposes an enhancement to the Rabin–Karp algorithm and then mixes it with the fuzzy ratio to make this algorithm suitable for working with CBC test data. The selection of these algorithms was performed after evaluating the utility of various string matching algorithms in order to choose the best ones to establish an accurate text collection tool to be a baseline for building a general report on patient information. The proposed method includes several basic steps: Firstly, the CBC-driven parameters are extracted using an efficient method for retrieving data information from pdf files or images of the CBC tests. This will be performed by implementing 12 traditional string matching algorithms, then finding the most effective ways based on the implementation results, and, subsequently, introducing a hybrid approach to address the shortcomings or issues in those methods to discover a more effective and faster algorithm to perform the analysis of the pathological tests. The proposed algorithm (Razy) was implemented using the Rabin algorithm and the fuzzy ratio method. The results show that the proposed algorithm is fast and efficient, with an average accuracy of 99.94% when retrieving the results. Moreover, we can conclude that the string matching algorithm is a crucial tool in the report analysis process that directly affects the efficiency of the analytical system.https://www.mdpi.com/2075-1680/11/10/547pathological analysisCBC testsCBC analysisstring matching algorithmspathological analysis |
| spellingShingle | Safa S. Abdul-Jabbar Alaa K. Farhan Abdelaziz A. Abdelhamid Mohamed E. Ghoneim Razy: A String Matching Algorithm for Automatic Analysis of Pathological Reports Axioms pathological analysis CBC tests CBC analysis string matching algorithms pathological analysis |
| title | Razy: A String Matching Algorithm for Automatic Analysis of Pathological Reports |
| title_full | Razy: A String Matching Algorithm for Automatic Analysis of Pathological Reports |
| title_fullStr | Razy: A String Matching Algorithm for Automatic Analysis of Pathological Reports |
| title_full_unstemmed | Razy: A String Matching Algorithm for Automatic Analysis of Pathological Reports |
| title_short | Razy: A String Matching Algorithm for Automatic Analysis of Pathological Reports |
| title_sort | razy a string matching algorithm for automatic analysis of pathological reports |
| topic | pathological analysis CBC tests CBC analysis string matching algorithms pathological analysis |
| url | https://www.mdpi.com/2075-1680/11/10/547 |
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