Natural Language Processing Techniques and FAIR Principles for Assisting Drug Prescription
Prescribing medicines for certain illnesses as correctly as possible is a challenge for all doctors and healthcare providers worldwide, and a big problem for the inexperienced ones. In this age of technology, we are confronted with a great deal of medical information from different sources. For phys...
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| Format: | Article |
| Language: | English |
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Iuliu Hatieganu University of Medicine and Pharmacy, Cluj-Napoca
2023-09-01
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| Series: | Applied Medical Informatics |
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| Online Access: | https://ami.info.umfcluj.ro/index.php/AMI/article/view/967 |
| _version_ | 1797669486346633216 |
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| author | Oana Sorina CHIRILĂ Lăcrămioara STOICU-TIVADAR |
| author_facet | Oana Sorina CHIRILĂ Lăcrămioara STOICU-TIVADAR |
| author_sort | Oana Sorina CHIRILĂ |
| collection | DOAJ |
| description | Prescribing medicines for certain illnesses as correctly as possible is a challenge for all doctors and healthcare providers worldwide, and a big problem for the inexperienced ones. In this age of technology, we are confronted with a great deal of medical information from different sources. For physicians to have access to this ocean of information, structuring and compaction is needed. Many papers in the scientific literature propose the structuring and use of medical information from clinical texts or other sources. We want to develop a medical information system that extracts specific drug information from Romanian pill leaflets. We intend to create a structured database and raise the interoperability degree for the system to communicate with other medical applications. First, we collect as much information as possible about Romanian drugs from different free online sources, from the leaflets of medicines in Romanian from ANMDMR - Nomenclature of medicines for human use and from scientific publications. We clean and structure the collected data by using machine learning techniques, especially natural language processing techniques. Next, we create ontologies and a complex database with the drug information’s and relationships between the information extracted about drugs (indications, contraindications, dosage according to age, side effects, etc.), and finally, we develop an application respecting the FAIR (Findability, Accessibility, Interoperability, and Reusability) principles that have as inputs the profile of a patient, and as outputs the drugs indicated for certain diseases, an explainable module for the drugs selected for physicians and an adverse drug reaction adding module. From the clinical perspective, this application will help improve the quality of prescriptions and provide a better knowledge database that can help physicians avoid prescription errors. |
| first_indexed | 2024-03-11T20:45:05Z |
| format | Article |
| id | doaj.art-178655b3b5d1448e82f3b49c3d674304 |
| institution | Directory Open Access Journal |
| issn | 2067-7855 |
| language | English |
| last_indexed | 2024-03-11T20:45:05Z |
| publishDate | 2023-09-01 |
| publisher | Iuliu Hatieganu University of Medicine and Pharmacy, Cluj-Napoca |
| record_format | Article |
| series | Applied Medical Informatics |
| spelling | doaj.art-178655b3b5d1448e82f3b49c3d6743042023-10-01T11:36:36ZengIuliu Hatieganu University of Medicine and Pharmacy, Cluj-NapocaApplied Medical Informatics2067-78552023-09-0145Suppl. S1S17S171074Natural Language Processing Techniques and FAIR Principles for Assisting Drug PrescriptionOana Sorina CHIRILĂ0Lăcrămioara STOICU-TIVADAR1Faculty of Automation and Computers, University Politehnica Timişoara, Vasile Parvan Blvd., no. 2, 300223 Timişoara, RomaniaFaculty of Automation and Computers, University Politehnica Timişoara, Vasile Parvan Blvd., no. 2, 300223 Timişoara, RomaniaPrescribing medicines for certain illnesses as correctly as possible is a challenge for all doctors and healthcare providers worldwide, and a big problem for the inexperienced ones. In this age of technology, we are confronted with a great deal of medical information from different sources. For physicians to have access to this ocean of information, structuring and compaction is needed. Many papers in the scientific literature propose the structuring and use of medical information from clinical texts or other sources. We want to develop a medical information system that extracts specific drug information from Romanian pill leaflets. We intend to create a structured database and raise the interoperability degree for the system to communicate with other medical applications. First, we collect as much information as possible about Romanian drugs from different free online sources, from the leaflets of medicines in Romanian from ANMDMR - Nomenclature of medicines for human use and from scientific publications. We clean and structure the collected data by using machine learning techniques, especially natural language processing techniques. Next, we create ontologies and a complex database with the drug information’s and relationships between the information extracted about drugs (indications, contraindications, dosage according to age, side effects, etc.), and finally, we develop an application respecting the FAIR (Findability, Accessibility, Interoperability, and Reusability) principles that have as inputs the profile of a patient, and as outputs the drugs indicated for certain diseases, an explainable module for the drugs selected for physicians and an adverse drug reaction adding module. From the clinical perspective, this application will help improve the quality of prescriptions and provide a better knowledge database that can help physicians avoid prescription errors.https://ami.info.umfcluj.ro/index.php/AMI/article/view/967prescriptionsnatural language processing (nlp)machine learningleaflets |
| spellingShingle | Oana Sorina CHIRILĂ Lăcrămioara STOICU-TIVADAR Natural Language Processing Techniques and FAIR Principles for Assisting Drug Prescription Applied Medical Informatics prescriptions natural language processing (nlp) machine learning leaflets |
| title | Natural Language Processing Techniques and FAIR Principles for Assisting Drug Prescription |
| title_full | Natural Language Processing Techniques and FAIR Principles for Assisting Drug Prescription |
| title_fullStr | Natural Language Processing Techniques and FAIR Principles for Assisting Drug Prescription |
| title_full_unstemmed | Natural Language Processing Techniques and FAIR Principles for Assisting Drug Prescription |
| title_short | Natural Language Processing Techniques and FAIR Principles for Assisting Drug Prescription |
| title_sort | natural language processing techniques and fair principles for assisting drug prescription |
| topic | prescriptions natural language processing (nlp) machine learning leaflets |
| url | https://ami.info.umfcluj.ro/index.php/AMI/article/view/967 |
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