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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2407.01627 |
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| _version_ | 1866914855592656896 |
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| author | Emdad, Forhan Bin Rahman, Mohammad Ishtiaque |
| author_facet | Emdad, Forhan Bin Rahman, Mohammad Ishtiaque |
| contents | This paper explores the development of the Six Stages of Information Search Model and its enhancement through the application of the Large Language Model (LLM) powered Information Search Processes (ISP) in healthcare. The Six Stages Model, a foundational framework in information science, outlines the sequential phases individuals undergo during information seeking: initiation, selection, exploration, formulation, collection, and presentation. Integrating LLM technology into this model significantly optimizes each stage, particularly in healthcare. LLMs enhance query interpretation, streamline information retrieval from complex medical databases, and provide contextually relevant responses, thereby improving the efficiency and accuracy of medical information searches. This fusion not only aids healthcare professionals in accessing critical data swiftly but also empowers patients with reliable and personalized health information, fostering a more informed and effective healthcare environment. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_01627 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Potential Renovation of Information Search Process with the Power of Large Language Model for Healthcare Emdad, Forhan Bin Rahman, Mohammad Ishtiaque Information Retrieval This paper explores the development of the Six Stages of Information Search Model and its enhancement through the application of the Large Language Model (LLM) powered Information Search Processes (ISP) in healthcare. The Six Stages Model, a foundational framework in information science, outlines the sequential phases individuals undergo during information seeking: initiation, selection, exploration, formulation, collection, and presentation. Integrating LLM technology into this model significantly optimizes each stage, particularly in healthcare. LLMs enhance query interpretation, streamline information retrieval from complex medical databases, and provide contextually relevant responses, thereby improving the efficiency and accuracy of medical information searches. This fusion not only aids healthcare professionals in accessing critical data swiftly but also empowers patients with reliable and personalized health information, fostering a more informed and effective healthcare environment. |
| title | Potential Renovation of Information Search Process with the Power of Large Language Model for Healthcare |
| topic | Information Retrieval |
| url | https://arxiv.org/abs/2407.01627 |