Applications of knowledge graph generation via keyword search for medical data

Artificial intelligence (AI) is making big changes in many areas, including medicine. More people are using online medical websites for health advice, which can be both good and bad. While these online tools give quick access to a lot of health information, there can be problems like wrong self-diag...

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Bibliografski detalji
Glavni autor: Abdul Hakiim Bin Jalil
Daljnji autori: Miao Chun Yan
Format: Final Year Project (FYP)
Jezik:English
Izdano: Nanyang Technological University 2023
Teme:
Online pristup:https://hdl.handle.net/10356/172622
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author Abdul Hakiim Bin Jalil
author2 Miao Chun Yan
author_facet Miao Chun Yan
Abdul Hakiim Bin Jalil
author_sort Abdul Hakiim Bin Jalil
collection NTU
description Artificial intelligence (AI) is making big changes in many areas, including medicine. More people are using online medical websites for health advice, which can be both good and bad. While these online tools give quick access to a lot of health information, there can be problems like wrong self-diagnoses. This report talks about using Knowledge Graphs (KG) to help solve some of these problems. KGs are like visual maps that show how different pieces of data connect, and they can make understanding complex topics, like diseases, easier. Our main goal was to make a KG for 'Diabetes'. We used OpenAI’s tools and checked our data with trusted medical websites. This report will explain how we made the system, what it looks like, and what we learned from it.
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spelling ntu-10356/1726222023-12-22T15:38:08Z Applications of knowledge graph generation via keyword search for medical data Abdul Hakiim Bin Jalil Miao Chun Yan School of Computer Science and Engineering ASCYMiao@ntu.edu.sg Engineering::Computer science and engineering Artificial intelligence (AI) is making big changes in many areas, including medicine. More people are using online medical websites for health advice, which can be both good and bad. While these online tools give quick access to a lot of health information, there can be problems like wrong self-diagnoses. This report talks about using Knowledge Graphs (KG) to help solve some of these problems. KGs are like visual maps that show how different pieces of data connect, and they can make understanding complex topics, like diseases, easier. Our main goal was to make a KG for 'Diabetes'. We used OpenAI’s tools and checked our data with trusted medical websites. This report will explain how we made the system, what it looks like, and what we learned from it. Bachelor of Engineering (Computer Engineering) 2023-12-18T03:05:54Z 2023-12-18T03:05:54Z 2023 Final Year Project (FYP) Abdul Hakiim Bin Jalil (2023). Applications of knowledge graph generation via keyword search for medical data. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/172622 https://hdl.handle.net/10356/172622 en SCSE22-1121 application/pdf Nanyang Technological University
spellingShingle Engineering::Computer science and engineering
Abdul Hakiim Bin Jalil
Applications of knowledge graph generation via keyword search for medical data
title Applications of knowledge graph generation via keyword search for medical data
title_full Applications of knowledge graph generation via keyword search for medical data
title_fullStr Applications of knowledge graph generation via keyword search for medical data
title_full_unstemmed Applications of knowledge graph generation via keyword search for medical data
title_short Applications of knowledge graph generation via keyword search for medical data
title_sort applications of knowledge graph generation via keyword search for medical data
topic Engineering::Computer science and engineering
url https://hdl.handle.net/10356/172622
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