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Session Ⅱ: Medical AI

Comparative Analysis for Chronic Disease Prediction via Deep Machine Learning Approaches

첫 페이지 보기
  • 발행기관
    한국차세대컴퓨팅학회 바로가기
  • 간행물
    한국차세대컴퓨팅학회 학술대회 바로가기
  • 통권
    The 9th International Conference on Next Generation Computing 2023 (2023.12)바로가기
  • 페이지
    pp.81-84
  • 저자
    Rabia Javed, Tahir Abbas, Jamshaid Iqbal Janjua, Sadaqat Ali Ramay, M. Kashan Basit, Muhammad Irfan
  • 언어
    영어(ENG)
  • URL
    https://www.earticle.net/Article/A448123

원문정보

초록

영어
Globally, chronic diseases have a significant impact on health. The diagnosis of chronic diseases has seen extensive usage of machine learning techniques. Early disease detection and treatment lower the risk of increasing disease severity and, consequently, related mortality. The major goal of this research is to provide a technique that increases classification accuracy while also shortening computing time. This comparative research shows the impact of distinct model architectures and features on disease prediction accuracy in addition to assessing the advantages and disadvantages of each technique. These discoveries have implications for personalized healthcare, allowing medical professionals to select the best models for various chronic conditions. Additionally, this research can direct the creation of better forecasting technologies, as well as influence healthcare legislation and budget allocation. In our study comparative analysis of the state-of-the-art approaches has been presented. Using a hybrid model combination of CNN and RNN could be more beneficial. In conclusion, our comparison research improves our comprehension of the potential of deep machine learning for chronic disease prediction, highlighting the significance of adjusting model selection to certain disease types. To progress the field of chronic disease prediction, future research should concentrate on improving these models, and further explore their applicability across various and larger datasets.

목차

Abstract
I. INTRODUCTION
II. RELATED WORK
III. METHODOLOGY
IV. CONCLUSION
REFERENCES

키워드

Chronic Disease Machine Learning Deep Learning Cardiovascular Disease Chronic Kidney Disease Diabetes Hepatitis Cancer Healthcare

저자

  • Rabia Javed [ Department of Computer Science TIMES Institute Multan, Pakistan ]
  • Tahir Abbas [ Department of Computer Science TIMES Institute Multan, Pakistan ]
  • Jamshaid Iqbal Janjua [ Al-Khwarizmi Institute of Computer Science (KICS), University of Engineering & Technology & NCBA&E Lahore, Pakistan ]
  • Sadaqat Ali Ramay [ Department of Computer Science TIMES Institute Multan, Pakistan ]
  • M. Kashan Basit [ Department of Computer Science MNS-UET Multan, Pakistan ]
  • Muhammad Irfan [ Department of Computer Science TIMES Institute Multan, Pakistan ]

참고문헌

자료제공 : 네이버학술정보

간행물 정보

발행기관

  • 발행기관명
    한국차세대컴퓨팅학회 [Korean Institute of Next Generation Computing]
  • 설립연도
    2005
  • 분야
    공학>컴퓨터학
  • 소개
    본 학회는 차세대 PC 및 그 관련분야의 학술활동을 통하여 차세대 PC의 학문 및 기술발전을 도모하고 산업발전 및 국제협력 증진을 목적으로 한다.

간행물

  • 간행물명
    한국차세대컴퓨팅학회 학술대회
  • 간기
    반년간
  • 수록기간
    2021~2025
  • 십진분류
    KDC 566 DDC 004

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