Special Disease Prediction System Using Machine Learning

Abstract: The wide variety of computer-based technologies within the healthcare industry has led to the gathering of electronic data. Due to the massive number of information, medical professionals are faced with the challenge of accurately diagnosing signs and figuring out diseases at an early stage. In medicine, misdiagnosis could be a major factor leading because of poor treatment and diagnosing the disease when it’s serious. However, supervised machine learning techniques have demonstrated the potential to surpass conventional diagnostic procedures and assist medical professionals in diagnosing highrisk diseases. Mostly people feel lazy to visit a hospital, and concern a doctor for a minor complication. However, this small problem can pose significant medical risk. Since, online medical advice is readily available. The system evaluates the symptoms that person give as an input and gives the disease as an output. Naive Bayes Classifier is used in the system. Our system focuses on accuracy, the more numbers of a symptoms furnished by the person as a input the disorder prediction as a output will be better. Work can enhance the health care industry to zenith and give cure to world

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Publication Details

Journal
International Journal for Research in Applied Science and Engineering Technology
Published
2025-04-21
DOI
https://doi.org/10.22214/ijraset.2025.69110
Primary Topic
Artificial Intelligence in Healthcare
Type
article
Field-Weighted Citation Impact
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article

Special Disease Prediction System Using Machine Learning

M Mitha, P Dharshini
International Journal for Research in Applied Science and Engineering Technology
Artificial Intelligence in Healthcare
article

Special Disease Prediction System Using Machine Learning

M Mitha, P Dharshini
article en

Abstract

Abstract: The wide variety of computer-based technologies within the healthcare industry has led to the gathering of electronic data. Due to the massive number of information, medical professionals are faced with the challenge of accurately diagnosing signs and figuring out diseases at an early stage. In medicine, misdiagnosis could be a major factor leading because of poor treatment and diagnosing the disease when it’s serious. However, supervised machine learning techniques have demonstrated the potential to surpass conventional diagnostic procedures and assist medical professionals in diagnosing highrisk diseases. Mostly people feel lazy to visit a hospital, and concern a doctor for a minor complication. However, this small problem can pose significant medical risk. Since, online medical advice is readily available. The system evaluates the symptoms that person give as an input and gives the disease as an output. Naive Bayes Classifier is used in the system. Our system focuses on accuracy, the more numbers of a symptoms furnished by the person as a input the disorder prediction as a output will be better. Work can enhance the health care industry to zenith and give cure to world

International Journal for Research in Applied Science and Engineering TechnologyVol. 13(4)
Kalasalingam Academy of Research and Education (IN)
Openalex Percentile: Top 91%
Artificial Intelligence in Healthcare
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