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All Journal Dinasti Health and Pharmacy Science
Aa Hubur
International Open University, Gambia
Health Professions

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Automated Cancer Detection and Classification Arsya Sinatria Artha; Andino Maseleno; Aa Hubur
Dinasti Health and Pharmacy Science Vol. 2 No. 2 (2024): Dinasti Health and Pharmacy Science (October 2024)
Publisher : Dinasti Research & Yayasan Dharma Indonesia Tercinta (DINASTI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38035/dhps.v2i2.1811

Abstract

Detection of cancer is very difficult and need more concern in the field of medical. This paper studies the various causes, types, symptoms of cancer. The main objective of this paper is to design an efficient and effective approach to detect the cancer using image processing. The research proposed an improved hybrid approach for detection and segmentation. The research work includes improvement of microscopic image, then segmentation of cells, extract the features of cancer and then at the final stage it described the classification step. After using different approaches and review several previous approaches this technique used an efficient and appropriate method to design a proposed framework.
Diseases Diagnosis using Machine Learning Arsya Sinatria Artha; Andino Maseleno; Aa Hubur
Dinasti Health and Pharmacy Science Vol. 2 No. 3 (2025): Dinasti Health and Pharmacy Science (January 2025)
Publisher : Dinasti Research & Yayasan Dharma Indonesia Tercinta (DINASTI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38035/dhps.v2i3.1812

Abstract

Method that is use to optimize the criterion efficiency that depend on the previous experience is known as machine learning. By using the statistics theory it creates the mathematical model, and its major work is to surmise from the examples gave. To take the data straightforwardly from the information the approach uses computational methods. For recognize and identify the disease correctly a pattern is very necessary in Diagnosis recognition of disease. for creating the different models machine learning is used, this model can use for prediction of output and this output is depend on the input that is related to the data which previously used. For curing any disease it is very important to identify and detect that disease. For classify the disease classification algorithms are used. It uses are many dimensionality reduction algorithms and classification algorithms. Without externally modified the computer can learn with the help of the machine learning. For taking the best fit from the observation set the hypothesis is selected. Multi dimensional and high dimensional are used in machine learning. By using machine learning automatic and classy algorithms can build.
Co-Authors Andino Maseleno Arsya Sinatria Artha