HUMAN DISEASE DETECTION USING ARTIFICIAL INTELLIGENCE
Yazarlar (8)
Vanita Jain
Bhawanand Jha
Sourav Joshi
Sourabh Miglani
Aman Singal
Shubham Babbar
Dr. Öğr. Üyesi Merve DEMİRCİ Kafkas Üniversitesi, Türkiye
Prof. Dr. Müslüm Cengiz Taplamacıoğlu Gazi Üniversitesi, Türkiye
| Makale Türü | Özgün Makale (SCOPUS dergilerinde yayınlanan tam makale) | ||
| Dergi Adı | International Journal on Technical and Physical Problems of Engineering | ||
| Dergi ISSN | 2077-3528 Dergi Bilgileri (2023) | ||
| Dergi Tarandığı Indeksler | Scopus | ||
| Makale Dili | İngilizce | Basım Tarihi | 06-2023 |
| Cilt / Sayı / Sayfa | 15 / 2 / 125–133 | DOI | – |
| Makale Linki | https://www.scopus.com/record/display.uri?eid=2-s2.0-85164024133&origin=resultslist&sort=plf-f&src=s&sid=4cfce998edcdafb77dc6744c587ac98a&sot=a&sdt=a&s=SOURCE-ID+%2821100913338%29&sl=23&sessionSearchId=4cfce998edcd | ||
| UAK Araştırma Alanları |
Elektrik Tesisleri
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| Özet |
| In twentieth century machine learning is being used in various fields; one of the most popular fields among them is the Medical. Few years ago, all the diseases were diagnosed by doctors through expensive machines like X-ray machines, MRI machines and others. Over the last decade disease detection through Machine learning has become quite popular. In this research work, the authors have diagnosed four human diseases viz. Pneumonia, Heart Disease, Breast Cancer and Thyroid. Seven Machine Learning and Deep Learning Algorithms have been used. The accuracies of all Machine Learning models have been compared on different splitting ratio of dataset in order to find the maximum accuracy. The maximum accuracy for heart disease and thyroid by Random Forest is 98.05% and 97.9% respectively. The best result for Breast Cancer by Neural Network is 98.2%. A Hybrid model which consists of … |
| Anahtar Kelimeler |
