Medical Image Analysis Using Machine Learning Techniques: A Systematic Review
Yazarlar (2)
Mustafa A Al-Asadi
Aalborg Business College, Irak
Aalborg Business College, Irak
Prof. Dr. Şakir TAŞDEMİR Sinop Üniversitesi, Türkiye
| Makale Türü | Özgün Makale (Uluslararası alan indekslerindeki dergilerde yayınlanan tam makale) | ||
| Dergi Adı | Machine Learning and Deep Learning in Efficacy Improvement of Healthcare Systems | ||
| Dergi Tarandığı Indeksler | |||
| Makale Dili | İngilizce | Basım Tarihi | 01-2022 |
| Cilt / Sayı / Sayfa | 0 / 0 / 137–153 | DOI | 10.1201/9781003189053-7/medical-image-analysis-using-machine-learning-techniques-mustafa-al-asadi-sa |
| Makale Linki | https://www.taylorfrancis.com/chapters/edit/10.1201/9781003189053-7/medical-image-analysis-using-machine-learning-techniques-mustafa-al-asadi-sakir-tasdemi%CC%87r | ||
| UAK Araştırma Alanları |
Yapay Zeka
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| Özet |
| Medical images are an essential means of diagnosing a set of diseases and treating patients in modern medicine. The development of imaging technology has allowed getting more detailed medical data. However, the volume of data has increased at the expense of this development, so it has become difficult to analyse medical image data according to human vision. Thus, machine learning has played an essential role in automatic medical images analysis for the past decade. In this chapter, we reviewed the history, principle, and applications of different medical images considered as eyes of modern medicine. Moreover, a systematic review of classic machine learning algorithms was conducted to refer to the main reviewers and authors in the region. As well, we discuss the successes and challenges of each machine learning model and offer some experimental approaches to address these challenges. |
| Anahtar Kelimeler |
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| Google Scholar | 14 |