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Mostly in the dataset, the healthy and cancerous bone images have similar characteristics. Therefore, the development of automated systems is necessary to classify normal and abnormal scan images. The objective of this paper is to identify the studies on classification techniques in detecting bone cancer with five criteria: feature extraction methods, machine learning (ML) and deep learning (DL) techniques, advantages, disadvantages and classifier accuracy. The current study performed the systematic literature review of 129 studies selected based on the use of different feature extractions to extract the textural characteristics of the images that are fed into the ML and DL algorithms to classify the normal and subtypes of bone cancer images for better analysis. The review concludes that convolutional neural network classifier along with different textural feature extraction techniques like gray level co-occurrence matrix (GLCM) and local binary pattern (LBP) detected the bone cancer with high accuracy compared to DL classification without feature extraction techniques in diagnosing the bone cancer. In this respect, this paper proposes a systematic review of types of bone cancer and recent advancements in feature extraction methods and classification involving deep learning and machine learning models to detect bone cancer with a higher accuracy rate.<\/jats:p>","DOI":"10.1088\/2057-1976\/ade8f8","type":"journal-article","created":{"date-parts":[[2025,6,27]],"date-time":"2025-06-27T22:47:20Z","timestamp":1751064440000},"page":"042003","update-policy":"https:\/\/doi.org\/10.1088\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Recent advancements in feature extraction and classification based bone cancer detection \u2013 a systematic review"],"prefix":"10.1088","volume":"11","author":[{"given":"Kanimozhi","family":"S","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8486-7960","authenticated-orcid":true,"given":"Sivakumar","family":"Rajagopal","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ananthakrishna","family":"Chintanpalli","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"266","published-online":{"date-parts":[[2025,7,7]]},"reference":[{"key":"bpexade8f8bib1","doi-asserted-by":"publisher","first-page":"4289","DOI":"10.2147\/IJN.S311001","article-title":"3D printing of micro-and nanoscale bone substitutes: a review on technical and translational perspectives","volume":"16","author":"Cheng","year":"2021","journal-title":"Int. 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