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has been cited by the following article:

• TITLE: Overview of Cancer Management—The Role of Medical Imaging and Machine Learning Techniques in Early Detection of Cancer: Prospects, Challenges, and Future Directions

  AUTHORS: Taofik Ahmed Suleiman, Adetola Mary Tolulope, Funmilola Olanike Wuraola, Rotimi Olorunfemi, Wakeel Adekunle Kasali, Bright Odinaka Okorocha, Christian Dirisu, Prisca Chinonso Njoku

  KEYWORDS: Cancer, Machine Learning, Medical Imaging, Neural Network, Computer-Aided Diagnosis

  JOURNAL NAME: Open Access Library Journal, Vol.10 No.4, April 30, 2023

  ABSTRACT: Globally, the advent of new cases of cancer has been steadily increasing, with rising mortality and a significant impact on the economy. Most malignancy outcomes are linked to early detection, prompt diagnosis, and treatment. The need for early detection is crucial to cancer management. With these increasing numbers, there is a need for the adoption of emerging technologies such as machine learning to help improve the outcome of cancer management. For these reasons, in this paper, we reviewed the role of medical imaging and machine learning techniques in the management of cancer. In general, the technology used in imaging generates enormous data and hence, these data can be analysed using machine learning techniques and the output can be used to predict potential tumour cells resulting in a significant difference in the management of cancer. However, despite these advantages, there are some challenges in using machine learning which has also been discussed in this review, as well as some recommendations and future directions for the successful utilization of machine learning techniques in cancer management.