We, the Publisher, have retracted the following article: Wenhao Tang et al. (2023). Review of AlexNet for Medical Image Classification. https://doi.org/10.4108/eetel.4389 The article has been retracted due to misconduct during the peer review process. This does not implicate any wrongdoing from the author’s side. We informed the authors about this decision. The retracted article will remain, and it has been watermarked as “RETRACTED”.
We, the Publisher, have retracted the following article: Jiayao Hu (2023). Microlearning helps Alzheimer’s Disease Patients. https://doi.org/10.4108/eetel.4321 The article has been retracted due to misconduct during the peer review process. This does not implicate any wrongdoing from the author’s side. We informed the authors about this decision. The retracted article will remain, and it has been watermarked as “RETRACTED”.
We, the Publisher, have retracted the following article: Haroon Altarawneh (2023). ChatGpt impact on Student Educational Performance: a conceptual analysis. https://doi.org/10.4108/eetel.4574 The article has been retracted due to misconduct during the peer review process. This does not implicate any wrongdoing from the author’s side. We informed the authors about this decision. The retracted article will remain, and it has been watermarked as “RETRACTED”.
We, the Publisher, have retracted the following article: S Suman Rajest et al. (2023). The Analysis of How Artificial Intelligence Has an Effect on Teachers and The Education System. https://doi.org/10.4108/eetel.3494 The article has been retracted due to misconduct during the peer review process. This does not implicate any wrongdoing from the author’s side. We informed the authors about this decision. The retracted article will remain, and it has been watermarked as “RETRACTED”. The author disagrees with this retraction.
A brain tumor is a serious neurological condition caused by the growth of abnormal cells in various regions of the brain, leading to a variety of health issues. Although the specific causes of brain tumors are not yet fully understood, known risk factors include genetic predisposition, ionizing radiation, viral infections, and exposure to certain chemicals. With the advancement of deep learning technology, computer-aided diagnosis systems can offer crucial support for the early diagnosis of brain tumors. Brain tumor image classification using deep learning has emerged as a prominent area of research. This article begins by summarizing the publicly available datasets frequently utilized in brain tumor classification tasks. It then provides an overview of the models commonly applied for diagnosing brain tumors. Following this, the paper reviews the advancements made in the field of brain tumor classification research to date. Finally, it highlights the future trends and challenges in brain tumor classification.
