Techniques of deep learning for diagnosing brain diseases: A review
1 Department of Computer Science, Institute of Engineering & Technology, Dr. Bhimrao Ambedkar University, Khandari, Agra, India.
2 Department of BCA, St. John’s College, Agra, India.
Review
World Journal of Advanced Engineering Technology and Sciences, 2022, 06(02), 001–025.
Article DOI: 10.30574/wjaets.2022.6.2.0072
Publication history:
Received on 16 May 2022; revised on 26 June 2022; accepted on 28 June 2022
Abstract:
Deep learning has been proved as a tremendous evolution in machine learning and computer vision. Through deep learning, computer machines become capable of solving the problems those were beyond the imagination two decades prior. Nowadays, Deep learning is significantly used in Natural language processing, image classification, medical science, handwriting recognition, face recognition, speech recognition, biometrics matching and in various real life problem domains. In this present paper, a review of deep learning techniques is presented for the diagnoses of brain diseases. Today, Deep learning is playing a crucial role in automating the medical equipment for the diagnosis of various brain diseases like tumor, Alzheimer, Mild Cognitive Impairment, brain hemorrhage, Parkinson etc. Deep learning has been tremendously used in detecting the severity of such diseases. This paper covers the recent approaches, techniques, learning algorithms of deep learning those have been used to detect major or minor diseases in a human brain. The paper also explores the future possibilities for Deep learning in medical science specifically for the brain diseases.
Keywords:
Computer Vision; Deep Learning; Convolution Neural Network; Recurrent Neural Network; Brain Diseases;
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