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An Extensive Review on Deep Learning and Machine Learning Intervention in Prediction and Classification of Types of Aneurysms

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Abstract

Aneurysm (Rupture of blood vessels) may happen in the cerebrum, abdominal aorta and thoracic aorta of humans, which has a high fatal rate. The advancement of the artificial technologies specifically machine learning algorithms and deep learning models have attempted to predict the aneurysm, which may reduce the death rate. The main objective of this paper is to provide the review of various algorithms and models for the early prediction of the various types of aneurysms. The focused literature review was conducted from the preferred journals from 2007 to 2022 on various parameters such as way of collecting images, the techniques used, number of images used in data set, performance metrics and future work. The summarized overview of advances in prediction of aneurysms using the machine learning algorithms from non linear kernel support regression algorithm to 3D Unet architecture of deep learning models starting from CT scan images to final performance analysis in prediction. The range of sensitivity, specificity and area under receiving operating characteristic was from 0. 7 to 1 for the abdominal aortic aneurysm detection, intracranial aneurysm detection. The thoracic aortic aneurysm was not concentrated much in the literature review, so the prediction of thoracic aortic aneurysm using machine learning as well as deep learning model is recommended.

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The data used to support the findings of this study are available from the corresponding author upon request.

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Authors and Affiliations

  1. Department of Electronics and Communication Engineering, Kongu Engineering College (Autonomous), Perundurai, Erode, Tamil Nadu, India

    Renugadevi Ammapalayam Sinnaswamy & Suresh Muthusamy

  2. Department of Computer Science and Engineering, Kongu Engineering College (Autonomous), Perundurai, Erode, Tamil Nadu, India

    Natesan Palanisamy & Kavitha Subramaniam

  3. Department of Electrical Engineering, Malaviya National Institute of Technology Jaipur, Jaipur, Rajasthan, India

    Ravita Lamba

  4. Department of Electrical Engineering, National Institute of Technology Silchar, Assam, India

    Sreejith Sekaran

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  1. Renugadevi Ammapalayam Sinnaswamy
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  4. Suresh Muthusamy
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RAS, NP—drafting the manuscript, KS—Supervision, SM, RL—Assisting in drafting the manuscript, SS—project administration.

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Correspondence to Suresh Muthusamy.

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Sinnaswamy, R.A., Palanisamy, N., Subramaniam, K. et al. An Extensive Review on Deep Learning and Machine Learning Intervention in Prediction and Classification of Types of Aneurysms. Wireless Pers Commun 131, 2055–2080 (2023). https://doi.org/10.1007/s11277-023-10532-y

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