Diagnosis of Brain Tumor Using Light Weight Deep Learning Model with Fine-Tuning Approach

Shelatkar, Tejas; Garg, Urvashi; Shorfuzzaman, Mohammad; Alsufyani, Abdulmajeed; Lakshmanna, Kuruva

doi:10.1155/2022/2858845

Cited by 41 publications

(24 citation statements)

References 36 publications

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“…e study in [29,30] used a DBN model to understand schizophrenia pathology wherein a DBN based deep learning model was used to extract features from brain morphometry data. is helps to investigate its performance discriminating healthy controls from patients suffering from schizophrenia.…”

Section: Exploration Of Educational Reform Taking Online Teaching As ...mentioning

confidence: 99%

The Reform of University Education Teaching Based on Cloud Computing and Big Data Background

Liu

2022

Computational Intelligence and Neuroscience

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In the era of big data and cloud computing, traditional college teaching model needs to be revolutionized in order to adapt to the needs of the present generation. The traditional college teaching model is currently facing unprecedented severe challenges which could be optimistically considered as a huge scope of development opportunity. In order to promote the gradual transformation of college teaching toward digitization, intelligence, and modernization, this paper comprehensively analyzes the impact of science and technology on college teaching. It further encourages the omnidirectional and multifaceted amalgamation of education with big data and cloud computing technology with an objective to improve the overall teaching level of colleges and universities. In order to realize the accurate evaluation of university teaching reform and improve teaching quality, the study presents an evaluation method of university teaching reform based on in-depth research network. Then, it further analyzes the main contents of university teaching reform, establishes the evaluation department of university teaching reform, and then establishes the evaluation model of university education reform. This is achieved by analyzing the relationship between university education reform and indicators using in-depth learning network followed by the development of simulation experiments pertinent to evaluation of university education reform. The results show that this method is helpful in improving the teaching quality.

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Section: Exploration Of Educational Reform Taking Online Teaching As ...mentioning

confidence: 99%

The Reform of University Education Teaching Based on Cloud Computing and Big Data Background

Liu

2022

Computational Intelligence and Neuroscience

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“…Khan et al 19 have proposed a system that uses the deep learning model MASK-RCNN for segmentation and pre-trained DenseNet for classification. Using YOLOv5, Shelatkar et al 20 describe a deep learning-based method for classifying and identifying brain tumours. To extract the features, a transfer learning concept is used which is then exposed to selection and classification stages.…”

Section: Literature Surveymentioning

confidence: 99%

Skin lesion classification of dermoscopic images using machine learning and convolutional neural network

Shetty¹,

Fernandes²,

Rodrigues³

et al. 2022

Sci Rep

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Detecting dangerous illnesses connected to the skin organ, particularly malignancy, requires the identification of pigmented skin lesions. Image detection techniques and computer classification capabilities can boost skin cancer detection accuracy. The dataset used for this research work is based on the HAM10000 dataset which consists of 10015 images. The proposed work has chosen a subset of the dataset and performed augmentation. A model with data augmentation tends to learn more distinguishing characteristics and features rather than a model without data augmentation. Involving data augmentation can improve the accuracy of the model. But that model cannot give significant results with the testing data until it is robust. The k-fold cross-validation technique makes the model robust which has been implemented in the proposed work. We have analyzed the classification accuracy of the Machine Learning algorithms and Convolutional Neural Network models. We have concluded that Convolutional Neural Network provides better accuracy compared to other machine learning algorithms implemented in the proposed work. In the proposed system, as the highest, we obtained an accuracy of 95.18% with the CNN model. The proposed work helps early identification of seven classes of skin disease and can be validated and treated appropriately by medical practitioners.

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“…Performing MRI for research is difficult due to cost burden. Recently, the use of deep learning algorithms in medical imaging is rapidly increasing 50 , 51 . If a model capable of diagnosing tarsal coalition using imaging findings of CT scans is developed, this problem could be improved.…”

Section: Discussionmentioning

confidence: 99%

Racial differences in prevalence and anatomical distribution of tarsal coalition

Park

Seok

Woo

et al. 2022

Sci Rep

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Previous studies have reported a prevalence of tarsal coalition of 0.03–13%. Calcaneonavicular coalition is known as main anatomical type, and the bilateral occurrence of tarsal coalition is known to be 50% or more. These are the results of studies on Caucasians, there have been few studies targeting large number of East Asians so far. We hypothesized that the prevalence and characteristics of tarsal coalition in East Asians might differ from those in Caucasians. The medical records of 839 patients who underwent bilateral computed tomography on foot and ankle in our hospital from January 2012 to April 2021 were retrospectively reviewed. The overall prevalence was 6.0%, talocalcaneal coalition was the most common anatomical type. The overall bilateral occurrence was 56.5%, talocalcaneal coalition had the highest bilateral occurrence (76.0%) among anatomical types. Isolated union of the posterior facet was the most common subtype of talocalcaneal coalition (43.2%). Talocalcaneal coalition had a significantly higher proportion of coalition-related symptomatic patients than calcaneonavicular coalition (p = 0.019). Our study showed a similar trend to other East Asian studies, confirming the existence of racial differences. The possibility of tarsal coalition in foot and ankle patients in East Asians should always be considered, and bilateral examination is essential for diagnosis.

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Diagnosis of Brain Tumor Using Light Weight Deep Learning Model with Fine-Tuning Approach

Cited by 41 publications

References 36 publications

The Reform of University Education Teaching Based on Cloud Computing and Big Data Background

The Reform of University Education Teaching Based on Cloud Computing and Big Data Background

Skin lesion classification of dermoscopic images using machine learning and convolutional neural network

Racial differences in prevalence and anatomical distribution of tarsal coalition

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