Periapical dental X-ray image classification using deep neural networks

Review Computer Science, Artificial Intelligence

Descriptive analysis of dental X-ray images using various practical methods: A review

Anuj Kumar et al.

Summary: Dental imaging plays a crucial role in diagnosis and treatment planning, but the analysis process is challenging. Automation is essential in order to ensure accurate diagnosis and improved treatment planning.

PEERJ COMPUTER SCIENCE (2021)

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Article Computer Science, Artificial Intelligence

An integrated approach based on artificial intelligence and novel meta-heuristic algorithms to predict demand for dairy products: a case study

Alireza Goli et al.

Summary: This research focuses on predicting the demand for dairy products in Iran using statistical tests, time-series neural networks, improved artificial intelligence tools, and novel meta-heuristic algorithms. By identifying effective indicators and eliminating ineffective ones, the designed hybrid method yields high accurate results, demonstrating the ability to enhance demand prediction across various products.

NETWORK-COMPUTATION IN NEURAL SYSTEMS (2021)

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Article Computer Science, Artificial Intelligence

An extended approach to the diagnosis of tumour location in breast cancer using deep learning

Saeid Jafarzadeh Ghoushchi et al.

Summary: Breast cancer, one of the most common and deadly cancers in women, can significantly increase survival rates through early detection. This study focuses on using modified deep learning methods and convolutional neural networks to diagnose tumor locations in breast cancer.

JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING (2021)

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Article Biotechnology & Applied Microbiology

Lung Infection Segmentation for COVID-19 Pneumonia Based on a Cascade Convolutional Network from CT Images

Ramin Ranjbarzadeh et al.

Summary: Automated detection of lung infections from medical images using a convolutional neural network shows promise in improving diagnosis speed and accuracy of COVID-19. The proposed framework achieved high precision and recall rates, demonstrating its potential in enhancing patient treatment strategies for tackling the pandemic.

BIOMED RESEARCH INTERNATIONAL (2021)

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Article Multidisciplinary Sciences

Brain tumor segmentation based on deep learning and an attention mechanism using MRI multi-modalities brain images

Ramin Ranjbarzadeh et al.

Summary: This paper proposes an effective brain tumor segmentation system, which solves the problems of brain tumor localization and segmentation in MRI images through methods like preprocessing, Cascade Deep Learning model, and Cascade Convolutional Neural Network. The proposed model achieves competitive results on the BRATS 2018 dataset.

SCIENTIFIC REPORTS (2021)

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Article Energy & Fuels

Performance of different hybrid algorithms for prediction of wind speed behavior

Ali Mostafaeipour et al.

Summary: This study proposed three hybrid algorithms and evaluated their efficiency in predicting wind speed behavior using meteorological data. Findings show that the shuffled frog-leaping neural network hybrid algorithm is more suitable than other algorithms for wind speed prediction in the study area.

WIND ENGINEERING (2021)

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Article Dentistry, Oral Surgery & Medicine