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Emad Abd Al Rahman¹, Nur Intan Raihana Ruhaiyem^1,*, Majed Bouchahma², Kamarul Imran Musa³
Intelligent Automation & Soft Computing, DOI:10.32604/iasc.2023.032580
Abstract This study offers a framework for a breast cancer computer-aided treatment prediction (CATP) system. The rising death rate among women due to breast cancer is a worldwide health concern that can only be addressed by early diagnosis and frequent screening. Mammography has been the most utilized breast imaging technique to date. Radiologists have begun to use computer-aided detection and diagnosis (CAD) systems to improve the accuracy of breast cancer diagnosis by minimizing human errors. Despite the progress of artificial intelligence (AI) in the medical field, this study indicates that systems that can anticipate a treatment plan once a patient has… More >

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Open Access

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D. Vidyabharathi^1,*, V. Mohanraj²
Intelligent Automation & Soft Computing, DOI:10.32604/iasc.2023.032255
Abstract For training the present Neural Network (NN) models, the standard technique is to utilize decaying Learning Rates (LR). While the majority of these techniques commence with a large LR, they will decay multiple times over time. Decaying has been proved to enhance generalization as well as optimization. Other parameters, such as the network’s size, the number of hidden layers, dropouts to avoid overfitting, batch size, and so on, are solely based on heuristics. This work has proposed Adaptive Teaching Learning Based (ATLB) Heuristic to identify the optimal hyperparameters for diverse networks. Here we consider three architectures Recurrent Neural Networks (RNN),… More >

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Open Access

ARTICLE

A. Selvi^*, S. Thilagamani
Intelligent Automation & Soft Computing, DOI:10.32604/iasc.2022.029850
Abstract Mammography is considered a significant image for accurate breast cancer detection. Content-based image retrieval (CBIR) contributes to classifying the query mammography image and retrieves similar mammographic images from the database. This CBIR system helps a physician to give better treatment. Local features must be described with the input images to retrieve similar images. Existing methods are inefficient and inaccurate by failing in local features analysis. Hence, efficient digital mammography image retrieval needs to be implemented. This paper proposed reliable recovery of the mammographic image from the database, which requires the removal of noise using Kalman filter and scale-invariant feature transform… More >

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Open Access

ARTICLE

Hosam Alhakami^1,*, Abdullah Baz², Mohammad Al-shareef³, Rajeev Kumar⁴, Alka Agrawal⁵, Raees Ahmad Khan⁵
Intelligent Automation & Soft Computing, DOI:10.32604/iasc.2023.021560
Abstract Recent transformation of Saudi Arabian healthcare sector into a revenue producing one has signaled several advancements in healthcare in the country. Transforming healthcare management into Smart hospital systems is one of them. Secure hospital management systems which are breach-proof only can be termed as effective smart hospital systems. Given the perspective of Saudi Vision-2030, many practitioners are trying to achieve a cost-effective hospital management system by using smart ideas. In this row, the proposed framework posits the main objectives for creating smart hospital management systems that can only be acknowledged by managing the security of healthcare data and medical practices.… More >

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