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EASE DIAGNOSTICS UNIVERSAL PROGRAMMER II PDF

Cardiac amyloidosis (CA) occurs mainly in primary light-chain (AL) amyloidosis, hereditary transthyretin (ATTRv) amyloidosis and senile or wild-type transthyretin (ATTRwt) amyloidosis. Finally, a comparison with other existing methods is performed, demonstrating that the proposed algorithm outperforms the other approaches.Īmyloidosis is a heterogeneous group of diseases caused by the extracellular deposition of amyloid insoluble fibrils in multiple organs, resulting in various clinical manifestations.

The maximum accuracy achieved in INbreast dataset is 99.7%, MIAS dataset has 99.8% and CBIS-DDSM has 93.8%.

To extract the features and perform the classification, three publicly available datasets are used: INbreast, MIAS, and CBIS-DDSM. Finally, by using the optimized deep features, the machine learning classifiers are applied to classify the breast cancer images. The optimized features are fused and optimized by using MEWOA. The features are extracted, and optimization is performed. In the proposed method, the fine-tuned MobilenetV2 and Nasnet Mobile are applied for simulation. The CAD system’s accuracy improved by reducing the false-positive rates.The Modified Entropy Whale Optimization Algorithm (MEWOA) is proposed based on fusion for deep feature extraction and perform the classification. The best feature optimization is performed to classify the results accurately. This paper aims to investigate ways to prevent the disease as well as to provide new methods of classification in order to reduce the risk of breast cancer in women’s lives. There is still a need to improve existing CAD systems by incorporating new methods and technologies in order to provide more precise results. To early diagnose the disease and provide better treatment lot of CAD systems were established. To perform detection and classification of breast cancer many computer-aided diagnosis (CAD) systems have been established because the inspection of the mammogram images by the radiologist is a difficult and time taken task.

EASE DIAGNOSTICS UNIVERSAL PROGRAMMER II PDF

To view the papers in pdf format, click on the "PDF Full-text" link, and use the free Adobe Reader to open them.īreast cancer has affected many women worldwide.

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Knowing more about MALDI-ToF AI, especially its weakness, can increase our confidence in it and help us to use it better. We identified that uncommon bacterial strain or highly complicated bacterial strain composition would be the causes leading to AI uncertainties. In the study, we examined the association between specimen types, MS spectral quality, phenotypic antibiotic susceptibility, bacterial strain composition, and the AI’s predictions. However, the AI is not perfect yet, and the reason for uncertain or incorrect predictions has not been investigated. MALDI-ToF AI is a promising approach to provide more rapid and accurate antibiotic resistance and bring in more precise management of bacterial infections.