This extensive research explores the most recent developments in datascience as they relate to developing nations. It carefully looks at four different categories: In an effort to find the cutting edge of technologic...
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Federated learning is a new family of privacy-preserving machinelearning, tackling at the same time the most demanding challenges set by data-driven systems. In this paper, we attempt to present a study on federated ...
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Cardiovascular disease is a non-communicable disease that is one of the leading causes of mortality worldwide, and its prevalence is growing year after year. Most cardiovascular diseases require percutaneous coronary ...
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Cardiac images play a vital role in early detection and diagnosing the heart diseases. Due to the advancement in machinelearning techniques many tools are emerging for early detection of heart disease and its diagnos...
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Alzheimer's disease (AD) is a devastating neurological disorder that progressively worsens cognitive function and memory. Early detection is critical to avoiding worse symptoms. While computational approaches have...
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Different data analysis techniques are used to perform data analysis on big data. Results of the analysis are affected by missing data values generated due to data generation sources. The general approach is to discar...
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This note surveys developments in particle physics due to advances made in the fields of statistics, machinelearning, and artificial intelligence. With the aid of examples and recent work, this article attempts to gi...
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ISBN:
(纸本)9783031585012;9783031585029
This note surveys developments in particle physics due to advances made in the fields of statistics, machinelearning, and artificial intelligence. With the aid of examples and recent work, this article attempts to give a flavor of the effect of these advances on particle physics, including brief mention of cloud computing, classic machinelearning techniques, statistics applications, new ML/AI techniques, reinforcement learning, and other advances. Suggestions are made regarding the future.
To promptly obtain an accurate diagnosis to effectively manage and treat epilepsy. This research introduces a novel method for automating the epilepsy diagnostic process in EHRs using Natural Language Processing (NLP)...
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This study explores the pivotal role of machinelearning models in predicting genetic diseases, revolutionizing the landscape of genomic medicine. Genetic diseases, often arising from mutations in DNA sequences, pose ...
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This study aims to detect depression by integrating machinelearning with facial analysis. It features two main components: a ten-question multiple-choice questionnaire (MCQ) to assess depression aspects, and a video ...
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