The proceedings contain 94 papers. The topics discussed include: bioacoustic data augmentation techniques for data-driven apiculture;early screening of breast cancer using machinelearning algorithms: a comparative st...
ISBN:
(纸本)9798350391213
The proceedings contain 94 papers. The topics discussed include: bioacoustic data augmentation techniques for data-driven apiculture;early screening of breast cancer using machinelearning algorithms: a comparative study;promoting equity: assessing algorithmic fairness in machinelearning approaches for predicting Alzheimer’s disease;general population projection models with census data;data-driven machinelearning hazmat incident duration prediction with random forest;application of machinelearning algorithms for predicting employee attrition;clustering optimization via centroid neural network ensemble;enhanced stratified sampling: a method for privacy preserving big data publishing;and deep reinforcement learning for automated stock trading using different reward schemes.
This paper applies machinelearning methods to generate effective population projections using the American Community Survey (ACS) 5-Year Estimate data. To quantify the error margin in the population projection for ea...
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Foundation models have emerged as remarkable tools in medical image analysis leading to a new era of smart healthcare and offering sophisticated capabilities to enhance diagnostic accuracy, treatment planning, and pat...
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Lung cancer remains a significant global health challenge, with early detection being crucial for improving patient outcomes. This paper presents the development of computer-aided diagnosis classification algorithms t...
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It is difficult to differentiate Prostate Cancer from Prostate Hyperplasia in medical images. We assess the utility of deep learning techniques applied to Magnetic Resonance Diffusion images to improve diagnosis. We i...
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The Internet of Medical Things (IoMT) has the potential to transform healthcare, but faces challenges like energy consumption, data scheduling, latency, privacy, joint offloading, limited data, and security. To addres...
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Spatial Crowdsourcing (SC) is an emerging crowdsourcing paradigm that allocates tasks based on real-time user locations to perform spatiotemporal relevant tasks. However, relying on continuously updated location and p...
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This paper explores the potential of data augmentation techniques to improve the detection of bee activities using machinelearning models applied to bioacoustic data. Traditional machinelearning methods used in bee ...
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The weather is the state of atmosphere that can be described with various categorical and quantitative parameters. A lot of everyday operations (ex: logistics) depend on these parameters and meteorologists all over th...
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Globally, supply and demand dynamics, energy security considerations, and volatile international relations influence the crude oil energy landscape. This research aims to predict the formation and dissolution of crude...
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