15 天前 - … using destructive or non-destructive methods with enough concrete samples. …
analysis, the use of machine learning methods such as Neural Net Fitting (NNF) to predict a data …

20 天前 - … Artificial intelligence was founded as an academic discipline in 1956, with hopes
based on dissecting data into specific subfields, such as robotics or machine learning, and …

23 天前 - … data cubes approach, which could organize multisource remote sensing data in
a unified manner and inherit the deep learning methods. Based on the spatiotemporal …

32 天前 - … Vector Machine (… data analysis and overcoming intricate challenges have become
achievable through the utilization of deep learning, which has proven to be a potent approach…

38 天前 - … By constructing performance prediction models using advanced data analytics
and machine learning algorithms, this approach enhances the accuracy of predicting how …

38 天前 - … By constructing performance prediction models using advanced data analytics
and machine learning algorithms, this approach enhances the accuracy of predicting how …

49 天前 - … Here, we provide proof-of-concept that machine learning-guided proteomic biomarker
discovery studies have the potential to improve prediction models for selected diseases. …

52 天前 - … It integrates Machine Learning (ML) techniques with DEA to develop an innovative
method for forecasting near-future PrP levels for proactive management of safety risks. The …

68 天前 - … Urgent innovation is needed to address this issue. This study aimed to use machine
learning methods … Using the training group, six machine learning models were developed, …

68 天前 - … This work proposes a prior and segmentation-free deep learning (DL)-based
PVC method for 99m Tc-TRODAT-1 PD SPECT. Methods: A population of 227 99m Tc-TRODAT-1 …