Results 151 to 160 of about 34,857 (308)
Advanced Intelligent Discovery, EarlyView.Exosomes are emerging as powerful biomarkers for disease diagnosis and monitoring. This review highlights the integration of surface‐enhanced Raman spectroscopy with artificial intelligence to enhance molecular fingerprinting of exosomes. Machine learning and deep learning techniques improve spectral interpretation, enabling accurate classification of ...
Munevver Akdeniz +2 more
wiley +1 more source
, 2010 This paper presents an approach to machine fault diagnosis and condition prognosis based on classification and regression tress (CART) and neuro-fuzzy inference systems (ANFIS).
Yang, Bo-Suk +3 more
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Advanced Intelligent Discovery, EarlyView.A sequential deep learning framework is developed to model surface roughness progression in multi‐stage microneedle fabrication. Using real‐world experimental data from 3D printing, molding, and casting stages, an long short‐term memory‐based recurrent neural network captures the cumulative influence of geometric parameters and intermediate outputs ...
Abdollah Ahmadpour +5 more
wiley +1 more source
Deep Learning‐Assisted Coherent Raman Scattering Microscopy
Advanced Intelligent Discovery, EarlyView.The analytical capabilities of coherent Raman scattering microscopy are augmented through deep learning integration. This synergistic paradigm improves fundamental performance via denoising, deconvolution, and hyperspectral unmixing. Concurrently, it enhances downstream image analysis including subcellular localization, virtual staining, and clinical ...
Jianlin Liu +4 more
wiley +1 more source
High-order fuzzy time series self-adaption prediction method based on spectral clustering
Tongxin xuebao, 2016 A fuzzy time series self-adaption prediction method based on spectral clusterin and data characteristics was proposed. First, based on spectral clustering and the racteristics of data, the number and scope of the discourses was obtained to convert into ...
Chun-nan ZHOU +4 more
doaj
Composition‐Aware Cross‐Sectional Integration for Spatial Transcriptomics
Advanced Intelligent Discovery, EarlyView.Multi‐section spatial transcriptomics demands coherent cell‐type deconvolution, domain detection, and batch correction, yet existing pipelines treat these tasks separately. FUSION unifies them within a composition‐aware latent framework, modeling reads as cell‐type–specific topics and clustering in embedding space.
Qishi Dong +5 more
wiley +1 more source
Advanced Intelligent Discovery, EarlyView.The authors develop a deep learning model for real‐time tracking of wound progression. The deep learning framework maps the nonlinear evolution of a time series of images to a latent space, where they learn a linear representation of the dynamics. The linear model is interpretable and suitable for applications in feedback control.
Fan Lu +11 more
wiley +1 more source
Havacılık ve Uzay Teknolojileri Dergisi, 2010 Time series models have been utilized to make accurate predictions in production. This paper employs a 3 year period of aviation fuel production data of Turkey as experimental data set.
Kubilay Ecerkale +2 more
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Forecasting Unemployment Rate Using a Neural Network with Fuzzy Inference System [PDF]
Greece is a low-productivity economy with an ineffective welfare state, relying almost exclusively on low wages and social transfers. Failure to come to terms with this reality hampers both the appropriateness of EU recommendations and the Greek ...
Camelia Ioana Ucenic +2 more
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