Results 211 to 220 of about 106,821 (289)

PulmoX-Net: a channel-attention enhanced deep learning model for multi-class pulmonary pathology classification in chest radiography. [PDF]

Front Med (Lausanne)
Wu W, Shi F, Hu Y, Shi J, Yan Z, Yang J, Yu D.   +6 more
europepmc   +1 more source

Explaining the Origin of Negative Poisson's Ratio in Amorphous Networks With Machine Learning

Advanced Intelligent Discovery, EarlyView.
This review summarizes how machine learning (ML) breaks the “vicious cycle” in designing auxetic amorphous networks. By transitioning from traditional “black‐box” optimization to an interpretable “AI‐Physics” closed‐loop paradigm, ML is shown to not only discover highly optimized structures—such as all‐convex polygon networks—but also unveil hidden ...
Shengyu Lu, Xiangying Shen
wiley   +1 more source

Quantitative investigation on working memory patterns through EEG based on visual attention task for children with learning disability. [PDF]

Front Syst Neurosci
Vidhusha S, Karthika S, Sahana N, Sabari Srinivas A, Selvarajan S, Sivakumar NR, Yogarayan S.   +6 more
europepmc   +1 more source

DeepMapper: Attention‐Based AutoEncoder for System Identification in Wound Healing and Stage Prediction

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, Ksenia Zlobina, Michael Briden, Oscar Avalos, Héctor Carrión, Sebastian Osorio, Hsin‐ya Yang, Alexandra Nava, Michelle D. Bagood, Marco Rolandi, Roslyn Rivkah Isseroff, Marcella Gomez   +11 more
wiley   +1 more source

Research on a rapid and accurate diagnosis platform for liver fibrosis based on machine learning-assisted SERS technology. [PDF]

Biomed Opt Express
Dai C, Bi C, Huang Y, Feng X.
europepmc   +1 more source

Overcoming the Nyquist Limit in Molecular Hyperspectral Imaging by Reinforcement Learning

Advanced Intelligent Discovery, EarlyView.
Explorative spectral acquisition guide automatically selects informative spectral bands to optimize downstream tasks, outperforming full‐spectrum acquisition. The selected hyperspectral data are used for tasks such as unmixing and segmentation. BandOptiNet encodes selection states and outputs optimal bands to guide spectral acquisition. Recent advances
Xiaobin Tang, Yongqing Zhang, Xinyu Deng, Hyeon Jeong Lee, Delong Zhang   +4 more
wiley   +1 more source

A federated multimodal deep learning framework for brain tumor classification using MRI. [PDF]

Front Artif Intell
Lakshmi Vasanthi K, Sree Darshne J, Venkatasubbu P, Ramasubramanian P.   +3 more
europepmc   +1 more source

Spatially Informed Feature Selection and Machine Learning in Matrix‐Assisted Laser Desorption/Ionization Imaging for Cohort‐Scale Molecular Tissue Phenomics in Glioblastoma

Advanced Intelligent Discovery, EarlyView.
Matrix‐assisted laser desorption/ionization imaging‐based identification of reliable small molecule markers across heterogeneous glioblastoma cohorts is challenging with intensity‐only methods. We present spatially informed feature selection (SIFS), a spatially informed framework that prioritizes molecules consistently colocalizing with histopathology.
Shad A. Mohammed, Denis Abu Sammour, Dirk C. Hoffmann, Philipp Sievers, Tobias Bausbacher, Melissa Hahn, Yasemin Ucal, Iris Mildenberger, Christiane A. Opitz, Stefan Schmidt, Michael Platten, Oliver Wasenmüller, Wolfgang Wick, Andreas von Deimling, Tobias Kessler, Carsten Hopf   +15 more
wiley   +1 more source

Development of a High-Sensitivity Screening Tool for Neuropathic Pain Integrating PainDETECT and BS-POP Using Machine Learning. [PDF]

J Pain Res
Furuya T, Yoshikai N, Suzuki S, Sawada H, Matsumoto K, Saito S, Ozaki R, Tsujisawa H, Nakanishi K.   +8 more
europepmc   +1 more source