Results 241 to 250 of about 3,188,697 (327)

A Novel Mixed Convolution Transformer Model for the Fast and Accurate Diagnosis of Glioma Subtypes

Advanced Intelligent Systems, EarlyView.
The mixed convolutional transformer model represents a novel approach for the accurate and rapid diagnosis of glioma subtypes. This model employs advanced, complex layers and functions, establishing its uniqueness and enhancing its ability to deliver precise outcomes in glioma subtype detection.
S. M. Nuruzzaman Nobel, S. M. Masfequier Rahman Swapno, Md Babul Islam, AKM Azad, Salem A. Alyami, Md Alamin, Pietro Liò, Mohammad Ali Moni   +7 more
wiley   +1 more source

Study on real-time warning system of blind path for the visually impaired based on improved deep residual shrinkage network. [PDF]

Sci Rep
Yu Z, Wang F.
europepmc   +1 more source

AF classification from a short single lead ECG recording: The PhysioNet/computing in cardiology challenge 2017

2017 Computing in Cardiology (CinC), 2017
G. Clifford, Chengyu Liu, Benjamin Moody, Li-wei H. Lehman, Ikaro Silva, Qiao Li, Alistair E. W. Johnson, R. Mark   +7 more
semanticscholar   +1 more source

Algorithmically Enhanced Wearable Multimodal Emotion Sensor

Advanced Intelligent Systems, EarlyView.
This study presents a fully printed, organic wearable sensor for multimodal emotion sensing by noninvasively monitoring physiological indicators like physiological pulse, breathing patterns, and voice signatures. Using LSTM networks and Q‐learning, the system achieves over 91% accuracy, offering a pathway to understanding complex emotions and enhancing
Anand Babu, Getnet Kassahun, Isabelle Dufour, Dipankar Mandal, Damien Thuau   +4 more
wiley   +1 more source

ResM-FusionNet for efficient landslide detection algorithm with a hybrid architecture. [PDF]

Sci Rep
Ren X, Wu X, Zhai D, Wang X, He N, Tarif M.   +5 more
europepmc   +1 more source

A Physics‐Informed Neural Network as a Digital Twin of Optically Turbid Media

Advanced Intelligent Systems, EarlyView.
In this work, a physics‐informed neural network is presented as a digital twin for modeling and studying optically turbid media without requiring reference light. The model learns and integrates complex wavefront modulation behavior, ensuring robustness without explicit calibration.
Mohammadrahim Kazemzadeh, Liam Collard, Linda Piscopo, Massimo De Vittorio, Ferruccio Pisanello   +4 more
wiley   +1 more source

Evaluating knowledge fusion models on detecting adverse drug events in text. [PDF]

PLOS Digit Health
Wegner P, Fröhlich H, Madan S.
europepmc   +1 more source

Generative Inverse Design of Metamaterials with Functional Responses by Interpretable Learning

Advanced Intelligent Systems, EarlyView.
This work introduces random‐forest‐based interpretable generative inverse design (RIGID), a new single‐shot inverse design method for metamaterials using interpretable machine learning and Markov chain Monte Carlo sampling. Once trained on a small dataset, RIGID can estimate the likelihood of designs achieving target behaviors (e.g., wave‐based ...
Wei (Wayne) Chen, Rachel Sun, Doksoo Lee, Carlos M. Portela, Wei Chen   +4 more
wiley   +1 more source

ALL diagnosis: can efficiency and transparency coexist? An explainble deep learning approach. [PDF]

Sci Rep
Muhammad D, Salman M, Keles A, Bendechache M.   +3 more
europepmc   +1 more source

π‐PhenoDrug: A Comprehensive Deep Learning‐Based Pipeline for Phenotypic Drug Screening in High‐Content Analysis

Advanced Intelligent Systems, EarlyView.
This study develops a deep learning‐based pipeline named π‐PhenoDrug for cell phenotype‐driven drug activity screening. π‐PhenoDrug integrates cell segmentation, morphological profile construction, and phenotype analysis modules, and it can assess drug effects on living cells in both supervised and unsupervised modes.
Xiao Li, Qinxue Ouyang, Mingfei Han, Xiaoqing Liu, Fuchu He, Yunping Zhu, Ling Leng, Jie Ma   +7 more
wiley   +1 more source