Results 121 to 130 of about 29,311 (260)

Volumetric macromolecule identification in cryo-electron tomograms using capsule networks. [PDF]

BMC Bioinformatics, 2022
Hajarolasvadi N, Sunkara V, Khavnekar S, Beck F, Brandt R, Baum D.   +5 more
europepmc   +1 more source

Smart, Bio‐Inspired Polymers and Bio‐Based Molecules Modified by Zwitterionic Motifs to Design Next‐Generation Materials for Medical Applications

Advanced Functional Materials, EarlyView.
Bio‐based and (semi‐)synthetic zwitterion‐modified novel materials and fully synthetic next‐generation alternatives show the importance of material design for different biomedical applications. The zwitterionic character affects the physiochemical behavior of the material and deepens the understanding of chemical interaction mechanisms within the ...
Theresa M. Lutz, Jonas De Breuck, Sahar Salehi, Meike N. Leiske   +3 more
wiley   +1 more source

A pre-trained convolutional neural network with optimized capsule networks for chest X-rays COVID-19 diagnosis. [PDF]

Cluster Comput, 2023
AbouEl-Magd LM, Darwish A, Snasel V, Hassanien AE.   +3 more
europepmc   +1 more source

MOFs and COFs in Electronics: Bridging the Gap between Intrinsic Properties and Measured Performance

Advanced Functional Materials, EarlyView.
Metal‐organic frameworks (MOFs) and covalent organic frameworks (COFs) hold promise for advanced electronics. However, discrepancies in reported electrical conductivities highlight the importance of measurement methodologies. This review explores intrinsic charge transport mechanisms and extrinsic factors influencing performance, and critically ...
Jonas F. Pöhls, R. Thomas Weitz
wiley   +1 more source

Medical code prediction via capsule networks and ICD knowledge. [PDF]

BMC Med Inform Decis Mak, 2021
Bao W, Lin H, Zhang Y, Wang J, Zhang S.
europepmc   +1 more source

Unleashing the Power of Machine Learning in Nanomedicine Formulation Development

Advanced Functional Materials, EarlyView.
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore, Cristiano Pesce, Antonietta Greco, Claudia Pisante, Greta Avancini, Valentina Di Francesco, Yosi Shamay, Paolo Decuzzi   +7 more
wiley   +1 more source

Capsule networks for segmentation of small intravascular ultrasound image datasets. [PDF]

Int J Comput Assist Radiol Surg, 2021
Bargsten L, Raschka S, Schlaefer A.
europepmc   +1 more source

Spatio-Temporal Features Representation Using Recurrent Capsules for Monaural Speech Enhancement

IEEE Access
Single-channel speech enhancement is important for modern communication systems and has received a lot of attention. A convolutional neural network (CNN) successfully learns feature representations from speech spectrograms but loses spatial information ...
Jawad Ali, Nasir Saleem, Sami Bourouis, Eatedal Alabdulkreem, Hela El Mannai, Sami Dhahbi   +5 more
doaj   +1 more source

Complex Cryptographic and User‐Centric Physically Unclonable Functions Enabled by Strain‐Sensitive Nanocrystals via Selective Ligand Exchange

Advanced Functional Materials, EarlyView.
This study investigates electromechanical PUFs that improve on traditional electric PUFs. The electron transport materials are coated randomly through selective ligand exchange. It produces multiple keys and a key with motion dependent on percolation and strain, and approaches almost ideal inter‐ and intra‐hamming distances.
Seungshin Lim, Hanseok Seo, Taesung Park, Byung Ku Jung, Junhyeok Park, Young Kyun Choi, Dae Yang Oh, Soong Ju Oh   +7 more
wiley   +1 more source

Enhanced sentiment extraction architecture for social media content analysis using capsule networks. [PDF]

Multimed Tools Appl, 2023
Demotte P, Wijegunarathna K, Meedeniya D, Perera I.   +3 more
europepmc   +1 more source