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Št. zadetkov: 4
Nanovaccines to combat drug resistance
K. Manju, S. Niranjan Raj, Raghuraj Singh Chouhan, Syed Baker
Pregledni znanstveni članek
Oznake: nanovaccines;antimicrobial drug resistance;nanomaterials;HIV;WHO;
Background. The present review envisages the role of nanovaccines to combat the global challenges of antimicrobial resistance. Nanovaccines are a novel formulation comprised of nanomaterials coupled with an immunogenic component to elicit the immune response and provide protection against the desire ...
Leto: 2023 Vir: Institut Jožef Stefan (IJS)
Nanoagrosomes
K. Manju, H.K. Ranjini, S. Niranjan Raj, Raghuraj Singh Chouhan, Syed Baker
Pregledni znanstveni članek
Oznake: odpornost na antimikrobna zdravila;protimikrobna odpornost;nanoagrosomes;agriculture;phytopatogens;antimicrobial resistance;
Agriculture plays a crucial role in sustaining the global population with food safety and security. The inadequacy of current agrochemicals in effectively controlling microbial infestations necessitates immediate attention. The over usage of agrochemicals has posed significant threat to agriculture ...
Leto: 2023 Vir: Institut Jožef Stefan (IJS)
Uncertainty estimation and evaluation of deformation image registration based convolutional neural networks
Luciano Rivetti, Andrej Studen, Manju Sharma, Jason Chan, Robert Jeraj
Izvirni znanstveni članek
Oznake: medicinska fizika;medicinske slike;deformabilna poravnava slik;adaptivna radioterapija;globoko učenje;nevronske mreže;ocena negotovosti;medical physics;medical images;deformable image registration;adaptive radiotherapy;deep learning;neural networks;uncertainty estimation;
Objective. Fast and accurate deformable image registration (DIR), including DIR uncertainty estimation, is essential for safe and reliable clinical deployment. While recent deep learning models have shown promise in predicting DIR with its uncertainty, challenges persist in proper uncertainty evalua ...
Leto: 2024 Vir: Fakulteta za matematiko in fiziko (UL FMF)
DiffuseRT: predicting likely anatomical deformations of patients undergoing radiotherapy
A. Smolders, Luciano Rivetti, N. Vatterodt, S. S. Korreman, A. Lomax, Manju Sharma, Andrej Studen, D. C. Weber, Robert Jeraj, F. Albertini
Izvirni znanstveni članek
Oznake: medicinsko slikanje;radioterapija;globoko učenje;medical imaging;radiotherapy;deep learning;
Objective. Predicting potential deformations of patients can improve radiotherapy treatment planning. Here, we introduce new deep-learning models that predict likely anatomical changes during radiotherapy for head and neck cancer patients. Approach. Denoising diffusion probabilistic models (DDPMs) w ...
Leto: 2024 Vir: Fakulteta za matematiko in fiziko (UL FMF)
Št. zadetkov: 4
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