AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Nanoparticles

Showing 51 to 60 of 194 articles

Clear Filters

Artificial intelligence in nanotechnology for treatment of diseases.

Journal of drug targeting
Nano-based drug delivery systems (DDSs) have demonstrated the ability to address challenges posed by therapeutic agents, enhancing drug efficiency and reducing side effects. Various nanoparticles (NPs) are utilised as DDSs with unique characteristics...

Development of fucoidan/polyethyleneimine based sorafenib-loaded self-assembled nanoparticles with machine learning and DoE-ANN implementation: Optimization, characterization, and in-vitro assessment for the anticancer drug delivery.

International journal of biological macromolecules
This study aims to develop sorafenib-loaded self-assembled nanoparticles (SFB-SANPs) using the combined approach of artificial neural network and design of experiments (ANN-DoE) and to compare it with other machine learning (ML) models. The central c...

Perovskite Probe-Based Machine Learning Imaging Model for Rapid Pathologic Diagnosis of Cancers.

ACS nano
Accurately distinguishing tumor cells from normal cells is a key issue in tumor diagnosis, evaluation, and treatment. Fluorescence-based immunohistochemistry as the standard method faces the inherent challenges of the heterogeneity of tumor cells and...

Predicting tissue distribution and tumor delivery of nanoparticles in mice using machine learning models.

Journal of controlled release : official journal of the Controlled Release Society
Nanoparticles (NPs) can be designed for targeted delivery in cancer nanomedicine, but the challenge is a low delivery efficiency (DE) to the tumor site. Understanding the impact of NPs' physicochemical properties on target tissue distribution and tum...

Quantitative Three-Dimensional Imaging Analysis of HfO Nanoparticles in Single Cells via Deep Learning Aided X-ray Nano-Computed Tomography.

ACS nano
It is crucial for understanding mechanisms of drug action to quantify the three-dimensional (3D) drug distribution within a single cell at nanoscale resolution. Yet it remains a great challenge due to limited lateral resolution, detection sensitiviti...

Enhanced Nanoparticle Recognition via Deep Learning-Accelerated Plasmonic Sensing.

Biosensors
Surface plasmon microscopy proves to be a potent tool for capturing interferometric scattering imaging data of individual particles at both micro and nanoscales, offering considerable potential for label-free analysis of bio-particles and bio-molecul...

AGILE platform: a deep learning powered approach to accelerate LNP development for mRNA delivery.

Nature communications
Ionizable lipid nanoparticles (LNPs) are seeing widespread use in mRNA delivery, notably in SARS-CoV-2 mRNA vaccines. However, the expansion of mRNA therapies beyond COVID-19 is impeded by the absence of LNPs tailored for diverse cell types. In this ...

Machine Learning-Assisted High-Throughput Identification and Quantification of Protein Biomarkers with Printed Heterochains.

Journal of the American Chemical Society
Advanced in vitro diagnosis technologies are highly desirable in early detection, prognosis, and progression monitoring of diseases. Here, we engineer a multiplex protein biosensing strategy based on the tunable liquid confinement self-assembly of mu...

Biohybrid microrobots regulate colonic cytokines and the epithelium barrier in inflammatory bowel disease.

Science robotics
Cytokines have been identified as key contributors to the development of inflammatory bowel disease (IBD), yet conventional treatments often prove inadequate and carry substantial side effects. Here, we present an innovative biohybrid robotic system,...

The role of artificial intelligence and data science in nanoparticles development: a review.

Nanomedicine (London, England)
Artificial intelligence has revolutionized many sectors with unparalleled predictive capabilities supported by machine learning (ML). So far, this tool has not been able to provide the same level of development in pharmaceutical nanotechnology. This ...