AI Medical Compendium Topic

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

Porosity

Showing 11 to 20 of 70 articles

Clear Filters

Constructing porous ZnFC-PA/PSF composite spheres for highly efficient Cs removal.

Journal of environmental sciences (China)
Radioisotope leaking from nuclear waste has become an intractable problem due to its gamma radiation and strong water solubility. In this work, a novel porous ZnFC-PA/PSF composite sphere was fabricated by immobilization of ferrocyanides modified zin...

Deep-learning-based pyramid-transformer for localized porosity analysis of hot-press sintered ceramic paste.

PloS one
Scanning Electron Microscope (SEM) is a crucial tool for studying microstructures of ceramic materials. However, the current practice heavily relies on manual efforts to extract porosity from SEM images. To address this issue, we propose PSTNet (Pyra...

Deep learning prediction and experimental investigation of specific capacitance of nitrogen-doped porous biochar.

Bioresource technology
N-doped porous biochar is a promising carbon material for supercapacitor electrodes due to its developed pore structure and high chemical activity which greatly affect the capacitive performance. Predicting the capacitance and exploring the most infl...

Hybrid machine learning model based predictions for properties of poly(2-hydroxyethyl methacrylate)-poly(vinyl alcohol) composite cryogels embedded with bacterial cellulose.

Journal of chromatography. A
Supermacroporous composite cryogels with enhanced adjustable functionality have received extensive interest in bioseparation, tissue engineering, and drug delivery. However, the variations in their components significantly impactfinal properties. Thi...

Causal prior-embedded physics-informed neural networks and a case study on metformin transport in porous media.

Water research
This study introduces a novel approach to transport modelling by integrating experimentally derived causal priors into neural networks. We illustrate this paradigm using a case study of metformin, a ubiquitous pharmaceutical emerging pollutant, and i...

Predicting and refining acid modifications of biochar based on machine learning and bibliometric analysis: Specific surface area, average pore size, and total pore volume.

The Science of the total environment
Acid-modified biochar is a modified biochar material with convenient preparation, high specific surface area, and rich pore structure. It has great potential for application in the heavy metal remediation, soil amendments, and carrying catalysts. Spe...

Au-decorated TiCT/porous carbon immunoplatform for ECM1 breast cancer biomarker detection with machine learning computation for predictive accuracy.

Talanta
Electrochemical immunosensors, surpassing conventional diagnostics, exhibit significant potential for cancer biomarker detection. However, achieving a delicate balance between signal sensitivity and operational stability, especially at the heterostru...

Osteoinductive biomaterials: Machine learning for prediction and interpretation.

Acta biomaterialia
Biomaterials with osteoinductivity are widely used for bone defect repair due to their unique structures and functions. Machine learning (ML) is pivotal in analyzing osteoinductivity and accelerating new material design. However, challenges include c...

Predicting ultrasound wave stimulated bone growth in bioinspired scaffolds using machine learning.

Journal of the mechanical behavior of biomedical materials
For conditions like osteoporosis, changes in bone pore geometry even when porosity is constant have been shown to correlate to increased fracture risk using techniques such as dual-energy x-ray absorptiometry (DXA) and computed tomography (CT). Addit...

Preparation of Multistage Pore TS-1 with Enhanced Photocatalytic Activity, Including Process Studies and Artificial Neural Network Modeling for Synergy Assessment.

Langmuir : the ACS journal of surfaces and colloids
Antibiotic residues have been found in several aquatic ecosystems as a result of the widespread use of antibiotics in recent years, which poses a major risk to both human health and the environment. At present, photocatalytic degradation is the most ...