AIMC Topic: Fluorescence

Clear Filters Showing 91 to 100 of 107 articles

Machine Learning-Driven Multi-Emission Fluorescence Array for Simultaneous Size Discrimination and Quantification of Gold Nanoparticles.

Analytical chemistry
Gold nanoparticles (AuNPs) exhibit size-dependent environmental behaviors and bioaccumulation risks, necessitating precise characterization of their hydrodynamic dimensions and concentrations for toxicity assessment. Existing analytical platforms are...

Machine learning-assisted ratiometric fluorescence sensor array for recognition of multiple quinolones antibiotics.

Food chemistry
Developing analytical methods for simultaneous detection of multiple antibiotic residues is crucial for environmental protection and human health. In this study, a dual lanthanide fluorescence probe (GDP-Eu-Tb) based on nucleotides has been designed....

Machine Learning-Assisted Multicolor Fluorescence Assay for Visual Data Acquisition and Intelligent Inspection of Multiple Food Hazards Regardless of Matrix Interference.

ACS sensors
Regarding the significant health risks of pesticide residue in foods, while current sensors still suffer from limited efficiency and stability, as well as difficulties in qualitative identification and quantitative detection of mixtures, development ...

A multimodal deep learning model for detecting endoscopic images of near-infrared fluorescence capsules.

Biosensors & bioelectronics
Early screening for gastrointestinal (GI) diseases is critical for preventing cancer development. With the rapid advancement of deep learning technology, artificial intelligence (AI) has become increasingly prominent in the early detection of GI dise...

Machine learning-assisted washing-free detection of extracellular vesicles by target recycling amplification based fluorescent aptasensor for accurate diagnosis of gastric cancer.

Talanta
Extracellular vesicles (EVs) are promising non-invasive biomarkers for cancer diagnosis. EVs proteins play a critical role in tumor progress and metastasis. However, accurately and reliably diagnosing cancers is greatly limited by single protein mark...

A Green Synchronous Fluorescence Analysis Approach for Simultaneous Determination of the Co-formulated Antihypertensives, Bisoprolol, and Amlodipine. Application to Plasma Samples, Market Formulations, Content Uniformity Test, and Greenness Evaluation.

Luminescence : the journal of biological and chemical luminescence
In this study, we present a direct, sensitive, and green spectrofluorimetric approach for simultaneous measurement of bisoprolol fumarate (BSL) and amlodipine besylate (AMD) in their tablets and plasma. This approach measures the synchronized fluores...

FMT-ReconNet: Fluorescence Molecular Tomography Reconstruction using Prior Knowledge and Deformation Neural Network.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Fluorescence molecular tomography (FMT) is a powerful imaging technique for 3D reconstruction of internal fluorescent sources. However, its spatial resolution is limited by a simplified forward model and an ill-posed inverse problem. To address this,...

Deep Learning for Breast Cancer Classification of Deep Ultraviolet Fluorescence Images toward Intra-Operative Margin Assessment.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Breast conserving surgery aims at the complete removal of malignant lesions while minimizing healthy tissue loss. To ensure the balance between complete resection of the cancer and conservation of healthy tissue, intra-operative margin assessment is ...

DeepLearnMOR: a deep-learning framework for fluorescence image-based classification of organelle morphology.

Plant physiology
The proper biogenesis, morphogenesis, and dynamics of subcellular organelles are essential to their metabolic functions. Conventional techniques for identifying, classifying, and quantifying abnormalities in organelle morphology are largely manual an...