AIMC Topic: Metal Nanoparticles

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Diagnosis of uterine diseases by label-free serum SERS fingerprints with machine learning.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Early detection of uterine diseases is critically important for women's reproductive health. Here, we propose a novel and robust serum-based SERS analysis platform that integrates machine learning algorithms. This is the first application of it in th...

The vertices number determined SERS activity of polyhedra and the application in oral cancer detection based on deep learning.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Due to the inherent specificity and high sensitivity, biomedical detections based on Surface-Enhanced Raman Scattering (SERS) technology have garnered increasing attention. In the SERS detection process, fabricating a highly sensitive SERS substrate ...

Microfluidics-based label-free SERS profiling of exosomes with machine learning for osteosarcoma diagnosis.

Talanta
Osteosarcoma (OS) calls for early diagnosis to significantly improve patient survival rates. Exosomes hold significant potential as noninvasive biomarkers for the early diagnosis of cancer. Here, we design a microfluidic device to purify and analyze ...

Rapid and quantitative detection of Botryosphaeria dothidea by surface-enhanced Raman spectroscopy with size-controlled spherical metal nanoparticles combined with machine learning.

International journal of food microbiology
Botryosphaeria dothidea infection has become a major factor affecting the quality of postharvest fruits, so detection of B. dothidea infection is very important to control the spread of infection and ensure food safety. In this study, we built a moni...

Advanced SERSome-based artificial-intelligence technology for identifying medicinal and edible homologs.

Talanta
Medicinal and edible homologs (MEHs) offer significant preventive and therapeutic benefits for various diseases and health functions. However, the widespread application of MEHs faces significant challenges, particularly in quality control and rapid ...

Fluorescent sensor array for rapid bacterial identification using antimicrobial peptide-functionalized gold nanoclusters and machine learning.

Talanta
Bacterial infectious diseases pose significant challenges to public health, emphasizing the need for rapid and accurate diagnostic tools. Here, we introduced a multichannel fluorescent sensor array based on antimicrobial peptide-functionalized gold n...

Dual-mode nanosensor for sensitive detection of methotrexate based on fluorescence technology and deep learning algorithms.

Analytica chimica acta
BACKGROUND: Methotrexate (MTX) in the body can result in severe, potentially life-threatening side effects. As a result, it is imperative to establish a dependable, precise, and specific method for detecting MTX. However, conventional sensors often s...

Molecule-Responsive SERS Sensors for Urine Diagnosis of Kidney Diseases Enhanced by Neural Networks.

Analytical chemistry
Early diagnosis of kidney disease is crucial for treatment and prognosis. Compared with kidney biopsy, a noninvasive urine-based diagnosis method of kidney disease can be more convenient and less painful for patients. Urine is closely associated with...

Deep Learning-Assisted Nanocavity Sensor for Amphiphilic Biomarker Analysis.

Analytical chemistry
Fluorescence enhancement using nanocavity structures is a promising approach for rapid detection of amphiphilic biomarkers, which are essential for diagnosing diseases such as cancer and infections. This paper presents the use of a silver nanocube (A...

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...