AIMC Topic: Principal Component Analysis

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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...

Sensitive Detection and Identification Method of Erythrocyte-like Cells upon Doxorubicin Induced Differentiation with Vibrational Techniques.

Analytical chemistry
Altered differentiation of blood cell precursors and their clonal expansion occurs in various types of leukemia. One treatment strategy is to induce differentiation into the mature form, which is capable of undergoing apoptosis. It has been found tha...

The oral microbiome and its effect on exhaled breath volatile analysis-the elephant in the room.

Journal of breath research
The rapid transfer of volatiles from alveolar blood into the lungs and then out of the body in exhaled breath leads to the common and natural conclusion that these volatiles provide information on health and metabolic processes, with considerable pot...

Sex-estimation method for three-dimensional shapes of the skull and skull parts using machine learning.

Forensic science international
Sex estimation is an indispensable test for identifying skeletal remains in the field of forensic anthropology. We developed a novel sex-estimation method for skulls and several parts of the skull using machine learning. A total of 240 skull shapes w...

Label-free rapid diagnosis of jaw osteonecrosis via the intersection of Raman spectroscopy and deep learning.

Bone
OBJECTIVES: To establish a precise and efficient diagnostic framework for distinguishing medication-related osteonecrosis of the jaw, radiation-induced osteonecrosis of the jaw, and normal bone tissue, thus enhancing clinical decision-making and enab...

Plastics detection and sorting using hyperspectral sensing and machine learning algorithms.

Waste management (New York, N.Y.)
Plastic waste second life management requires effective detection (and sorting if necessary) techniques to tackle the environmental challenge it poses. This research explores the application of hyperspectral imaging in the spectral range 900-1700 nm ...

Mid-level data fusion of pleural effusion SERS spectra and serum CEA levels using machine learning algorithms for precise lung cancer detection.

Nanoscale
Accurate identification of clinically malignant pleural effusions is critical for cancer diagnosis and subsequent treatment planning. Here, surface-enhanced Raman spectroscopy (SERS) data of pleural effusions and serum carcinoembryonic antigen (CEA) ...

Leveraging infrared spectroscopy for cocoa content prediction: A dual approach with Kohonen neural network and multivariate modeling.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
People of all ages enjoy chocolate, and its popularity is attributed to its pleasant taste and aroma, as well as its associated health benefits. Produced through both artisanal and industrial processes, which involve harvesting, selecting, fermenting...

Interpretable Multimodal Deep Ensemble Framework Dissecting Bloodbrain Barrier Permeability with Molecular Features.

The journal of physical chemistry letters
Blood-brain barrier permeability (BBBP) prediction plays a critical role in the drug discovery process, particularly for compounds targeting the central nervous system. While machine learning (ML) has significantly advanced the prediction of BBBP, th...

Rapid identification of coffee species and origin using affordable multi-channel spectral sensor combined with machine learning.

Food research international (Ottawa, Ont.)
The rapid identification of coffee species and origin is critical for ensuring quality control and authenticity in the coffee industry. This study explores the use of an affordable multi-channel spectral sensor, AS7265X (410-940 nm), combined with ma...