AIMC Topic: Formaldehyde
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Self-Taught Learning Based on Sparse Autoencoder for E-Nose in Wound Infection Detection.
Sensors (Basel, Switzerland)
Oct 7, 2017
For an electronic nose (E-nose) in wound infection distinguishing, traditional learning methods have always needed large quantities of labeled wound infection samples, which are both limited and expensive; thus, we introduce self-taught learning comb...
Machine Learning-based Classification of Diffuse Large B-cell Lymphoma Patients by Their Protein Expression Profiles.
Molecular & cellular proteomics : MCP
Aug 26, 2015
Characterization of tumors at the molecular level has improved our knowledge of cancer causation and progression. Proteomic analysis of their signaling pathways promises to enhance our understanding of cancer aberrations at the functional level, but ...
Tissue Embedding
Tissue Fixation
Phosphoprotein Phosphatases
Gene Expression Regulation, Neoplastic
Proteomics
Proteome
Signal Transduction
Lymphoma, Large B-Cell, Diffuse
Cell Line, Tumor
Biomarkers, Tumor
Apoptosis Regulatory Proteins
Isotope Labeling
GTPase-Activating Proteins
Neprilysin
Principal Component Analysis
Formaldehyde
Neoplasm Proteins
Humans
Machine Learning
An Artificial Olfactory System Based on Synaptic Transistors for Precepting Hazardous Gas to Simulate Organ Injury.
ACS sensors
May 23, 2025
Recent advances in artificial olfactory systems have attracted significant attention for their potential applications in humanoid robots and intelligent nasal devices capable of identifying objects and sensing hazards; however, the memory function is...
Biological activities of crude leaf extract and fractions of Scutellaria sibthorpii (Benth.) Halácsy: An endemic plant of North-Cyprus.
Pakistan journal of pharmaceutical sciences
Nov 1, 2023
Scutellaria sibthorpii is used in treatment of bacterial infections, pains and inflammations. The leaf was extracted by maceration and then partitioned with hexane, ethyl acetate and n-butanol. The extract was screened for phytochemicals. The antioxi...
A Computer-Aided Diagnosis System of Fetal Nucleated Red Blood Cells With Convolutional Neural Network.
Archives of pathology & laboratory medicine
Nov 1, 2022
CONTEXT.—: The rapid recognition of fetal nucleated red blood cells (fNRBCs) presents considerable challenges.
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