Blood cancer diagnosis using ensemble learning based on a random subspace method in laser-induced breakdown spectroscopy.

There are two main challenges in the diagnosis of blood cancer. The first is to diagnose cancer from healthy control, and the second is to identify the types of blood cancer. The chemometrics method combined with laser-induced breakdown spectroscopy (LIBS) can be used for cancer detection.

Diagnosis of nasopharyngeal carcinoma from serum samples using hyperspectral imaging combined with a chemometric method.

Diagnosing nasopharyngeal carcinoma (NPC) is a significant challenge because of the highly complex process. We proposed an approach to diagnose NPC serum using a combination of hyperspectral imaging and weight-based principal component analysis. Samples were prepared by pressing boric acid into pellets for use as the sera substrate.

Accuracy improvement of quantitative analysis in spatially resolved fiber-optic laser-induced breakdown spectroscopy.

Fiber-optic laser-induced breakdown spectroscopy (FO-LIBS) has been employed in many applications because of the flexibility of optical fiber cable. However, the inhomogeneous elemental distribution of plasmas can cause a self-absorption effect and, hence, significantly hinder the determination of FO-LIBS. Here, to solve this flaw, we took iron (Fe), magnesium (Mg), and zinc (Zn) elements in aluminum alloy as examples to investigate the self-absorption reduction and accuracy improvement using spatially resolved FO-LIBS.

Accuracy and stability improvement for meat species identification using multiplicative scatter correction and laser-induced breakdown spectroscopy.

An efficient method has been developed to identify meat species by using laser-induced breakdown spectroscopy (LIBS). To improve the accuracy and stability of meat species identification, multiplicative scatter correction (MSC) was adopted to first pretreat the spectrum for correction of spectrum scatter. Then the corrected spectra were identified by using the K-nearest neighbor (KNN) model.