# A New COVID-19 Detection Method Based on CSK/QAM Visible Light Communication and Machine Learning
## 2 State-of-the-Art Techniques
### Galois Field Mapping/Galois Fields Demapping  
In [58], the author describes the problems faced and efforts to eradicate the COVID-19 pandemic. In order to achieve this objective, documentation is produced to examine the signatures of genomes using chaotic studies. First, alternative representations of the SAR-COV-2 DNA sequences, such as colour-coded images, indicator matrices, DNA walks, and chaotic games were created.  
In [59], the detection of cancer using images is proposed. Cells are constantly exposed to numerous mutagens that produce diverse types of DNA lesions. Eukaryotic cells have evolved to contain a vast array of DNA repair mechanisms that are capable of detecting and repairing these lesions, thereby preventing genomic instability. Based on their functions, repair proteins are recruited to lesions sequentially.  
In [60], the heltrons, eukaryotic transposable elements transposed by the rolling-circle mechanism, are defined. These have been identified in numerous species with highly variable copy numbers and, in some cases, they comprise a significant portion of the genome. Using images of the constituent helitron features and a pretrained neural network as a classifier, classification was conducted using the \(k\)-means features corresponding to genomic sequences, and this method was compared with the Support Vector Machine (SVM) and Random Forest methods.  
A few studies have employed Galois fields to numerically represent DNA [29; 31]. Representation through Galois Fields \(GF(p)\) is based on gel electrophoresis, a standard method for separating double-stranded DNA (dsDNA) fragments of different sizes previously obtained by the Polymerisation Chain Reaction. When interpreting the electrophoresis of \(GF(p)\) and its extension \(GF(p^{n})\), the standard notation [61; 62] is utilised. Pathogen-causing SARS-CoV-2 DNA is used for COVID-19 detection because it contains four distinct genes: Adenine (A), Cytosine (C), Guanine (G), and Thymine (T). By using four non-binary symbols, the four states \(2^{2^{i}},i=1\) can be represented by natural numbers such as \([0,1,2,3]\) or by colours such as \([red,green,blue,yellow]\)[63; 64].  
In [59], the author proposed the detection of cancer using images. Cells are constantly exposed to a variety of mutagens that generate various types of DNA lesions. In order to prevent genomic instability, eukaryotic cells have evolved a vast array of DNA repair mechanisms capable of detecting and repairing these lesions. According to their function, repair proteins are sequentially recruited to lesions.  
Reference [60] described how helitrons, eukaryotic transposable elements (tes) transposed by the rolling-circle mechanism, have been identified in numerous species with highly variable copy numbers and, in some cases, constitute a significant portion of the genome. Using images of the constituent helitron features and a pretrained neural network as a classifier, classification using the \(k\)-means features that correspond to genomic sequences was conducted, and a comparison to the SVM and Random Forest methods was made.  
Many studies have linked ML to the diagnosis of COVID-19 using lung X-rays [23; 65; 66]. Deep neural networks (DNN) were used to process images in [67], and statistical methods were used in conjunction with heuristic filtering to identify somatic mutations in tumour samples.