Urine fluorescence spectroscopy combined with machine learning for screening of hepatocellular carcinoma and liver cirrhosis

Rapid detection of cholecystitis by serum fluorescence spectroscopy combined with machine learning

“…Dos Santos et al [18] applied fluorescence spectroscopy to rapidly differentiate the serum samples of Alzheimer disease patients from those of healthy individuals. Some researchers have established that an excitation wavelength of 405 nm yields more fluorescence information than other excitation wavelengths [19], which is consistent with the findings of our previous study [13]. Additionally, machine learning algorithms, which offer remarkable advantages in analysing large and complex data, have been considered a potential tool for improving disease diagnosis [20].…”

“…Preliminary analysis of the cholecystitis group fluorescence spectra indicated that the main features were emission peaks at 450-550 and 600-690 nm and that the excitation wavelength appeared at 405 nm. Therefore, the excitation wavelength was set to 405 nm, the fluorescence spectra were recorded from 430 to 750 nm, and the width of the emission and excitation slits was 5 nm [13,17]. The spectral integration time and acquisition interval were 100 ms and 1 nm, respectively.…”

“…Fluorescence spectroscopy is a spectroscopic detection technique based on the fluorescence properties of biomolecules; it is applicable to quantitative and qualitative analysis and has been widely used in the field of disease diagnosis [11, 12]. Fluorescence spectroscopy has the advantages of simplicity, rapid detection, high accuracy and cost‐efficiency; moreover, sample pre‐treatment is not required [13]. Blood may accurately reflect changes in the internal environment of the human body [14].…”

Rapid and non‐invasive detection of cystic echinococcosis in sheep based on serum fluorescence spectrum combined with machine learning algorithms

“…It is considered that fluorescence spectroscopy can be used for rapid identification of pharyngitis diseases and can be used in clinical practice in the future. Fluorescence spectrum detection only needs a small amount of serum [19]. Serum is composed of porphyrin, enzyme, lipid, and other natural fluorophores, which have different fluorescence characteristics under different pathological conditions [20,21].…”

“…Fluorescence spectroscopy was used by Francisco et al [18] to evaluate its ability to distinguish between probably cancerous conditions and normal oral mucosa, and they concluded that it can be very effective in doing so. Timurzieva et al [19] used fluorescence spectroscopy to study the importance of inflammatory diseases of the pharynx. It is considered that fluorescence spectroscopy can be used for rapid identification of pharyngitis diseases and can be used in clinical practice in the future.…”