Machine learning-empowered cis-diol metabolic fingerprinting enables precise diagnosis of primary liver cancer

Abstract

A mass spectrometric platform was built for in-depth profiling of mutational landscape of cis-diol metabolites from the healthy to primary liver cancer (PLC) patients. This method enabled more precise PLC diagnosis than protein marker-based methods.

Analysing pharmacodynamic interactions of traditional Chinese medicine in treating acute pancreatitis based on OPLS method

“…The data were calculated by normalization, and then visualized by applying pattern recognition methods, such as partial least squares (PLS), 21,22 orthogonal partial least squares (OPLS), 23,24 and the variable influence on projection approach for O2PLS (R) models, which is a model-based method for judging the importance of variables; its cornerstone is the 2-way formalism of the O2PLS models. 25 The study used Simca-p 12.0 to construct the model by OPLS and O2PLS when analysing a dependent variable or multiple dependent variables, respectively.…”

Glycan-specific molecularly imprinted polymers towards cancer diagnostics: merits, applications, and future perspectives

“…This property is advantageous for selectively enriching cis -diols from complex matrices. 120 However, when it comes to reporting precise information in diagnostic methods, the lack of specificity hinders the ability to precisely identify and differentiate between specific glycan structures.…”

The Role of Artificial Intelligence in the Detection and Implementation of Biomarkers for Hepatocellular Carcinoma: Outlook and Opportunities

“…Their dysregulation has been noted in many complex diseases, such as cancer and diabetes. A 2023 study demonstrated the ability of machine learning to interpret cis-diol metabolic fingerprinting for precise diagnosis of primary liver cancer [30]. Ge et al recently discovered VIPR1 as an early diagnostic biomarker through machine learning from microarray datasets [31].…”