Machine learning (ML) is increasingly used in clinical oncology to diagnose cancers, predict
patient outcomes, and inform treatment planning. Here, we review recent applications of ML …

There exists a tremendous opportunity in identifying and determining the appropriate
predictive and prognostic biomarker (s) for risk stratification of patients with colorectal …

Circulating tumour DNA (ctDNA) assays conducted on plasma are rapidly developing a
strong evidence base for use in patients with cancer. The European Society for Medical …

The continuous improvement in cancer care over the past decade has led to a gradual
decrease in cancer-related deaths. This is largely attributed to improved treatment and …

Importance Detection of molecular residual disease and risk stratification as early as
possible may improve the treatment of patients with cancer. Efficient pragmatic tests are …

Tissue-based biopsy is the present main tool to explore the molecular landscape of cancer,
but it also has many limits to be frequently executed, being too invasive with the risk of side …

The innovation of liquid biopsy holds great potential to revolutionise cancer management
through early diagnosis and timely treatment of cancer. Integrative analysis of different …

In the era of precision oncology, use of circulating tumor DNA (ctDNA) is emerging as a
minimally invasive approach for the diagnosis and management of patients with cancer and …

Background Multiple approaches based on cell-free DNA (cfDNA) have been applied to
detect minimal residual disease (MRD) and to predict prognosis or recurrence. However, a …

Liquid biopsies that detect circulating tumour DNA (ctDNA) have the potential to
revolutionise the personalised management of colorectal cancer. For patients with early …