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 …

Survival improves when cancer is detected early. However,~ 50% of cancers are at an
advanced stage when diagnosed. Early detection of cancer or precancerous change allows …

Historically, studies of disseminated tumour cells in bone marrow and circulating tumour
cells in peripheral blood have provided crucial insights into cancer biology and the …

The field of machine learning (ML) is sufficiently young that it is still expanding at an
accelerating pace, lying at the crossroads of computer science and statistics, and at the core …

Artificial intelligence (AI) is the use of mathematical algorithms to mimic human cognitive
abilities and to address difficult healthcare challenges including complex biological …

Cell-free DNA (cfDNA) analysis represents a promising method for the diagnosis, treatment
selection and clinical follow-up of cancer patients. Although its general methodological …

Liquid biopsies (LBs), particularly using circulating tumor DNA (ctDNA), are expected to
revolutionize precision oncology and blood-based cancer screening. Recent technological …

The development of artificial intelligence (AI) algorithms has permeated the medical field
with great success. The widespread use of AI technology in diagnosing and treating several …

Background: Endometriosis diagnosis constitutes a considerable economic burden for the
healthcare system with diagnostic tools often inconclusive with insufficient accuracy. We …

Widespread adaptation of liquid biopsy for the early detection of cancer has yet to reach
clinical utility. Circulating tumor DNA is commonly detected though the presence of genetic …