The rapid development of precision medicine in recent years has started to challenge
diagnostic pathology with respect to its ability to analyze histological images and …

Machine learning models are poised to make a transformative impact on chemical sciences
by dramatically accelerating computational algorithms and amplifying insights available from …

Deep learning approaches to anomaly detection (AD) have recently improved the state of
the art in detection performance on complex data sets, such as large collections of images or …

Cancer of unknown primary (CUP) origin is an enigmatic group of diagnoses in which the
primary anatomical site of tumour origin cannot be determined,. This poses a considerable …

Histomorphology has been a mainstay of cancer diagnosis in anatomic pathology for many
years. DNA methylation profiling is an additional emerging tool that will serve as an adjunct …

The number of publications on deep learning for cancer diagnostics is rapidly increasing,
and systems are frequently claimed to perform comparable with or better than clinicians …

Rational design of compounds with specific properties requires understanding and fast
evaluation of molecular properties throughout chemical compound space—the huge set of …

The success of convolutional neural networks (CNNs) in various applications is
accompanied by a significant increase in computation and parameter storage costs. Recent …

Precision in the diagnosis of diverse central nervous system (CNS) tumor types is crucial for
optimal treatment. DNA methylation profiles, which capture the methylation status of …

The low abundance of circulating tumour DNA (ctDNA) in plasma samples makes the
analysis of ctDNA biomarkers for the detection or monitoring of early-stage cancers …