Metasurfaces, interacted with artificial intelligence, have now been motivating many
contemporary research studies to revisit established fields, eg, direction of arrival (DOA) …

In the last decades, the development of high‐throughput molecular assays has
revolutionised cancer diagnostics, paving the way for the concept of personalised cancer …

Simple Summary Ampullary tumors are rare malignancies of the upper gastrointestinal tract.
Histologic, immunohistochemical and, most recently, genomic biomarkers have been used …

Background In∼ 3%-5% of patients with metastatic disease, tumor origin remains unknown
despite modern imaging techniques and extensive pathology work-up. With long diagnostic …

Purpose: The clinical behavior of ampullary adenocarcinoma varies widely. Targeted tumor
sequencing may better define biologically distinct subtypes to improve diagnosis and …

Purpose: Intrahepatic cholangiocarcinoma (IHC) is a heterogeneous tumor. The hidden-
genome classifier, a supervised machine learning–based algorithm, was used to quantify …

Importance Ampullary adenocarcinoma (AA) is characterized by clinical and genomic
heterogeneity. A previously developed genomic classifier defined biologically distinct …

Abstract In oncology, Deep Learning has shown great potential to personalise tasks such as
tumour type classification, based on per-patient omics data-sets. Being high dimensional …

Inferring the cancer-type specificities of ultra-rare, genome-wide somatic mutations is an
open problem. Traditional statistical methods cannot handle such data due to their ultra-high …

Numerous studies over the past generation have identified germline variants that increase
specific cancer risks. Simultaneously, a revolution in sequencing technology has permitted …