Deep learning models have recently attracted great interest as an effective solution to the
challenging problem of human activity recognition (HAR) and its widespread applications in …

The bovine respiratory disease complex (BRDC) is caused by a variety of pathogens, as
well as contributing environmental and host-related risk factors. BRDC is the costliest …

Intratumoral heterogeneity can wreak havoc on current precision medicine strategies
because of challenges in sufficient sampling of geographically separated areas of …

Early detection is critical for successfully diagnosing cancer, and timely analysis of
diagnostic tests is increasingly important. In the context of neuroendocrine tumors, the Ki-67 …

The convergence of digital pathology and artificial intelligence could assist histopathology
image analysis by providing tools for rapid, automated morphological analysis. This …

Aims Deep-learning methods for scoring biomarkers are an active research topic. However,
the superior performance of many studies relies on large datasets collected from clinical …

Deep learning has proven to be capable of automating key aspects of histopathologic
analysis, but its continual reliance on large expert-annotated training datasets hinders …

Классическая лимфома Ходжкина (ЛХ) представляет собой уникальное
злокачественное новообразование лимфатической системы, характеризующееся …

With image analysis as the core for multitarget detection and intelligent tracking, mostly
applying the Faster R‐CNN or YOLO framework, the MOTA score for multitarget tracking is …