Results 121 to 130 of about 496,156 (331)
Molecular Oncology, EarlyView.The LEXOVE prospective study evaluated plasma cell‐free extracellular vesicle (cfEV) dynamics using Bradford assay and dynamic light scattering in metastatic non‐small cell lung cancer patients undergoing first‐line treatments, correlating a ∆cfEV < 20% with improved median progression‐free survival in responders versus non‐responders.
Valerio Gristina +17 more
wiley +1 more source
Efforts estimation of doctors annotating medical image [PDF]
arXiv, 2019 Accurate annotation of medical image is the crucial step for image AI clinical application. However, annotating medical image will incur a great deal of annotation effort and expense due to its high complexity and needing experienced doctors. To alleviate annotation cost, some active learning methods are proposed.
arxiv
A study into annotation ranking metrics in geo-tagged image corpora [PDF]
, 2012 Community contributed datasets are becoming increasingly common in automated image annotation systems. One important issue with community image data is that there is no guarantee that the associated metadata is relevant.
Hughes, Mark +2 more
core
Molecular Oncology, EarlyView.We quantified and cultured circulating tumor cells (CTCs) of 62 patients with various cancer types and generated CTC‐derived tumoroid models from two salivary gland cancer patients. Cellular liquid biopsy‐derived information enabled molecular genetic assessment of systemic disease heterogeneity and functional testing for therapy selection in both ...
Nataša Stojanović Gužvić +31 more
wiley +1 more source
Graph of Concepts for Semantic Annotation of Remotely Sensed Images based on Direct Neighbors in RAG
Canadian Journal of Remote Sensing, 2018 Image annotation is a challenging task and is widely studied in several fields such as image interpretation and retrieval. With the overwhelming volume of image data, manual annotation is no longer practical.
Khitem Amiri, Mohamed Farah
doaj +1 more source
Clearing noisy annotations for computed tomography imaging [PDF]
arXiv, 2018 One of the problems on the way to successful implementation of neural networks is the quality of annotation. For instance, different annotators can annotate images in a different way and very often their decisions do not match exactly and in extreme cases are even mutually exclusive which results in noisy annotations and, consequently, inaccurate ...
arxiv
Suggestive Annotation of Brain Tumour Images with Gradient-guided Sampling [PDF]
arXiv, 2020 Machine learning has been widely adopted for medical image analysis in recent years given its promising performance in image segmentation and classification tasks. As a data-driven science, the success of machine learning, in particular supervised learning, largely depends on the availability of manually annotated datasets.
arxiv
Molecular Oncology, EarlyView.Adaptive ERK reactivation hinders FLT3 tyrosine kinase inhibitor (TKI) treatment in FLT3/ITD acute myeloid leukemia. Here, we report that FLT3 TKI treatment rapidly induces AXL expression and upregulation that is temporally associated with the adaptive ERK reactivation.
Tessa S. Seale +9 more
wiley +1 more source
Open-source tool for eye image annotation
Revista Información Científica, 2022 Introduction: the tracking of the pupil center using videoculography images is widely used for the diagnosis of diseases of the nervous system. The difference between the automatically detected value of the pupil center and the reference value marked by ...
Talía Vázquez-Romaguera +2 more
doaj
Frontiers in Medicine, 2019 The emergence of computational pathology comes with a demand to extract more and more information from each tissue sample. Such information extraction often requires the segmentation of numerous histological objects (e.g., cell nuclei, glands, etc.) in ...
Yves-Rémi Van Eycke +4 more
doaj +1 more source