scholarly journals Peer Review #1 of "Description and classification of bivalve mollusks hemocytes: a computational approach (v0.1)"

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Eliada Pampoulou ◽  
Donald R. Fuller

PurposeWhen the augmentative and alternative communication (ACC) model (Lloyd et al., 1990) was proposed, these components of symbols were not considered, nor were they contemplated when superordinate (Lloyd and Fuller, 1986) and subordinate levels (Fuller et al., 1992) of AAC symbol taxonomy were developed. The purpose of this paper is to revisit the ACC model and propose a new symbol classification system called multidimensional quaternary symbol continuum (MQSC)Design/methodology/approachThe field of AAC is evolving at a rapid rate in terms of its clinical, social, research and theoretical underpinnings. Advances in assessment and intervention methods, technology and social issues are all responsible to some degree for the significant changes that have occurred in the field of AAC over the last 30 years. For example, the number of aided symbol collections has increased almost exponentially over the past couple of decades. The proliferation of such a large variety of symbol collections represents a wide range of design attributes, physical attributes and linguistic characteristics for aided symbols and design attributes and linguistic characteristics for unaided symbols.FindingsTherefore, it may be time to revisit the AAC model and more specifically, one of its transmission processes referred to as the means to represent.Originality/valueThe focus of this theoretical paper then, is on the current classification of symbols, issues with respect to the current classification of symbols in terms of ambiguity of terminology and the evolution of symbols, and a proposal for a new means of classifying the means to represent.Peer reviewThe peer review history for this article is available at: https://publons.com/publon10.1108/JET-04-2021-0024


2018 ◽  
Vol 69 (4) ◽  
pp. 409-416 ◽  
Author(s):  
Csilla Egri ◽  
Kathryn E. Darras ◽  
Elena P. Scali ◽  
Alison C. Harris

Peer review for radiologists plays an important role in identifying contributing factors that can lead to diagnostic errors and patient harm. It is essential that all radiologists be aware of the multifactorial causes of diagnostic error in radiology and the methods available to reduce it. This pictorial review provides readers with an overview of common errors that occur in abdominal radiology and strategies to reduce them. This review aims to make readers more aware of pitfalls in abdominal imaging so that these errors can be avoided in the future. This essay also provides a systematic approach to classifying abdominal imaging errors that will be of value to all radiologists participating in peer review.


2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Fabio Zanini ◽  
Bojk A. Berghuis ◽  
Robert C. Jones ◽  
Benedetta Nicolis di Robilant ◽  
Rachel Yuan Nong ◽  
...  

Abstract Single cell transcriptomics is revolutionising our understanding of tissue and disease heterogeneity, yet cell type identification remains a partially manual task. Published algorithms for automatic cell annotation are limited to known cell types and fail to capture novel populations, especially cancer cells. We developed northstar, a computational approach to classify thousands of cells based on published data within seconds while simultaneously identifying and highlighting new cell states such as malignancies. We tested northstar on data from glioblastoma, melanoma, and seven different healthy tissues and obtained high accuracy and robustness. We collected eleven pancreatic tumors and identified three shared and five private neoplastic cell populations, offering insight into the origins of neuroendocrine and exocrine tumors. Northstar is a useful tool to assign known and novel cell type and states in the age of cell atlases.


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