Results 11 to 20 of about 8,414 (201)
Factors affecting hospital readmission rates following an acute coronary syndrome: A systematic review. [PDF]
Abstract Aim To synthesise quantitative evidence on factors that impact hospital readmission rates following ACS with comorbidities. Design Systematic review and narrative synthesis. Data sources A search of eight electronic databases, including Embase, Medline, PsycINFO, Web of Science, CINAHL, Cochrane Library, Scopus and the Joanna Briggs Institute (
Rashidi A, Whitehead L, Glass C.
europepmc +2 more sources
Validity of Danish public criteria for providing flash glucose monitoring to participants with type 1 diabetes-An explorative cohort study. [PDF]
Use of Flash Glucose Monitoring (FGM) in treatment of diabetes is increasing. We assessed the validity of Danish public institutional criteria for regulatory use of FGM. Our study point out that the seemingly promising current parameters, do not identify the patients with Type 1 diabetes who will benefit from FGM use.
Nielsen IR +2 more
europepmc +2 more sources
X‐ray powder diffraction mapping at multiple length scales revealed the unusual presence of lead(II) formate, Pb(HCOO)2, in several areas of The Night Watch, Rembrandt's most famous painting. A possible chemical pathway resulting in the formation of this compound in historical oil paint was explored via micro‐analysis, notably using synchrotron ...
Victor Gonzalez +11 more
wiley +2 more sources
The prevalence of 30-day readmission after acute myocardial infarction: A systematic review and meta-analysis. [PDF]
Abstract Objective The 30‐day readmission is associated with increased medical costs, which has become an important quality metric in several medical institutions. This current study is aimed at clarifying the prevalence, the underlying risk factors, and reasons of the 30‐day readmission after acute myocardial infarction (AMI). Methods PubMed, Cochrane
Wang H, Zhao T, Wei X, Lu H, Lin X.
europepmc +2 more sources
Abstract Purpose We sought to understand concerns fundamental to planning medical education specific to rural southern African Americans who are virtually nonexistent in American medical schools. Methods A diverse multidisciplinary research team conducted this qualitative study with 3 focus groups, including 17 rural medical educators recruited ...
John R. Wheat +8 more
wiley +1 more source
GrowliFlower: An image time‐series dataset for GROWth analysis of cauLIFLOWER
Abstract In this paper, we present GrowliFlower, a georeferenced, image‐based unmanned aerial vehicle time‐series dataset of two monitored cauliflower fields (0.39 and 0.60 ha) acquired in 2 years, 2020 and 2021. The proposed dataset contains RGB and multispectral orthophotos with coordinates of approximately 14,000 individual cauliflower plants.
Jana Kierdorf +8 more
wiley +1 more source
Mapping and monitoring cluster morphology provides insights for disease risk assessment, quality control in wine production, and understanding environmental influences on cluster shape. During the progression of grapevine morphology, cluster closure (CC) (also called bunch closure) is the stage when berries touch one another.
Manushi Trivedi +7 more
wiley +1 more source
Lesion region segmentation via weakly supervised learning
Background Image‐based automatic diagnosis of field diseases can help increase crop yields and is of great importance. However, crop lesion regions tend to be scattered and of varying sizes, this along with substantial intra‐class variation and small inter‐class variation makes segmentation difficult.
Ran Yi +5 more
wiley +1 more source
How does the EU non‐financial directive affect the assurance market?
Abstract The objective of this paper was to determine the impact produced by Directive 2014/95/EU on companies’ decisions regarding the assurance of non‐financial information statements and the quality parameters under which this service is contracted.
Isabel‐María García‐Sánchez +2 more
wiley +1 more source
End‐to‐End Semantic Leaf Segmentation Framework for Plants Disease Classification
Pernicious insects and plant diseases threaten the food science and agriculture sector. Therefore, diagnosis and detection of such diseases are essential. Plant disease detection and classification is a much‐developed research area due to enormous development in machine learning (ML).
Khalil Khan +4 more
wiley +1 more source

