Development and validation of a model to predict perioperative mortality following heart transplantation in the UK

2004 ◽  
Vol 23 (2) ◽  
pp. S118-S119
Author(s):  
J.S Ganesh ◽  
C.A Rogers ◽  
N.R Banner ◽  
R.S Bonser
Cancers ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 1291
Author(s):  
Seda Camalan ◽  
Hanya Mahmood ◽  
Hamidullah Binol ◽  
Anna Luiza Damaceno Araújo ◽  
Alan Roger Santos-Silva ◽  
...  

Oral cancer/oral squamous cell carcinoma is among the top ten most common cancers globally, with over 500,000 new cases and 350,000 associated deaths every year worldwide. There is a critical need for objective, novel technologies that facilitate early, accurate diagnosis. For this purpose, we have developed a method to classify images as “suspicious” and “normal” by performing transfer learning on Inception-ResNet-V2 and generated automated heat maps to highlight the region of the images most likely to be involved in decision making. We have tested the developed method’s feasibility on two independent datasets of clinical photographic images of 30 and 24 patients from the UK and Brazil, respectively. Both 10-fold cross-validation and leave-one-patient-out validation methods were performed to test the system, achieving accuracies of 73.6% (±19%) and 90.9% (±12%), F1-scores of 97.9% and 87.2%, and precision values of 95.4% and 99.3% at recall values of 100.0% and 81.1% on these two respective cohorts. This study presents several novel findings and approaches, namely the development and validation of our methods on two datasets collected in different countries showing that using patches instead of the whole lesion image leads to better performance and analyzing which regions of the images are predictive of the classes using class activation map analysis.


2018 ◽  
Vol 37 (4) ◽  
pp. 441-450 ◽  
Author(s):  
Christopher S. Almond ◽  
Helena Hoen ◽  
Joseph W. Rossano ◽  
Chesney Castleberry ◽  
Scott R. Auerbach ◽  
...  

2003 ◽  
Vol 31 (2) ◽  
pp. 207-212
Author(s):  
Sylvia Vaughan

The Animal Welfare Advisory Committee (AWAC) was established in July 1996, to consider the care, welfare and use of animals involved in procedures for defence research purposes at Defence and Evaluation Research Agency (DERA) establishments in the UK. Two of the objectives of AWAC are to examine the broad trends in animal use at DERA establishments, and to implement and audit the application of the Three Rs principle. AWAC's sixth report addressed the period from 31 October 2000 to 28 February 2002. The statistics of animal use within the report are briefly examined, and some of the actions undertaken by defence research establishments to facilitate the application of the Three Rs are highlighted. It is recommended that, if possible (subject to security constraints), figures detailing the severity of the procedures undertaken should be included in future issues of the report, in order to provide a more-detailed account. It is concluded that Defence Science and Technology Laboratory establishments have made a contribution to the Three Rs, and that other establishments may be able to incorporate some of their actions into their own research programmes. There was an overall 36% increase in the number of procedures carried out by defence research establishments between 1995 and 2000, from 8,900 to 12,065. This probably reflects alterations in the research programme, which is, in turn, decided primarily by the Ministry of Defence's customers and the progress made with previous research programmes. It is therefore recommended that the UK Government allocates significantly more financial resources for the development and validation of alternatives, in order to maximise the potential for achieving the Three Rs in defence research, and to complement the existing initiatives within the defence research industry.


1999 ◽  
Vol 31 (6) ◽  
pp. 2509-2510 ◽  
Author(s):  
C Espinoza ◽  
N Manito ◽  
E Castells ◽  
R Rodriguez ◽  
M.C Octavio de Toledo ◽  
...  

BMJ ◽  
2011 ◽  
Vol 342 (may05 2) ◽  
pp. d2483-d2483 ◽  
Author(s):  
G. A. MacGowan ◽  
G. Parry ◽  
S. Schueler ◽  
A. Hasan
Keyword(s):  

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