https://ogma.newcastle.edu.au/vital/access/ /manager/Index ${session.getAttribute("locale")} 5 https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:44235 Wed 28 Jun 2023 11:00:19 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:53802 Tue 16 Jan 2024 14:51:48 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:55150 Tue 16 Apr 2024 15:25:36 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:50991 Tue 15 Aug 2023 09:50:57 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:31893 Tue 10 Apr 2018 10:47:16 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:50338 .8) for most normal cell types and did not require any manual reassignment. The AI digital differential was less reliable for abnormal blood films (r = .50-.87), but could be greatly improved by manual assessment of digital images for most cell types (r > .95) with the exception of immature granulocytes (r = .62). For blast identification, initial AI digital differentials showed 96% sensitivity and 25% specificity, which was improved to 99% and 84%, respectively, after manual digital review.Conclusions: The Techcyte platform allowed remote viewing and manual analysis of digitized slides that was comparable to microscopy. The AI software produced adequate WBC differentials for normal films and had high sensitivity for blast identification in malignant films.]]> Thu 20 Jul 2023 11:18:11 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:28736 Sat 24 Mar 2018 07:35:38 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:27237 Sat 24 Mar 2018 07:29:12 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:31891 Fri 06 Apr 2018 11:33:24 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:30563 Fri 03 Dec 2021 10:32:15 AEDT ]]>