Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Joram Posma"'
Autor:
Jennifer F. Barcroft, Kristofer Linton-Reid, Chiara Landolfo, Maya Al-Memar, Nina Parker, Chris Kyriacou, Maria Munaretto, Martina Fantauzzi, Nina Cooper, Joseph Yazbek, Nishat Bharwani, Sa Ra Lee, Ju Hee Kim, Dirk Timmerman, Joram Posma, Luca Savelli, Srdjan Saso, Eric O. Aboagye, Tom Bourne
Publikováno v:
npj Precision Oncology, Vol 8, Iss 1, Pp 1-10 (2024)
Abstract Ultrasound-based models exist to support the classification of adnexal masses but are subjective and rely upon ultrasound expertise. We aimed to develop an end-to-end machine learning (ML) model capable of automating the classification of ad
Externí odkaz:
https://doaj.org/article/92b75ac45e804737b72f77c54a6be285
Autor:
Nicholas Penney, Derek Yeung, Isabel Garcia-Perez, Joram POSMA, Aleksandra Kopytek, Bethany Garratt, Hutan Ashrafian, Gary Frost, Julian Marchesi, Sanjay Purkayastha, Lesley Hoyles, Ara Darzi, Elaine Holmes
Resolution of type-2 diabetes (T2D) is common following bariatric surgery, particularly Roux-en-Y gastric bypass (RYGB). However, the underlying mechanisms have not been fully elucidated. To address this we compared the integrated serum, urine and fa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6ca52f00653520b77b842c0813def541
https://doi.org/10.21203/rs.3.rs-1146471/v1
https://doi.org/10.21203/rs.3.rs-1146471/v1
Autor:
Joram Posma, John Lindon
The nature of metabolic phenotyping data, where typically more variables are measured than samples are available, requires careful application of statistical methods in order to be able to make meaningful inferences from the data. This chapter descri
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4924a387a1f789d32c11cf72665a72d2
https://doi.org/10.1016/b978-0-12-812293-8.00009-8
https://doi.org/10.1016/b978-0-12-812293-8.00009-8