Zobrazeno 1 - 10
of 48
pro vyhledávání: '"Parsons, Owen"'
Autor:
Parsons, Owen, Barlow, Nathan E, Baxter, Janie, Paraschin, Karen, Derix, Andrea, Hein, Peter, Dürichen, Robert
The availability of large and deep electronic healthcare records (EHR) datasets has the potential to enable a better understanding of real-world patient journeys, and to identify novel subgroups of patients. ML-based aggregation of EHR data is mostly
Externí odkaz:
http://arxiv.org/abs/2208.01607
Autor:
Javer, Avelino, Parsons, Owen, Carr, Oliver, Baxter, Janie, Diedrich, Christian, Elçi, Eren, Schaper, Steffen, Coboeken, Katrin, Dürichen, Robert
Electronic healthcare records are an important source of information which can be used in patient stratification to discover novel disease phenotypes. However, they can be challenging to work with as data is often sparse and irregularly sampled. One
Externí odkaz:
http://arxiv.org/abs/2112.07239
The increase in availability of longitudinal electronic health record (EHR) data is leading to improved understanding of diseases and discovery of novel phenotypes. The majority of clustering algorithms focus only on patient trajectories, yet patient
Externí odkaz:
http://arxiv.org/abs/2111.06152
Autor:
Parsons, Owen1 (AUTHOR) oep20@cam.ac.uk, Baron-Cohen, Simon1 (AUTHOR) oep20@cam.ac.uk
Publikováno v:
PLoS ONE. 6/2/2023, Vol. 17 Issue 6, p1-21. 21p.
Autor:
Baron-Cohen, Simon, Parsons, Owen
Background We aimed to assess whether autistic individuals were able to generalise across contexts when building statistical expectations of their environment to the same extent as non-autistic individuals. We did this by assessing the implicit aware
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e86d00c0f44de6906862a06fe0f840d5
https://www.repository.cam.ac.uk/handle/1810/350814
https://www.repository.cam.ac.uk/handle/1810/350814
This pilot study compared autistic (N = 15) and non-autistic (N = 19) adults in a systemizing (physics reasoning) task using observational measures of attention, reasoning, and communication. Autistic adults mentioned more non-salient details (autist
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bf06519c55a960974d1ffb1d33af304f
https://www.repository.cam.ac.uk/handle/1810/343143
https://www.repository.cam.ac.uk/handle/1810/343143
Autor:
Jassim, Nazia, Baron-Cohen, Simon, Parsons, Owen, Owen, Adrian M, Lawson, Rebecca P, Smith, Paula, Suckling, John
Publikováno v:
Neuroscience Institute Publications
Funder: Newnham College, University of Cambridge; doi: http://dx.doi.org/10.13039/501100000663
Funder: CIFAR
Funder: NIHR Cambridge Biomedical Research Centre; doi: http://dx.doi.org/10.13039/501100018956
Funder: Autistica; doi: http:/
Funder: CIFAR
Funder: NIHR Cambridge Biomedical Research Centre; doi: http://dx.doi.org/10.13039/501100018956
Funder: Autistica; doi: http:/
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2cb07a1fab889e9621f291f3cdd06257
https://doi.org/10.1038/s41598-022-19640-4
https://doi.org/10.1038/s41598-022-19640-4
Autor:
Leighton B Hinkley, Kensuke eSekihara, Julia Parsons Owen, Kelly eWestlake, Nancy eByl, Srikantan eNagarajan
Publikováno v:
Frontiers in Neurology, Vol 4 (2013)
Resting-state imaging designs are powerful in modeling functional networks in movement disorders because they eliminate task performance related confounds. However, the most common metric for quantifying functional connectivity, i.e. bivariate magnit
Externí odkaz:
https://doaj.org/article/58be05e9533d4030a0525fac7fe03e5f
Publikováno v:
Frontiers in Neuroscience, Vol 6 (2012)
Uncovering brain activity from MEG data requires solving an ill-posed inverse problem, greatly confounded by noise, interference, and correlated sources. Sparse reconstruction algorithms, such as Champagne, show great promise in that they provide foc
Externí odkaz:
https://doaj.org/article/c49217f620d0499ba8609e0645204c78
Publikováno v:
Molecular Autism. 4/12/2017, Vol. 8, p1-12. 12p. 2 Diagrams, 6 Charts, 1 Graph.