Family‐centred care interventions for children with chronic conditions: A scoping review
Andrea J. Chow
Ammar Saad
Zobaida Al‐Baldawi
Ryan Iverson
Becky Skidmore
Isabel Jordan
Nicole Pallone
Maureen Smith
Pranesh Chakraborty
Jamie Brehaut
Eyal Cohen
Sarah Dyack
Jane Gillis
Sharan Goobie
Cheryl Greenberg
Robin Hayeems
Brian Hutton
Michal Inbar-Feigenberg
Shailly Jain-Ghai
Sara Khangura … (see 18 more)
Jennifer MacKenzie
John J. Mitchell
Zeinab Moazin
Stuart G. Nicholls
Amy Pender
Chitra Prasad
Andreas Schulze
Komudi Siriwardena
Rebecca N. Sparkes
Kathy N. Speechley
Sylvia Stockler
Monica Taljaard
Mari Teitelbaum
Clara Van Karnebeek
Jagdeep S. Walia
Kumanan Wilson
Beth K. Potter
Children with chronic conditions have greater health care needs than the general paediatric population but may not receive care that centres… (see more) their needs and preferences as identified by their families. Clinicians and researchers are interested in developing interventions to improve family‐centred care need information about the characteristics of existing interventions, their development and the domains of family‐centred care that they address. We conducted a scoping review that aimed to identify and characterize recent family‐centred interventions designed to improve experiences with care for children with chronic conditions.
GrowSpace: A reinforcement learning environment for plant architecture
Yasmeen Hitti
Ionelia Buzatu
Manuel Del Verme
Mark Lefsrud
Florian Golemo
Improving Pediatric Trauma Education by Teaching Non-technical Skills: A Randomized Controlled Trial
Fabio Botelho
Ayla Gerk
Jason M. Harley
Inter- and intra-year forest change detection and monitoring of aboveground biomass dynamics using Sentinel-2 and Landsat
Flavie Pelletier
Michael A. Wulder
Joanne C. White
Txomin Hermosilla
Inter- and intra-year forest change detection and monitoring of aboveground biomass dynamics using Sentinel-2 and Landsat
Flavie Pelletier
Michael A. Wulder
Joanne C. White
Txomin Hermosilla
Inter- and intra-year forest change detection and monitoring of aboveground biomass dynamics using Sentinel-2 and Landsat
Flavie Pelletier
Michael A. Wulder
Joanne C. White
Txomin Hermosilla
Inter- and intra-year forest change detection and monitoring of aboveground biomass dynamics using Sentinel-2 and Landsat
Flavie Pelletier
Michael A. Wulder
Joanne C. White
Txomin Hermosilla
Inter- and intra-year forest change detection and monitoring of aboveground biomass dynamics using Sentinel-2 and Landsat
Flavie Pelletier
Michael A. Wulder
Joanne C. White
Txomin Hermosilla
Linking biodiversity, ecosystem function, and Nature’s contributions to people: a macroecological energy flux perspective
Ana Carolina Antunes
Emilio Berti
Ulrich Brose
Myriam R. Hirt
Dirk N. Karger
Louise M. J. O'Connor
Wilfried Thuiller
Benoit Gauzens
Linking biodiversity, ecosystem function, and Nature's contributions to people: a macroecological energy flux perspective.
Ana Carolina Antunes
Emilio Berti
Ulrich Brose
Myriam R. Hirt
Dirk N. Karger
Louise M. J. O'Connor
Wilfried Thuiller
Benoit Gauzens
Machine Learning Informed Diagnosis for Congenital Heart Disease in Large Claims Data Source
Ariane Marelli
Chao Li
Aihua Liu
Hanh Nguyen
Harry Moroz
James M. Brophy
Liming Guo
Model Collapse Demystified: The Case of Regression
Yunzhen Feng
Julia Kempe
In the era of proliferation of large language and image generation models, the phenomenon of "model collapse" refers to the situation whereb… (see more)y as a model is trained recursively on data generated from previous generations of itself over time, its performance degrades until the model eventually becomes completely useless, i.e the model collapses. In this work, we study this phenomenon in the setting of high-dimensional regression and obtain analytic formulae which quantitatively outline this phenomenon in a broad range of regimes. In the special case of polynomial decaying spectral and source conditions, we obtain modified scaling laws which exhibit new crossover phenomena from fast to slow rates. We also propose a simple strategy based on adaptive regularization to mitigate model collapse. Our theoretical results are validated with experiments.