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Articles by Matthew H. S
Machine learning and Bayesian network analyses identifies associations with insomnia in a national sample of 31,285 treatment-seeking college students | BMC Psychiatry | Full Text
The current study was a secondary analysis of 39,194 treatment-seeking participants across 26 U.S. colleges and universities who participated in screening for an ongoing randomized controlled trial investigating the effectiveness of a transdiagnostic coached mobile mental health intervention that used population-level screening for engaging college students in tailored services for preventing and treating anxiety, depression, and eating disorders (clinicaltrial.gov; ID: NCT04162847).
The pursuit of approaches to federate data to accelerate Alzheimer’s disease and related dementia research: GAAIN, DPUK, and ADDI
Introduction Science is a data-driven economy. Access to high-quality data is the sine qua non of creating knowledge and deriving benefit. Data sharing mandates from journals and funders are now requiring studies to make data accessible (Nature Methods, 2023). However, in the health sciences, data access is challenging.
The pursuit of approaches to federate data to accelerate Alzheimer's disease and related dementia research: GAAIN, DPUK, and ADDI
Arthur W. Toga1*, Mukta Phatak2*, Ioannis Pappas1, Simon Thompson3, Caitlin P. McHugh2, Matthew H.
Frontiers | The European Prevention of Alzheimer's Dementia Programme: An Innovative Medicines Initiative-funded partnership to facilitate secondary prevention of Alzheimer's disease dementia
Introduction Early detection of Alzheimer's disease (AD) pathology offers an opportunity for intervention, either to delay symptom onset or to stop the disease development entirely. Due to the long silent period in the AD pathology where the disease starts developing more than 20 years before traditional symptoms of dementia manifest (1, 2), identifying individuals at risk of dementia in pre-dementia stages is a major aim of many disease-modifying therapies currently developed for AD.
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