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Impact of a 6-Week Postpartum Text Messaging Program (Essential Coaching for Every Mother) at 6 Months: Follow-Up Study to a Randomized Controlled Trial

Justine Dol, Marsha Campbell-Yeo, Megan Aston, Douglas McMillan, Amy K Grant

JMIR Pediatr Parent 2025;8:e62841

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Impact of a Symptom Checker App on Patient-Physician Interaction Among Self-Referred Walk-In Patients in the Emergency Department: Multicenter, Parallel-Group, Randomized, Controlled Trial

Malte L Schmieding, Marvin Kopka, Myrto Bolanaki, Hendrik Napierala, Maria B Altendorf, Doreen Kuschick, Sophie K Piper, Lennart Scatturin, Konrad Schmidt, Claudia Schorr, Alica Thissen, Cornelia Wäscher, Christoph Heintze, Martin Möckel, Felix Balzer, Anna Slagman

J Med Internet Res 2025;27:e64028

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Assessment and Intervention for Diabetes Distress in Primary Care Using Clinical and Technological Interventions: Protocol for a Single-Arm Pilot Trial

Marisa Kostiuk, Susan L Moore, E Seth Kramer, Joshua Felton Gilens, Ashwin Sarwal, David Saxon, John F Thomas, Tamara K Oser

JMIR Res Protoc 2025;14:e62916

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Unsupervised Deep Learning of Electronic Health Records to Characterize Heterogeneity Across Alzheimer Disease and Related Dementias: Cross-Sectional Study

Alternative methods, such as K-means, Gaussian mixture models [40], and density-based spatial clustering of applications with noise (DBSCAN) [41], face theoretical limitations: K-means assumes spherical clusters that is difficult to satisfy in high-dimensional embeddings; DBSCAN relies on density thresholds that break down in such spaces; and Gaussian mixture models can be unstable with overlapping subtypes.

Matthew West, You Cheng, Yingnan He, Yu Leng, Colin Magdamo, Bradley T Hyman, John R Dickson, Alberto Serrano-Pozo, Deborah Blacker, Sudeshna Das