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

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

(C) Violin plot illustrating the distribution of age of onset across clusters. Each violin plot shows the kernel density estimate of the data, with the center line representing the median age of onset. Box plot elements are overlaid, where the box limits indicate the upper and lower quartiles, and the whiskers extend to 1.5 times the IQR. Individual points are hidden for clarity.

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

JMIR Aging 2025;8:e65178

Acceptability of a Web-Based Health App (PortfolioDiet.app) to Translate a Nutrition Therapy for Cardiovascular Disease in High-Risk Adults: Mixed Methods Randomized Ancillary Pilot Study

Acceptability of a Web-Based Health App (PortfolioDiet.app) to Translate a Nutrition Therapy for Cardiovascular Disease in High-Risk Adults: Mixed Methods Randomized Ancillary Pilot Study

Several recent Canadian population-based studies have shown that many patients at high CVD risk continue to have low-density lipoprotein cholesterol (LDL-C) levels well above the guideline targets [2,3]. LDL-C has been extensively studied and described as a causal factor for CVD [4]. LDL-C levels above the target can result from multiple factors such as insufficient LDL-C lowering with statins, statin-related side effects, suboptimal medication adherence, and treatment inertia [5].

Meaghan E Kavanagh, Laura Chiavaroli, Selina M Quibrantar, Gabrielle Viscardi, Kimberly Ramboanga, Natalie Amlin, Melanie Paquette, Sandhya Sahye-Pudaruth, Darshna Patel, Shannan M Grant, Andrea J Glenn, Sabrina Ayoub-Charette, Andreea Zurbau, Robert G Josse, Vasanti S Malik, Cyril W C Kendall, David J A Jenkins, John L Sievenpiper

JMIR Cardio 2025;9:e58124

Biases in Race and Ethnicity Introduced by Filtering Electronic Health Records for “Complete Data”: Observational Clinical Data Analysis

Biases in Race and Ethnicity Introduced by Filtering Electronic Health Records for “Complete Data”: Observational Clinical Data Analysis

Available percentage of patients’ data upon individually applying all 19 filters in different ethnic subgroups in (A) the Cedars-Sinai dataset, (B) the CUIMC dataset, and (C) the Ao U dataset. The filters are in descending order following the available percentage of the category, all. The points are connected to ease the visualization, but the filters are not cumulative. Stacked bar plots show the ethnicity distribution of the datasets in percentages.

Jose Miguel Acitores Cortina, Yasaman Fatapour, Kathleen LaRow Brown, Undina Gisladottir, Michael Zietz, Oliver John Bear Don't Walk IV, Danner Peter, Jacob S Berkowitz, Nadine A Friedrich, Sophia Kivelson, Aditi Kuchi, Hongyu Liu, Apoorva Srinivasan, Kevin K Tsang, Nicholas P Tatonetti

JMIR Med Inform 2025;13:e67591

Treatment of Substance Use Disorders With a Mobile Phone App Within Rural Collaborative Care Management (Senyo Health): Protocol for a Mixed Methods Randomized Controlled Trial

Treatment of Substance Use Disorders With a Mobile Phone App Within Rural Collaborative Care Management (Senyo Health): Protocol for a Mixed Methods Randomized Controlled Trial

Panel (C) shows a behavioral activation task, and panel (D) showcases the points awarded for completing this task. Senyo Health chat feature being displayed from the perspective of the recovery coach. The left is conversations with multiple patients. Once selected, the full conversation appears in the center of the screen, with the recovery coach able to text back and forth. Surveys, modules, and activation tasks can also be assigned to the participant through the chat.

Tyler S Oesterle, Nicholas L Bormann, Margaret M Paul, Scott A Breitinger, Benjamin Lai, Jamie L Smith, Cindy J Stoppel, Stephan Arndt, Mark D Williams

JMIR Res Protoc 2025;14:e65693