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Automatic Human Embryo Volume Measurement in First Trimester Ultrasound From the Rotterdam Periconception Cohort: Quantitative and Qualitative Evaluation of Artificial Intelligence

Automatic Human Embryo Volume Measurement in First Trimester Ultrasound From the Rotterdam Periconception Cohort: Quantitative and Qualitative Evaluation of Artificial Intelligence

The data used for this study was collected within the Rotterdam Periconception Cohort (Predict Study). The Rotterdam Periconception Cohort is an ongoing prospective tertiary hospital–based cohort conducted since November 2010 at the Department of Obstetrics and Gynecology of the Erasmus MC, University Medical Center, Rotterdam, The Netherlands [27,28]. The included women were at least 18 years old, with an ongoing singleton pregnancy of less than 10 weeks GA.

Wietske A P Bastiaansen, Stefan Klein, Batoul Hojeij, Eleonora Rubini, Anton H J Koning, Wiro Niessen, Régine P M Steegers-Theunissen, Melek Rousian

J Med Internet Res 2025;27:e60887

Effect of a Telemedicine Model on Patients With Heart Failure With Reduced Ejection Fraction in a Resource-Limited Setting in Vietnam: Cohort Study

Effect of a Telemedicine Model on Patients With Heart Failure With Reduced Ejection Fraction in a Resource-Limited Setting in Vietnam: Cohort Study

This prospective cohort study was conducted at the Vietnam National Heart Institute (VNHI), Bach Mai Hospital, Hanoi, Vietnam. Between January 2023 and October 2023, the study recruited 2 cohorts of patients managed and monitored in the outpatient department at VNHI. One cohort consisted of patients who received remote monitoring and management (telemedicine model), while the second cohort received standard monitoring and management (usual care model).

Hoai Thi Thu Nguyen, Hieu Ba Tran, Phuong Minh Tran, Hung Manh Pham, Co Xuan Dao, Thanh Ngoc Le, Loi Doan Do, Ha Quoc Nguyen, Thom Thi Vu, James Kirkpatrick, Christopher Reid, Dung Viet Nguyen

J Med Internet Res 2025;27:e67228

Digital Assessment of Cognitive Health in Outpatient Primary Care: Usability Study

Digital Assessment of Cognitive Health in Outpatient Primary Care: Usability Study

After assessments were completed for the entire cohort, all PCPs involved in the study completed a provider feedback survey sent by email and completed an interview assessing their impressions of the CCE. After completion of the CCE, results were immediately uploaded into the Linus Health portal.

Adam J Doerr, Taylor A Orwig, Matthew McNulty, Stephanie Denise M Sison, David R Paquette, Robert Leung, Huitong Ding, Stephen B Erban, Bruce R Weinstein, Yurima Guilarte-Walker, Adrian H Zai, Allan J Walkey, Apurv Soni, David D McManus, Honghuang Lin

JMIR Form Res 2025;9:e66695

Assessing the Data Quality Dimensions of Partial and Complete Mastectomy Cohorts in the All of Us Research Program: Cross-Sectional Study

Assessing the Data Quality Dimensions of Partial and Complete Mastectomy Cohorts in the All of Us Research Program: Cross-Sectional Study

The framework comprises 5 mutually exclusive and parsimonious dimensions that can be operationalized and applied to a mastectomy cohort as primary outcome variables: conformance, completeness, concordance, plausibility, and temporality. A prior study applied these dimensions to a ductal carcinoma in situ cohort data quality analysis [17]. Concomitantly, we evaluated the application of the DQD framework to a mastectomy cohort.

Matthew Spotnitz, John Giannini, Yechiam Ostchega, Stephanie L Goff, Lakshmi Priya Anandan, Emily Clark, Tamara R Litwin, Lew Berman

JMIR Cancer 2025;11:e59298

Real-World Insights Into Dementia Diagnosis Trajectory and Clinical Practice Patterns Unveiled by Natural Language Processing: Development and Usability Study

Real-World Insights Into Dementia Diagnosis Trajectory and Clinical Practice Patterns Unveiled by Natural Language Processing: Development and Usability Study

The study cohort was defined as patients who met the following criteria: (1) received a dementia diagnosis, (2) had at least one outpatient visit per year, (3) had at least one visit before the dementia diagnosis, and (4) had documented memory loss–related symptoms (eg, memory loss, confusion, cognition impairment, trouble remembering, not recalling, forgetting, and blackout) in the EHR.

Hunki Paek, Richard H Fortinsky, Kyeryoung Lee, Liang-Chin Huang, Yazeed S Maghaydah, George A Kuchel, Xiaoyan Wang

JMIR Aging 2025;8:e65221

Changing User Experience of Wearable Activity Monitors Over 7 Years: Repeat Cross-Sectional Survey Study

Changing User Experience of Wearable Activity Monitors Over 7 Years: Repeat Cross-Sectional Survey Study

The use of multivariable analysis methods would have enabled examination of the effects of these cohort differences but was not possible due to the unavailability of the individual-level data from the 2016 survey. We conducted our analyses using the summary data available, which still offers valuable insights into the trends and changes over time. Another limitation of the study includes the presence of numerous internet bots from MTurk that had completed the 2023 survey.

Darcy Beckett, Rachel Curtis, Kimberley Szeto, Carol Maher

J Med Internet Res 2025;27:e56251

Assessing the Impact of Distance Traveled and Birth Volumes of Hospital Maternity Units on Newborn Outcomes: Population-Based Cohort Study

Assessing the Impact of Distance Traveled and Birth Volumes of Hospital Maternity Units on Newborn Outcomes: Population-Based Cohort Study

In this study, we conducted a population-based cohort study in Lombardy, the largest and most populous region of Italy, to investigate the singular and combined effects of HMU volumes and RTD on specific outcomes in births occurring in hospitals without intensive care units (ICUs). Additionally, we studied the influence of perinatal factors like antenatal care (ANC) and sociodemographic features of the mothers.

Anna Cantarutti, Riccardo Boracchini, Roberto Bellù, Raffaella Ronco, Federico Rea, Anna Locatelli, Rinaldo Zanini, Giovanni Corrao

JMIR Public Health Surveill 2025;11:e58944

Personalized Mobile App–Based Program for Preparation and Recovery After Radical Prostatectomy: Initial Evidence for Improved Outcomes From a Prospective Nonrandomized Study

Personalized Mobile App–Based Program for Preparation and Recovery After Radical Prostatectomy: Initial Evidence for Improved Outcomes From a Prospective Nonrandomized Study

Data for cohort A were collected from January 2023 to early July 2023, when the intervention with the betty.care app was introduced. Data for cohort B were collected from July 2023 to November 2023. The overall cohort included all consecutive RP patients before and after the implementation of the mobile app program. Surgeons enrolling patients in the study complete 3 of 4 robotic operations per week.

Alberto Martini, Claudia Kesch, Alae Touzani, Giorgio Calleris, Bogdan Buhas, Rawad Abou-Zahr, Razvan-George Rahota, Benjamin Pradère, Christophe Tollon, Jean-Baptiste Beauval, Guillaume Ploussard

J Med Internet Res 2024;26:e55429

SARS-CoV-2 Infection Risk by Vaccine Doses and Prior Infections Over 24 Months: ProHEpiC-19 Longitudinal Study

SARS-CoV-2 Infection Risk by Vaccine Doses and Prior Infections Over 24 Months: ProHEpiC-19 Longitudinal Study

Another study analyzed the severity of reinfections in a cohort of health care workers [17]. A recent review found that studies tended to focus on the characteristics and risk factors of SARS-Co V-2 reinfection, particularly during the Omicron wave, but did not compare the severity of reinfection and primary infection before vaccine availability. This review suggested that reinfections are generally milder than primary infections, with lower viral loads and fewer self-reported symptoms.

Pere Torán-Monserrat, Noemí Lamonja-Vicente, Anna Costa-Garrido, Lucía A Carrasco-Ribelles, Bibiana Quirant, Marc Boigues, Xaviera Molina, Carla Chacón, Rosalia Dacosta-Aguayo, Fernando Arméstar, Eva María Martínez Cáceres, Julia G Prado, Concepción Violán, ProHEpiC-19 study group

JMIR Public Health Surveill 2024;10:e56926

Development and Validation of Deep Learning–Based Infectivity Prediction in Pulmonary Tuberculosis Through Chest Radiography: Retrospective Study

Development and Validation of Deep Learning–Based Infectivity Prediction in Pulmonary Tuberculosis Through Chest Radiography: Retrospective Study

The cohort comprised patients who met the following criteria: (1) first PTB diagnosis between January 2004 and June 2023, (2) underwent sputum examinations, (3) CXR performed within –60 to +180 days from the initial diagnosis date, (4) at least 1 positive sputum sample (smear or culture), and (5) received a successful 6-month treatment course (no treatment after the seventh month).

Wou young Chung, Jinsik Yoon, Dukyong Yoon, Songsoo Kim, Yujeong Kim, Ji Eun Park, Young Ae Kang

J Med Internet Res 2024;26:e58413