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Comparison of Deep Learning Approaches Using Chest Radiographs for Predicting Clinical Deterioration: Retrospective Observational Study

Comparison of Deep Learning Approaches Using Chest Radiographs for Predicting Clinical Deterioration: Retrospective Observational Study

All adult patients (age ≥18 years) hospitalized at the University of Wisconsin Health System (UW Health) between 2009 and 2020 with an elevated e CART score ≥93 (which is the threshold used in clinical practice at UW Health) on the medical-surgical wards were eligible for inclusion in this retrospective cohort study.

Mahmudur Rahman, Jifan Gao, Kyle A Carey, Dana P Edelson, Askar Afshar, John W Garrett, Guanhua Chen, Majid Afshar, Matthew M Churpek

JMIR AI 2025;4:e67144

Augmenting Insufficiently Accruing Oncology Clinical Trials Using Generative Models: Validation Study

Augmenting Insufficiently Accruing Oncology Clinical Trials Using Generative Models: Validation Study

Furthermore, our retrospective analysis was limited to 9 clinical trials that were actually completed. Studies that do not reach accrual targets may have different characteristics, which could lead to different results. While our results are encouraging based on a retrospective analysis, future work should evaluate this approach through a prospective design. When the r value increases, the available dataset size to train a generative model decreases.

Samer El Kababji, Nicholas Mitsakakis, Elizabeth Jonker, Ana-Alicia Beltran-Bless, Gregory Pond, Lisa Vandermeer, Dhenuka Radhakrishnan, Lucy Mosquera, Alexander Paterson, Lois Shepherd, Bingshu Chen, William Barlow, Julie Gralow, Marie-France Savard, Christian Fesl, Dominik Hlauschek, Marija Balic, Gabriel Rinnerthaler, Richard Greil, Michael Gnant, Mark Clemons, Khaled El Emam

J Med Internet Res 2025;27:e66821

Comparative Effectiveness of Wearable Devices and Built-In Step Counters in Reducing Metabolic Syndrome Risk in South Korea: Population-Based Cohort Study

Comparative Effectiveness of Wearable Devices and Built-In Step Counters in Reducing Metabolic Syndrome Risk in South Korea: Population-Based Cohort Study

This retrospective cohort study examined changes in walking routines, health behavior patterns, and metabolic syndrome risk factors among participants who either continued using a wearable activity tracker or switched to a smartphone’s built-in step counter after 12 weeks of the program. The study group comprised individuals with at least 1 metabolic syndrome risk factor who switched from a wearable activity tracker to their smartphone’s built-in step counter after 12 weeks.

Kyung-In Joung, Sook Hee An, Joon Seok Bang, Kwang Joon Kim

JMIR Mhealth Uhealth 2025;13:e64527

Correlation Between Objective Habit Metrics and Objective Medication Adherence: Retrospective Study of 15,818 Participants From Clinical Studies

Correlation Between Objective Habit Metrics and Objective Medication Adherence: Retrospective Study of 15,818 Participants From Clinical Studies

This study was a retrospective cohort study. AARDEX Group’s database, the Medication Event Monitoring System (MEMS; AARDEX Group) Adherence Knowledge Center was used as the data source. This database contains anonymized electronic medication adherence data from ambulant participants enrolled in clinical studies that ran between 1989 and 2016. These participants’ medication adherence was electronically monitored using the MEMS.

Antoine Pironet, L Alison Phillips, Bernard Vrijens

Interact J Med Res 2025;14:e63987

Effectiveness of Remote Patient Monitoring Equipped With an Early Warning System in Tertiary Care Hospital Wards: Retrospective Cohort Study

Effectiveness of Remote Patient Monitoring Equipped With an Early Warning System in Tertiary Care Hospital Wards: Retrospective Cohort Study

To this end, a retrospective analysis was conducted to evaluate its effectiveness in identifying patient deterioration. The performance of R-EWS was also benchmarked against simulated versions of MEWS (S-MEWS) and the ICU’s continuous threshold-based alert system (S-Threshold).

Pavithra Lakshman, Priyanka T Gopal, Sheen Khurdi

J Med Internet Res 2025;27:e56463

Leveraging Machine Learning to Identify Subgroups of Misclassified Patients in the Emergency Department: Multicenter Proof-of-Concept Study

Leveraging Machine Learning to Identify Subgroups of Misclassified Patients in the Emergency Department: Multicenter Proof-of-Concept Study

We conducted a multicenter retrospective cohort study at the main ED at Haukeland University Hospital, Bergen, and St. Olav’s University Hospital in Trondheim, Norway. Haukeland University Hospital functions as a referral center for about a million inhabitants in the Bergen metropolitan area [10] and had an annual ED admission ranging from 33,000 to 38,000 during the study period.

Sage Wyatt, Dagfinn Lunde Markussen, Mounir Haizoune, Anders Strand Vestbø, Yeneabeba Tilahun Sima, Maria Ilene Sandboe, Marcus Landschulze, Hauke Bartsch, Christopher Martin Sauer

J Med Internet Res 2024;26:e56382

Association Between Patient Portal Engagement and Weight Loss Outcomes in Patients After Bariatric Surgery: Longitudinal Observational Study Using Electronic Health Records

Association Between Patient Portal Engagement and Weight Loss Outcomes in Patients After Bariatric Surgery: Longitudinal Observational Study Using Electronic Health Records

A full waiver of written informed consent from patients was granted by the IRB because this study is retrospective with minimal risks to patients and the study data are deidentified. This study follows the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) reporting guideline.

Xinmeng Zhang, Kaidi Kang, Chao Yan, Yubo Feng, Simon Vandekar, Danxia Yu, S Trent Rosenbloom, Jason Samuels, Gitanjali Srivastava, Brandon Williams, Vance L Albaugh, Wayne J English, Charles R Flynn, You Chen

J Med Internet Res 2024;26:e56573

Whole-Body Cryotherapy Reduces Systemic Inflammation in Healthy Adults: Pilot Cohort Study

Whole-Body Cryotherapy Reduces Systemic Inflammation in Healthy Adults: Pilot Cohort Study

Reference 13: The healthspan project: a retrospective pilot of biomarkers and biometric outcomes afterretrospective

Elizabeth Chun, Richard Joseph, Rachele Pojednic

Interact J Med Res 2024;13:e60942

Peer Review for “Identification of COVID-19–Associated Hepatitis in Children as an Emerging Complication in the Wake of SARS-CoV-2 Infections: Ambispective Observational Study”

Peer Review for “Identification of COVID-19–Associated Hepatitis in Children as an Emerging Complication in the Wake of SARS-CoV-2 Infections: Ambispective Observational Study”

Acute severe non-A-E-hepatitis of unknown origin in children – a 30-year retrospective observational study from north-west Germany. J Hepatol. May 2023;78(5):971-978. [doi: 10.1016/j.jhep.2022.12.012] [Medline: 36572350] Coccia M. How do low wind speeds and high levels of air pollution support the spread of COVID-19? Atmos Pollut Res. Jan 2021;12(1):437-445. [doi: 10.1016/j.apr.2020.10.002] [Medline: 33046960] Cooper S, Waisbourd-Zinman O.

Mario Coccia

JMIRx Med 2024;5:e59596