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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

Various early warning scores (EWS) have been developed to identify the deterioration risk by monitoring different clinical variables, and the implementation of machine-learning EWS, such as the electronic cardiac arrest risk triage (e CART) score, has been associated with improved mortality [3-6]. Current EWS rely on structured data, such as vital signs and laboratory values, to predict clinical deterioration and ignore other data modalities that could potentially enhance prediction accuracy [7].

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

Effects of Using a Smart Bassinet on the Mental Health of Military-Affiliated Pregnant Women: Protocol for a Randomized Controlled Sleep Health and Mood in Newly Expectant Military Mothers (SHINE) Trial

Effects of Using a Smart Bassinet on the Mental Health of Military-Affiliated Pregnant Women: Protocol for a Randomized Controlled Sleep Health and Mood in Newly Expectant Military Mothers (SHINE) Trial

Despite these elevated risks, this segment of our population has been insufficiently evaluated as it pertains to PMAD risk and warrants further attention. It is well appreciated that sleep disturbance is associated with both new and recurrent depressive and anxiety episodes in all populations, especially perinatal women [17-22]. Sleep disturbance often precedes the development of mood disorders [23,24].

Michele L Okun, Jennifer L Payne, Lauren M Osborne, Leilani Feliciano, Andrew Lac

JMIR Res Protoc 2025;14:e66439

Examining a Telemedicine-Based Virtual Reality Clinic in Treating Adults With Specific Phobia: Protocol for a Feasibility Randomized Controlled Efficacy Trial

Examining a Telemedicine-Based Virtual Reality Clinic in Treating Adults With Specific Phobia: Protocol for a Feasibility Randomized Controlled Efficacy Trial

Telemental health care (TMH) has revolutionized mental health services by providing accessible, personalized treatment from the comfort and privacy of home [1,2]. TMH is equally to more effective than in-person care, with patients generally reporting higher satisfaction and reduced costs [3-11]. Furthermore, TMH alleviates sociocultural (eg, stigma) and geographic (eg, transportation) barriers to mental health care [12-14].

Kaitlyn R Schuler, Triton Ong, Brandon M Welch, Jason G Craggs, Brian E Bunnell

JMIR Res Protoc 2025;14:e65770

Association of Social Media Recruitment and Depression Among Racially and Ethnically Diverse Metabolic and Bariatric Surgery Candidates: Prospective Cohort Study

Association of Social Media Recruitment and Depression Among Racially and Ethnically Diverse Metabolic and Bariatric Surgery Candidates: Prospective Cohort Study

Over the past 2 decades, obesity (ie, BMI ≥30 kg/m2) prevalence among adults in the United States has risen from 30.5% to 42.4% [1], and has nearly tripled worldwide [2]. Further, the prevalence of severe obesity (BMI ≥40 kg/m2) has doubled from 4.7% to 9.2% [3]. Non-Hispanic Black (NHB) adults are disproportionately impacted, with an age-adjusted obesity prevalence of 49.9%, followed by Hispanic (45.6%), non-Hispanic White (NHW) (41.4%), and non-Hispanic Asian (16.1%) individuals [3].

Jackson M Francis, Sitapriya S Neti, Dhatri Polavarapu, Folefac Atem, Luyu Xie, Olivia Kapera, Matthew S Mathew, Elisa Marroquin, Carrie McAdams, Jeffrey Schellinger, Sophia Ngenge, Sachin Kukreja, Benjamin E Schneider, Jaime P Almandoz, Sarah E Messiah

JMIR Form Res 2025;9:e58916

Decentralized Biobanking Apps for Patient Tracking of Biospecimen Research: Real-World Usability and Feasibility Study

Decentralized Biobanking Apps for Patient Tracking of Biospecimen Research: Real-World Usability and Feasibility Study

The lack of an efficient market for ensuring the use of donated materials deepens the crisis of faith in public health institutions and has prompted attempts at marketplace solutions [10,11]. We are advancing decentralized biobanking as a software platform predicated on blockchain technology’s democratic ethos, incentive alignment, transparency, and assurances of trust [12].

William Sanchez, Ananya Dewan, Eve Budd, M Eifler, Robert C Miller, Jeffery Kahn, Mario Macis, Marielle Gross

JMIR Bioinform Biotech 2025;6:e70463

Safety and Efficacy of Modular Digital Psychotherapy for Social Anxiety: Randomized Controlled Trial

Safety and Efficacy of Modular Digital Psychotherapy for Social Anxiety: Randomized Controlled Trial

While symptoms do not typically improve in the absence of treatment [5,6], cognitive behavioral therapy for social anxiety (CBT-SA) has been established as an effective treatment with moderate to large effects on social anxiety symptoms [7-9].

Mona M Garvert, Jessica McFadyen, Stuart Linke, Tayla McCloud, Sofie S Meyer, Sandra Sobanska, Paul B Sharp, Alex Long, Quentin J M Huys, Mandana Ahmadi

J Med Internet Res 2025;27:e64138

Identification of Patients With Congestive Heart Failure From the Electronic Health Records of Two Hospitals: Retrospective Study

Identification of Patients With Congestive Heart Failure From the Electronic Health Records of Two Hospitals: Retrospective Study

We used the embeddings from Ro BERTa as our feature matrix with no additional pretraining, as previous studies have shown that Ro BERTa has already been optimized [20]. We did this in three different ways. First, we split the note into sections of up to 512 tokens with each section having a one-sentence overlap. We then took the vector representations of these segments and took the elementwise average to get a feature matrix.

Daniel Sumsion, Elijah Davis, Marta Fernandes, Ruoqi Wei, Rebecca Milde, Jet Malou Veltink, Wan-Yee Kong, Yiwen Xiong, Samvrit Rao, Tara Westover, Lydia Petersen, Niels Turley, Arjun Singh, Stephanie Buss, Shibani Mukerji, Sahar Zafar, Sudeshna Das, Valdery Moura Junior, Manohar Ghanta, Aditya Gupta, Jennifer Kim, Katie Stone, Emmanuel Mignot, Dennis Hwang, Lynn Marie Trotti, Gari D Clifford, Umakanth Katwa, Robert Thomas, M Brandon Westover, Haoqi Sun

JMIR Med Inform 2025;13:e64113

Development of Digital Strategies for Reducing Sedentary Behavior in a Hybrid Office Environment: Modified Delphi Study

Development of Digital Strategies for Reducing Sedentary Behavior in a Hybrid Office Environment: Modified Delphi Study

Recent evidence has highlighted the capability of digital interventions to reduce workplace SB and its associated harmful effects on health and work-related outcomes among office workers [16-18]. However, this research has focused on the traditional office environment, with a dearth of research available on the use of digital interventions to reduce of employees’ SB while working remotely or undertaking hybrid work [19,20].

Iris Parés-Salomón, Cristina Vaqué-Crusellas, Alan Coffey, Bette Loef, Karin I Proper, Anna M Señé-Mir, Anna Puig-Ribera, Kieran P Dowd, Judit Bort-Roig

JMIR Hum Factors 2025;12:e59405