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Optimizing the Postcataract Patient Journey Using AI-Driven Teleconsultation: Prospective Case Study

Joukje C Wanten, Noël J C Bauer, Mohita Chowdhury, Aisling Higham, Nick de Pennington, Frank J H M van den Biggelaar, Rudy M M A Nuijts

JMIR Form Res 2025;9:e72574

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Use of Wearable Sensors to Assess Fall Risk in Neurological Disorders: Systematic Review

Notably, Silva de Lima et al [42] detected fall events automatically using a wearable sensor, without monitoring ADLs or gait. We analyzed features extracted from wearable sensors related to the quantification of supervised or unsupervised motor tasks in patients with MS, PD, or stroke. Several of the studies (10/19, 53%) [35,36,39-41,45,47-49,52] extracted specific gait parameters from wearable sensors.

Mirjam Bonanno, Augusto Ielo, Paolo De Pasquale, Antonio Celesti, Alessandro Marco De Nunzio, Angelo Quartarone, Rocco Salvatore Calabrò

JMIR Mhealth Uhealth 2025;13:e67265

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Promoting Comprehensive Care for People With Rare Diseases in a Tertiary Care Setting in Brazil: Protocol for a Mixed Methods Implementation Study

CIA: Information and Informatics Center; DAS: department of health care; HCRP: Clinics Hospital of Ribeirão Preto (Hospital das Clínicas de Ribeirão Preto); GGA: general outpatient management; PCC: primary care center; RD: rare disease; RG: research group; WG: working group.

Domingos Alves, Filipe Andrade Bernardi, Vinicius Costa Lima, Diego Bettiol Yamada, Tatiana Takahasi Komoto, Michele de Souza Seixas, Victor Cassão, Leticia Fontanelli Straube de Souza, Amaury Lelis Dal Fabbro, Têmis Maria Félix, Ricardo Cavalli, Victor Evangelista de Faria Ferraz

JMIR Res Protoc 2025;14:e68949

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Optimizing and Testing an Individualized and Adaptive Physical Activity Digital Health Intervention: Protocol for a Control Optimization Trial Embedded Within a Randomized Controlled Trial

De-identified data were downloaded for analysis and stored on password-protected servers at the EPARC, with no personally identifiable information was linked to the device-captured data. EPARC servers were accessible only to study staff involved in the measurement of study participants and analysis of study data.

Meelim Kim, Shadia Mansour-Assi, Mohamed El Mistiri, Junghwan Park, Sarasij Banerjee, Owais Khan, Steven De La Torre, Michael Higgins, Job Godino, Kevin Patrick, Camille Nebeker, Sonia Jain, Predrag Klasnja, Daniel E Rivera, Eric Hekler

JMIR Res Protoc 2025;14:e70599

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The Use of Mobile Health Technology and Behavioral Economics to Encourage Adherence to Statins and Blood Pressure–Lowering Medication in Adolescents with Familial Hypercholesterolemia or Hypertension: Protocol for a Pre-Post Cohort Study

Jacob Hartz, Hannah Chiert, Sarah de Ferranti, Tiffany Powell-Wiley

JMIR Res Protoc 2025;14:e65105

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Economic Evaluations and Equity in the Use of Artificial Intelligence in Imaging Examinations for Medical Diagnosis in People With Dermatological, Neurological, and Pulmonary Diseases: Systematic Review

To tackle these challenges, the Brazilian Ministry of Health’s Support Program for the Institutional Development of the Unified Health System (in Portuguese, “Programa de Apoio ao Desenvolvimento Institucional do Sistema Único de Saúde,” known as PROADI-SUS) supports a collaborative project named “Banco de Imagens” (Bank of Images) to create a nationwide cloud-based repository of medical images, as well as to develop and validate AI algorithms to assist in disease diagnosis.

Giulia Osório Santana, Rodrigo de Macedo Couto, Rafael Maffei Loureiro, Brunna Carolinne Rocha Silva Furriel, Luis Gustavo Nascimento de Paula, Edna Terezinha Rother, Joselisa Péres Queiroz de Paiva, Lucas Reis Correia