AIMC Topic: United States

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Closing the Digital Health Evidence Gap: Development of a Predictive Score to Maximize Patient Outcomes.

Telemedicine journal and e-health : the official journal of the American Telemedicine Association
Clinical studies of telemedicine (TM) programs for chronic illness have demonstrated mixed results across settings and populations. With recent uptake in use of digital health modalities, more precise patient classification may improve outcomes, eff...

Clinician Perceptions of Robotic Exoskeletons for Locomotor Training After Spinal Cord Injury: A Qualitative Approach.

Archives of physical medicine and rehabilitation
OBJECTIVE: To describe the experiences of clinicians who have used robotic exoskeletons in their practice and acquire information that can guide clinical decisions and training strategies related to robotic exoskeletons.

Tree-Based Machine Learning to Identify and Understand Major Determinants for Stroke at the Neighborhood Level.

Journal of the American Heart Association
Background Stroke is a major cardiovascular disease that causes significant health and economic burden in the United States. Neighborhood community-based interventions have been shown to be both effective and cost-effective in preventing cardiovascul...

Trends in robotic surgery utilization across tertiary children's hospitals in the United States.

Surgical endoscopy
BACKGROUND: A growing number of tertiary children's hospitals are utilizing robotic surgical technology. We sought to characterize national trends in pediatric surgical robotic case utilization and related drivers.

Conversion rate of laparoscopic or robotic to open sacrocolpopexy: are there associated factors and complications?

International urogynecology journal
OBJECTIVES: To evaluate the conversion rate of laparoscopic or robotic to open sacrocolpopexy and to identify associated factors in a large population-based database.

A Novel Use of Artificial Intelligence to Examine Diversity and Hospital Performance.

The Journal of surgical research
BACKGROUND: The US population is becoming more racially and ethnically diverse. Research suggests that cultural diversity within organizations can increase team potency and performance, yet this theory has not been explored in the field of surgery. F...

Comparison of Machine Learning Models for the Androgen Receptor.

Environmental science & technology
The androgen receptor (AR) is a target of interest for endocrine disruption research, as altered signaling can affect normal reproductive and neurological development for generations. In an effort to prioritize compounds with alternative methodologie...

Residents' Views on the Impact of Robotic Surgery on General Surgery Education.

Journal of surgical education
OBJECTIVE: The use of the da Vinci Robot has been fast growing in general surgery in the United States over the past decade. While the financial cost of robot-assisted procedures has been studied, there has been limited research on the educational co...

Industry ties and evidence in public comments on the FDA framework for modifications to artificial intelligence/machine learning-based medical devices: a cross sectional study.

BMJ open
OBJECTIVES: To determine the extent and disclosure of financial ties to industry and use of scientific evidence in comments on a US Food and Drug Administration (FDA) regulatory framework for modifications to artificial intelligence/machine learning ...

Utilization of Deep Learning for Subphenotype Identification in Sepsis-Associated Acute Kidney Injury.

Clinical journal of the American Society of Nephrology : CJASN
BACKGROUND AND OBJECTIVES: Sepsis-associated AKI is a heterogeneous clinical entity. We aimed to agnostically identify sepsis-associated AKI subphenotypes using deep learning on routinely collected data in electronic health records.