AIMC Topic: United States

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Falls Prevention Using AI and Remote Surveillance in Nursing Homes.

Journal of the American Medical Directors Association
The older population of United States is growing, with more adults having complicated medical conditions being admitted into nursing facilities and assisted living facilities. With the COVID-19 pandemic, the biggest challenge has been falls preventio...

Healthcare Violence and the Potential Promises and Harms of Artificial Intelligence.

Journal of patient safety
Currently, the healthcare workplace is one of the most dangerous in the United States. Over a 3-month period in 2022, two nurses were assaulted every hour. Artificial intelligence (AI) has the potential to prevent workplace violence by developing uni...

Deep learning models for predicting the survival of patients with hepatocellular carcinoma based on a surveillance, epidemiology, and end results (SEER) database analysis.

Scientific reports
Hepatocellular carcinoma (HCC) is a common malignancy with poor survival and requires long-term follow-up. Hence, we collected information on patients with Primary Hepatocellular Carcinoma in the United States from the Surveillance, Epidemiology, and...

Symptom phenotyping in people with cystic fibrosis during acute pulmonary exacerbations using machine-learning K-means clustering analysis.

Journal of cystic fibrosis : official journal of the European Cystic Fibrosis Society
INTRODUCTION: People with cystic fibrosis (PwCF) experience frequent symptoms associated with chronic lung disease. A complication of CF is a pulmonary exacerbation (PEx), which is often preceded by an increase in symptoms and a decline in lung funct...

Exploring predictors of substance use disorder treatment engagement with machine learning: The impact of social determinants of health in the therapeutic landscape.

Journal of substance use and addiction treatment
BACKGROUND: Improved knowledge of factors that influence treatment engagement could help treatment providers and systems better engage patients. The present study used machine learning to explore associations between individual- and neighborhood-leve...

Interpretable machine learning predicts postpartum hemorrhage with severe maternal morbidity in a lower-risk laboring obstetric population.

American journal of obstetrics & gynecology MFM
BACKGROUND: Early identification of patients at increased risk for postpartum hemorrhage (PPH) associated with severe maternal morbidity (SMM) is critical for preparation and preventative intervention. However, prediction is challenging in patients w...

Trust but Verify: Lessons Learned for the Application of AI to Case-Based Clinical Decision-Making From Postmarketing Drug Safety Assessment at the US Food and Drug Administration.

Journal of medical Internet research
Adverse drug reactions are a common cause of morbidity in health care. The US Food and Drug Administration (FDA) evaluates individual case safety reports of adverse events (AEs) after submission to the FDA Adverse Event Reporting System as part of it...

Two-part predictive modeling for COVID-19 cases and deaths in the U.S.

PloS one
COVID-19 prediction has been essential in the aid of prevention and control of the disease. The motivation of this case study is to develop predictive models for COVID-19 cases and deaths based on a cross-sectional data set with a total of 28,955 obs...

Regulatory and Implementation Considerations for Artificial Intelligence.

Otolaryngologic clinics of North America
Successful artificial intelligence (AI) implementation is predicated on the trust of clinicians and patients, and is achieved through a culture of responsible use, focusing on regulations, standards, and education. Otolaryngologists can overcome barr...

Artificial Intelligence in the Provision of Health Care: An American College of Physicians Policy Position Paper.

Annals of internal medicine
Internal medicine physicians are increasingly interacting with systems that implement artificial intelligence (AI) and machine learning (ML) technologies. Some physicians and health care systems are even developing their own AI models, both within an...