AIMC Topic: United States

Clear Filters Showing 791 to 800 of 1288 articles

A Machine Learning Approach to Identify NIH-Funded Applied Prevention Research.

American journal of preventive medicine
INTRODUCTION: To fulfill its mission, the NIH Office of Disease Prevention systematically monitors NIH investments in applied prevention research. Specifically, the Office focuses on research in humans involving primary and secondary prevention, and ...

Minimally invasive, robot-assisted procedure for kidney transplantation among morbidly obese: Positive outcomes at 5 years post-transplant.

Clinical transplantation
The pre-transplant weight loss required of end-stage renal disease patients is often unachievable. Though robot-assisted procedures among extremely obese have shown minimal complication, long-term outcomes are understudied. Previously, we reported no...

Predictive models for charitable giving using machine learning techniques.

PloS one
Private giving represents more than three fourths of all U.S. charitable donations, about 2% of total Gross Domestic Product (GDP). Private giving is a significant factor in funding the nonprofit sector of the U.S. economy, which accounts for more th...

"Plutchik": artificial intelligence chatbot for searching NCBI databases.

Journal of the Medical Library Association : JMLA
As genetic testing gains ground in medicine, the ability to search across the suite of biomedical and clinical care databases offered through the National Library of Medicine/National Center for Biotechnology Information (NCBI)-such as PubMed, GENE, ...

Estimation of the Basic Reproduction Number and Vaccination Coverage of Influenza in the United States (2017-18).

Journal of research in health sciences
BACKGROUND: Determining the epidemic threshold parameter helps health providers calculate the coverage while guiding them in planning the process of vaccination strategy. Since the trend and mechanism of influenza is very similar in different countri...

Machine learning ensemble models predict total charges and drivers of cost for transsphenoidal surgery for pituitary tumor.

Journal of neurosurgery
OBJECTIVE: Efficient allocation of resources in the healthcare system enables providers to care for more and needier patients. Identifying drivers of total charges for transsphenoidal surgery (TSS) for pituitary tumors, which are poorly understood, r...

Machine learning reveals chronic graft--host disease phenotypes and stratifies survival after stem cell transplant for hematologic malignancies.

Haematologica
The application of machine learning in medicine has been productive in multiple fields, but has not previously been applied to analyze the complexity of organ involvement by chronic graft--host disease. Chronic graft--host disease is classified by an...

Identifying Latent Subgroups of High-Risk Patients Using Risk Score Trajectories.

Journal of general internal medicine
OBJECTIVE: Many healthcare systems employ population-based risk scores to prospectively identify patients at high risk of poor outcomes, but it is unclear whether single point-in-time scores adequately represent future risk. We sought to identify and...