AIMC Topic: United States

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Deep Learning Predicts Interval and Screening-detected Cancer from Screening Mammograms: A Case-Case-Control Study in 6369 Women.

Radiology
Background The ability of deep learning (DL) models to classify women as at risk for either screening mammography-detected or interval cancer (not detected at mammography) has not yet been explored in the literature. Purpose To examine the ability of...

Contemporary Pure Laparoscopic Robot-Assisted Laparoscopic Radical Nephrectomy: Is the Transition Worth It?

Journal of endourology
The proportion of robotic procedures continues to rise. The literature reinforces that robotic procedures take longer and are often more costly. We compared cost and perioperative outcomes of laparoscopic radical nephrectomy (LRN) and robot-assisted...

Malfunction Events in the US FDA MAUDE Database: How Does Robotic Gynecologic Surgery Compare with Other Specialties?

Journal of minimally invasive gynecology
STUDY OBJECTIVE: To review malfunction events (MEs) related to the use of the da Vinci robot reported to the United States Food and Drug Administration Manufacturer and User Facility Device Experience in the last 10 years and compare gynecologic surg...

Catalyzing Knowledge-Driven Discovery in Environmental Health Sciences through a Community-Driven Harmonized Language.

International journal of environmental research and public health
Harmonized language is critical for helping researchers to find data, collecting scientific data to facilitate comparison, and performing pooled and meta-analyses. Using standard terms to link data to knowledge systems facilitates knowledge-driven an...

The role of machine learning in clinical research: transforming the future of evidence generation.

Trials
BACKGROUND: Interest in the application of machine learning (ML) to the design, conduct, and analysis of clinical trials has grown, but the evidence base for such applications has not been surveyed. This manuscript reviews the proceedings of a multi-...

Predicting Incident Heart Failure in Women With Machine Learning: The Women's Health Initiative Cohort.

The Canadian journal of cardiology
BACKGROUND: Heart failure (HF) is a leading cause of cardiac morbidity among women, whose risk factors differ from those in men. We used machine-learning approaches to develop risk- prediction models for incident HF in a cohort of postmenopausal wome...

A machine learning approach identifies 5-ASA and ulcerative colitis as being linked with higher COVID-19 mortality in patients with IBD.

Scientific reports
Inflammatory bowel diseases (IBD), namely Crohn's disease (CD) and ulcerative colitis (UC) are chronic inflammation within the gastrointestinal tract. IBD patient conditions and treatments, such as with immunosuppressants, may result in a higher risk...

A Machine Learning Approach in Predicting Mortality Following Emergency General Surgery.

The American surgeon
BACKGROUND: There is a significant mortality burden associated with emergency general surgery (EGS) procedures. The objective of this study was to develop and validate the use of a machine learning approach to predict mortality following EGS.