Results 1 to 10 of about 56,255 (180)

Automated Measurement of Vascular Calcification in Femoral Endarterectomy Patients Using Deep Learning [PDF]

open access: yesDiagnostics 2023, 13, 3363, 2023
Atherosclerosis, a chronic inflammatory disease affecting the large arteries, presents a global health risk. Accurate analysis of diagnostic images, like computed tomographic angiograms (CTAs), is essential for staging and monitoring the progression of atherosclerosis-related conditions, including peripheral arterial disease (PAD).
arxiv   +1 more source

Adjusting for bias introduced by instrumental variable estimation in the Cox Proportional Hazards Model [PDF]

open access: yesBiostatistics, 2017, 2017
Instrumental variable (IV) methods are widely used for estimating average treatment effects in the presence of unmeasured confounders. However, the capability of existing IV procedures, and most notably the two-stage residual inclusion (2SRI) procedure recommended for use in nonlinear contexts, to account for unmeasured confounders in the Cox ...
arxiv   +1 more source

Rounded notch method of femoral endarterectomy offers mechanical advantages in finite element models [PDF]

open access: yesarXiv, 2023
Objective: Use of a vascular punch to produce circular heel and toe arteriotomies for femoral endarterectomy with patch angioplasty is a novel technique. This study investigated the plausibility of this approach and the mechanical advantages of the technique using finite element models.
arxiv  

Trusting Machine Learning Results from Medical Procedures in the Operating Room [PDF]

open access: yesAAAI workshop on Trustworthy AI for Healthcare 2022, 2022
Machine learning can be used to analyse physiological data for several purposes. Detection of cerebral ischemia is an achievement that would have high impact on patient care. We attempted to study if collection of continous physiological data from non-invasive monitors, and analysis with machine learning could detect cerebral ischemia in tho different ...
arxiv  

Robust Machine Learning in Critical Care -- Software Engineering and Medical Perspectives [PDF]

open access: yesarXiv, 2021
Using machine learning in clinical practice poses hard requirements on explainability, reliability, replicability and robustness of these systems. Therefore, developing reliable software for monitoring critically ill patients requires close collaboration between physicians and software engineers.
arxiv  

Coronary Radiography and Endarterectomy [PDF]

open access: bronze, 1963
Nelson R. Niles, Charles T. Dotter
openalex   +1 more source

Femoro-popliteal Endarterectomy [PDF]

open access: bronze, 1965
W.T. Irvine, E. J. Willimas, S Plessas
openalex   +1 more source

Anaesthetic considerations for carotid thrombo-endarterectomy [PDF]

open access: bronze, 1967
Leonard C. Jenkins   +2 more
openalex   +1 more source

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