Results 211 to 220 of about 101,249 (289)

Evaluation of Arteriography Time in Non-Thrombosed Intracranial Aneurysms Completely After Endovascular Treatment: a systematic review

open access: diamond
Laécio Carvalho de Barros   +3 more
openalex   +1 more source

Low‐Molecular‐Weight Heparin for Adult ICU Patients Who Require Thromboprophylaxis: Protocol for the INCEPT‐Thromboprophylaxis Platform Trial Domain

open access: yesActa Anaesthesiologica Scandinavica, Volume 70, Issue 3, March 2026.
ABSTRACT Background Low‐molecular‐weight heparin (LMWH) is recommended for thromboprophylaxis in adult intensive care unit (ICU) patients. Despite its widespread use, there is insufficient evidence on the optimal dose, and there appears to be practice variation.
Ruben Eck   +10 more
wiley   +1 more source

Treatment of Partial Thrombosed Giant Aneurysm, Enlarged and Regrown Following Endovascular Surgery

open access: bronze, 1993
Hideki Murakami   +9 more
openalex   +2 more sources

CYP2C19 genotype testing for clopidogrel: A guideline developed by the UK Centre of Excellence in Regulatory Science and Innovation in Pharmacogenomics (CERSI‐PGx)

open access: yesBritish Journal of Clinical Pharmacology, Volume 92, Issue 2, Page 329-347, February 2026.
Clopidogrel, an antiplatelet agent, is currently licensed in the United Kingdom for the prevention and treatment of atherothrombotic events in cerebrovascular disease, coronary artery disease and peripheral arterial disease. Clopidogrel requires metabolic activation by the cytochrome P450 enzyme CYP2C19 to be effective.
Cinzia Dello Russo   +22 more
wiley   +1 more source

Basic Technique of Endovascular Treatment of Intracranial Aneurysms

open access: diamond, 2015
Nobuyuki Sakai   +13 more
openalex   +2 more sources

Machine learning methods for predicting adverse drug events: A systematic review

open access: yesBritish Journal of Clinical Pharmacology, Volume 92, Issue 2, Page 422-444, February 2026.
Abstract Predicting adverse drug events (ADEs) in outpatient settings is crucial for improving medication safety, identifying high‐risk patients and reducing health‐care costs. While traditional methods struggle with the complexity of health‐care data, machine learning (ML) models offer improved prediction capabilities; however, their effectiveness in ...
Niaz Chalabianloo   +8 more
wiley   +1 more source

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