AI Medical Compendium Topic

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Hemorrhage

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Solitary Fibrous Tumor of the Prostate Treated with Frozen-Section Supported Robot-Assisted Nerve-Sparing Radical Prostatectomy.

Urologia internationalis
INTRODUCTION: Solitary fibrous tumors (SFTs) of the prostate are extremely rare. We report on a 60-year-old man who was diagnosed with prostatic SFT through transurethral resection (TUR) of the prostate, and we provide a narrative literature review t...

APPRAISE-HRI: AN ARTIFICIAL INTELLIGENCE ALGORITHM FOR TRIAGE OF HEMORRHAGE CASUALTIES.

Shock (Augusta, Ga.)
Background: Hemorrhage remains the leading cause of death on the battlefield. This study aims to assess the ability of an artificial intelligence triage algorithm to automatically analyze vital-sign data and stratify hemorrhage risk in trauma patient...

Doctors Identify Hemorrhage Better during Chart Review when Assisted by Artificial Intelligence.

Applied clinical informatics
OBJECTIVES: This study evaluated if medical doctors could identify more hemorrhage events during chart review in a clinical setting when assisted by an artificial intelligence (AI) model and medical doctors' perception of using the AI model.

Pilot Analysis of Surgeon Instrument Utilization Signatures Based on Shannon Entropy and Deep Learning for Surgeon Performance Assessment in a Cadaveric Carotid Artery Injury Control Simulation.

Operative neurosurgery (Hagerstown, Md.)
BACKGROUND AND OBJECTIVES: Assessment and feedback are critical to surgical education, but direct observational feedback by experts is rarely provided because of time constraints and is typically only qualitative. Automated, video-based, quantitative...

Quantitative image signature and machine learning-based prediction of outcomes in cerebral cavernous malformations.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
PURPOSE: There is increasing interest in novel prognostic tools and predictive biomarkers to help identify, with more certainty, cerebral cavernous malformations (CCM) susceptible of bleeding if left untreated. We developed explainable quantitative-b...

A weakly supervised deep learning model integrating noncontrasted computed tomography images and clinical factors facilitates haemorrhagic transformation prediction after intravenous thrombolysis in acute ischaemic stroke patients.

Biomedical engineering online
BACKGROUND: Haemorrhage transformation (HT) is a serious complication of intravenous thrombolysis (IVT) in acute ischaemic stroke (AIS). Accurate and timely prediction of the risk of HT before IVT may change the treatment decision and improve clinica...

Using machine learning to predict bleeding after cardiac surgery.

European journal of cardio-thoracic surgery : official journal of the European Association for Cardio-thoracic Surgery
OBJECTIVES: The primary objective was to predict bleeding after cardiac surgery with machine learning using the data from the Australia New Zealand Society of Cardiac and Thoracic Surgeons Cardiac Surgery Database, cardiopulmonary bypass perfusion da...