AIMC Topic: Retrospective Studies

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Extracting seizure frequency from epilepsy clinic notes: a machine reading approach to natural language processing.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Seizure frequency and seizure freedom are among the most important outcome measures for patients with epilepsy. In this study, we aimed to automatically extract this clinical information from unstructured text in clinical notes. If success...

Automated prediction of the Thoracolumbar Injury Classification and Severity Score from CT using a novel deep learning algorithm.

Neurosurgical focus
OBJECTIVE: Damage to the thoracolumbar spine can confer significant morbidity and mortality. The Thoracolumbar Injury Classification and Severity Score (TLICS) is used to categorize injuries and determine patients at risk of spinal instability for wh...

Feasibility of salvage robotic partial nephrectomy after ablative treatment failure (UroCCR-62 study).

Minerva urology and nephrology
BACKGROUND: Ablative therapies (AT) are increasingly being offered to patients with kidney tumors. In cases of failure or local relapse, salvage surgery may be required. Such procedures often require an open approach, are difficult and have received ...

Deep learning-enabled coronary CT angiography for plaque and stenosis quantification and cardiac risk prediction: an international multicentre study.

The Lancet. Digital health
BACKGROUND: Atherosclerotic plaque quantification from coronary CT angiography (CCTA) enables accurate assessment of coronary artery disease burden and prognosis. We sought to develop and validate a deep learning system for CCTA-derived measures of p...

Machine Learning Refinement of the NSQIP Risk Calculator: Who Survives the "Hail Mary" Case?

Journal of the American College of Surgeons
BACKGROUND: The American College of Surgeons (ACS) NSQIP risk calculator helps guide operative decision making. In patients with significant surgical risk, it may be unclear whether to proceed with "Hail Mary"-type interventions. To refine prediction...

High-Throughput Precision Phenotyping of Left Ventricular Hypertrophy With Cardiovascular Deep Learning.

JAMA cardiology
IMPORTANCE: Early detection and characterization of increased left ventricular (LV) wall thickness can markedly impact patient care but is limited by under-recognition of hypertrophy, measurement error and variability, and difficulty differentiating ...

Mass Deployment of Deep Neural Network: Real-Time Proof of Concept With Screening of Intracranial Hemorrhage Using an Open Data Set.

Neurosurgery
BACKGROUND: Intracranial hemorrhage (ICH) is considered an emergency that requires rapid medical or surgical management. Previous studies have used artificial intelligence to attempt to expedite the diagnosis of this pathology on neuroimaging. Howeve...

Antegrade Colonic Enema Channels in Pediatric Patients Using Appendix or Cecal Flap: A Comparative Robotic Open Series.

Journal of endourology
We present perioperative outcomes of a single-center experience with robot-assisted antegrade colonic enema (ACE) channel creation for the treatment of chronic constipation refractory to medical therapy and compare it to the traditional open surgica...

Early Experience of Transabdominal and Novel Transvaginal Robot-Assisted Laparoscopic Removal of Transvaginal Mesh.

Journal of endourology
Mesh removal after transvaginal mesh placement has typically involved transvaginal, open pelvic, laparoscopic, or a combination of approaches. Robotic pelvic mesh removal has been described in a small number of cases only. This study aims at determi...