AIMC Topic: Retrospective Studies

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Robot-assisted laparoscopic nephrectomy: early outcome measures with the implementation of multimodal analgesia and intrathecal morphine via the acute pain service.

World journal of urology
PURPOSE: The objective of this study was to perform a retrospective cohort analysis, in which we measured the association of an acute pain service (APS)-driven multimodal analgesia protocol that included preoperative intrathecal morphine (ITM) compar...

Predicting microvascular invasion in hepatocellular carcinoma with a CT- and MRI-based multimodal deep learning model.

Abdominal radiology (New York)
PURPOSE: To investigate the value of a multimodal deep learning (MDL) model based on computed tomography (CT) and magnetic resonance imaging (MRI) for predicting microvascular invasion (MVI) in hepatocellular carcinoma (HCC).

Development and Validation of a Natural Language Processing Model to Identify Low-Risk Pulmonary Embolism in Real Time to Facilitate Safe Outpatient Management.

Annals of emergency medicine
STUDY OBJECTIVE: This study aimed to (1) develop and validate a natural language processing model to identify the presence of pulmonary embolism (PE) based on real-time radiology reports and (2) identify low-risk PE patients based on previously valid...

Deep Learning for Automatic Gross Tumor Volumes Contouring in Esophageal Cancer Based on Contrast-Enhanced Computed Tomography Images: A Multi-Institutional Study.

International journal of radiation oncology, biology, physics
PURPOSE: To develop and externally validate an automatic artificial intelligence (AI) tool for delineating gross tumor volume (GTV) in patients with esophageal squamous cell carcinoma (ESCC), which can assist in neo-adjuvant or radical radiation ther...

Magnetic resonance imaging-based deep learning imaging biomarker for predicting functional outcomes after acute ischemic stroke.

European journal of radiology
PURPOSE: Clinical risk scores are essential for predicting outcomes in stroke patients. The advancements in deep learning (DL) techniques provide opportunities to develop prediction applications using magnetic resonance (MR) images. We aimed to devel...

Gasless robot-assisted transaxillary hemithyroidectomy (RATH): learning curve and complications.

BMC surgery
PURPOSE: Gasless robot-assisted transaxillary hemithyroidectomy (RATH) is regarded as an alternative surgical option for thyroid operations. However, the associated steep learning curve is a clinical concern. This study evaluated the learning curve o...

Comparison of perioperative outcomes between robot-assisted adrenalectomy and laparoscopic adrenalectomy: a propensity score matching analysis.

Journal of robotic surgery
This study aimed to evaluate and compare the perioperative outcomes of robot-assisted adrenalectomy (RAA) and laparoscopic adrenalectomy (LA) using propensity score matching. This retrospective study included 395 patients who underwent minimally inva...

Advancements in Uric Acid Stone Detection: Integrating Deep Learning with CT Imaging and Clinical Assessments in the Upper Urinary Tract.

Urologia internationalis
INTRODUCTION: Among upper urinary tract stones, a significant proportion comprises uric acid stones. The aim of this study was to use machine learning techniques to analyze CT scans and blood and urine test data, with the aim of establishing multiple...

Utilizing imaging parameters for functional outcome prediction in acute ischemic stroke: A machine learning study.

Journal of neuroimaging : official journal of the American Society of Neuroimaging
BACKGROUND AND PURPOSE: We aimed to predict the functional outcome of acute ischemic stroke patients with anterior circulation large vessel occlusions (LVOs), irrespective of how they were treated or the severity of the stroke at admission, by only u...