AIMC Topic: Retrospective Studies

Clear Filters Showing 5271 to 5280 of 9989 articles

Performance of a Machine Learning Algorithm Using Electronic Health Record Data to Predict Postoperative Complications and Report on a Mobile Platform.

JAMA network open
IMPORTANCE: Predicting postoperative complications has the potential to inform shared decisions regarding the appropriateness of surgical procedures, targeted risk-reduction strategies, and postoperative resource use. Realizing these advantages requi...

Validation of Soft Labels in Developing Deep Learning Algorithms for Detecting Lesions of Myopic Maculopathy From Optical Coherence Tomographic Images.

Asia-Pacific journal of ophthalmology (Philadelphia, Pa.)
PURPOSE: It is common for physicians to be uncertain when examining some images. Models trained with human uncertainty could be a help for physicians in diagnosing pathologic myopia.

Propensity-Matched Analysis of the Short-Term Outcome of Robot-Assisted Minimally Invasive Esophagectomy Versus Conventional Thoracoscopic Esophagectomy in Thoracic Esophageal Cancer.

World journal of surgery
BACKGROUND: In this matched-cohort study, we investigated the short-term outcome of robot-assisted minimally invasive esophagectomy (RAMIE) compared with conventional minimally invasive thoracoscopic esophagectomy (MIE) in esophageal cancer patients.

Diagnostic performance for detecting bone marrow edema of the hip on dual-energy CT: Deep learning model vs. musculoskeletal physicians and radiologists.

European journal of radiology
PURPOSE: To compare the diagnostic performance of a deep learning (DL) model with that of musculoskeletal physicians and radiologists for detecting bone marrow edema on dual-energy CT (DECT).

The efficacy of deep learning models in the diagnosis of endometrial cancer using MRI: a comparison with radiologists.

BMC medical imaging
PURPOSE: To compare the diagnostic performance of deep learning models using convolutional neural networks (CNN) with that of radiologists in diagnosing endometrial cancer and to verify suitable imaging conditions.

Da Vinci Robot-Assisted Video Image Processing under Artificial Intelligence Vision Processing Technology.

Computational and mathematical methods in medicine
This research was aimed to explore the application value of intelligent algorithm-based digital images in Da Vinci robot-assisted treatment of patients with gastric cancer surgery. 154 patients were included as the research objects, with 89 cases in ...

Understanding land degradation induced by gully erosion from the perspective of different geoenvironmental factors.

Journal of environmental management
Complex interrelationships between landscape-level geoenvironmental factors and natural phenomena have rendered land degradation control measures ineffective. For control to be effective, this study argues that the interactions between different geoe...

Automated detection of arterial landmarks and vascular occlusions in patients with acute stroke receiving digital subtraction angiography using deep learning.

Journal of neurointerventional surgery
BACKGROUND: Digital subtraction angiography (DSA) is the gold-standard method of assessing arterial blood flow and blockages prior to endovascular thrombectomy.

POTTER-ICU: An artificial intelligence smartphone-accessible tool to predict the need for intensive care after emergency surgery.

Surgery
BACKGROUND: Delays in admitting high-risk emergency surgery patients to the intensive care unit result in worse outcomes and increased health care costs. We aimed to use interpretable artificial intelligence technology to create a preoperative predic...

Short-term results of robot-assisted colorectal cancer surgery using Senhance Digital Laparoscopy System.

Asian journal of endoscopic surgery
BACKGROUND: The Senhance Digital Laparoscopy System (Asensus Surgical Inc, Morrisville, NC, United States), which was introduced for the first time in Japan by our hospital, is a new surgical assistive robot following the da Vinci Surgical System. We...