AIMC Topic: Retrospective Studies

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Application of deterministic networking for reducing network delay in urological telesurgery: A retrospective study.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: Deterministic Networking (DetNet) is a new technology that can effectively control network delay and may promote the revolution of telemedicine. This study verified the feasibility and advantage of deterministic networking in telesurgery.

Discriminating malignant from benign testicular masses using machine-learning based radiomics signature of appearance diffusion coefficient maps: Comparing with conventional mean and minimum ADC values.

European journal of radiology
PURPOSE: To develop a machine-learning-based radiomics signature of ADC for discriminating between benign and malignant testicular masses and compare its classification performance with that of minimum and mean ADC.

Deep learning of early brain imaging to predict post-arrest electroencephalography.

Resuscitation
INTRODUCTION: Guidelines recommend use of computerized tomography (CT) and electroencephalography (EEG) in post-arrest prognostication. Strong associations between CT and EEG might obviate the need to acquire both modalities. We quantified these asso...

Joint segmentation and classification of breast masses based on ultrasound radio-frequency data and convolutional neural networks.

Ultrasonics
In this paper, we propose a novel deep learning method for joint classification and segmentation of breast masses based on radio-frequency (RF) ultrasound (US) data. In comparison to commonly used classification and segmentation techniques, utilizing...

Deep learning-based algorithm for lung cancer detection on chest radiographs using the segmentation method.

Scientific reports
We developed and validated a deep learning (DL)-based model using the segmentation method and assessed its ability to detect lung cancer on chest radiographs. Chest radiographs for use as a training dataset and a test dataset were collected separatel...

Machine Learning-Based Mortality Prediction of Patients at Risk During Hospital Admission.

Journal of patient safety
OBJECTIVES: The ability to predict in-hospital mortality from data available at hospital admission would identify patients at risk and thereby assist hospital-wide patient safety initiatives. Our aim was to use modern machine learning tools to predic...

Human identification performed with skull's sphenoid sinus based on deep learning.

International journal of legal medicine
Human identification plays a significant role in the investigations of disasters and criminal cases. Human identification could be achieved quickly and efficiently via 3D sphenoid sinus models by customized convolutional neural networks. In this retr...

A tale of two robots: Operating times and learning curves in robot-assisted lumbar fusion.

Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
Robotic assistance technologies are being incorporated into minimally invasive transforaminal lumbar interbody fusion (MIS-TLIF) to minimize radiation exposure to the patient and operating staff. However, they introduce new issues including increased...

Robot-assisted versus laparoscopic approach to concurrent bariatric surgery and hiatal hernia repair: propensity score matching analysis using the 2015-2018 MBSAQIP.

Surgical endoscopy
BACKGROUND: Up to 37% of class three obesity patients have a Hiatal Hernia (HH). Most of the existent HHs get repaired at the time of bariatric surgery. Although the robotic platform might offer potential technical advantages over traditional laparos...