AIMC Topic: Retrospective Studies

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Implementation of a robot-mediated upper limb rehabilitation protocol for a customized treatment after stroke: A retrospective analysis.

NeuroRehabilitation
BACKGROUND: Many authors have emphasized the need for individualized treatments in rehabilitation, but no tailored robotic rehabilitation protocol for stroke patients has been established yet.

Is the learning curve of the urology resident for conventional radical prostatectomy similar to that of staff initiating robot-assisted radical prostatectomy?

International braz j urol : official journal of the Brazilian Society of Urology
INTRODUCTION: The superiority of the functional results of robot-assisted radical prostatectomyis still controversial. Despite this, it is known that minimally invasive surgery obtains better results when analyzing blood loss, blood transfusion and l...

Gd-EOB-DTPA-enhanced MRI Image Characteristics and Radiomics Characteristics Combined with Machine Learning for Assessment of Functional Liver Reserve.

Current medical imaging
OBJECTIVE: To investigate the feasibility of image characteristics and radiomics combined with machine learning based on Gd-EOB-DTPA-enhanced MRI for functional liver reserve assessment in cirrhotic patients.

[Safety of robot-assisted implantation of deep electrodes for invasive stereo-EEG monitoring].

Zhurnal voprosy neirokhirurgii imeni N. N. Burdenko
UNLABELLED: Robot-assisted implantation of deep electrodes for stereo-EEG monitoring has become popular in recent years in patients with drug-resistant epilepsy. However, there are still few data on safety of this technique.

Severity-stratification of interstitial lung disease by deep learning enabled assessment and quantification of lesion indicators from HRCT images.

Journal of X-ray science and technology
BACKGROUND: Interstitial lung disease (ILD) represents a group of chronic heterogeneous diseases, and current clinical practice in assessment of ILD severity and progression mainly rely on the radiologist-based visual screening, which greatly restric...

Examination-Level Supervision for Deep Learning-based Intracranial Hemorrhage Detection on Head CT Scans.

Radiology. Artificial intelligence
Purpose To compare the effectiveness of weak supervision (ie, with examination-level labels only) and strong supervision (ie, with image-level labels) in training deep learning models for detection of intracranial hemorrhage (ICH) on head CT scans. M...

A CT-based Deep Learning Model for Predicting Subsequent Fracture Risk in Patients with Hip Fracture.

Radiology
Background Patients have the highest risk of subsequent fractures in the first few years after an initial fracture, yet models to predict short-term subsequent risk have not been developed. Purpose To develop and validate a deep learning prediction m...

Synthetic Data Improve Survival Status Prediction Models in Early-Onset Colorectal Cancer.

JCO clinical cancer informatics
PURPOSE: In artificial intelligence-based modeling, working with a limited number of patient groups is challenging. This retrospective study aimed to evaluate whether applying synthetic data generation methods to the clinical data of small patient gr...

Application of Machine-learning based on Radiomics Features in Differential Diagnosis of Superficial Lymphadenopathy.

Current medical imaging
OBJECTIVE: The accurate diagnosis of superficial lymphadenopathy is challenging. We aim to explore a non-invasive and accurate machine-learning method for distinguishing benign lymph nodes, lymphoma, and metastatic lymph nodes.