AIMC Topic: Retrospective Studies

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Performance of deep convolutional neural network for classification and detection of oral potentially malignant disorders in photographic images.

International journal of oral and maxillofacial surgery
Oral potentially malignant disorders (OPMDs) are a group of conditions that can transform into oral cancer. The purpose of this study was to evaluate convolutional neural network (CNN) algorithms to classify and detect OPMDs in oral photographs. In t...

Real-time artificial intelligence for detecting focal lesions and diagnosing neoplasms of the stomach by white-light endoscopy (with videos).

Gastrointestinal endoscopy
BACKGROUND AND AIMS: White-light endoscopy (WLE) is the most pivotal tool to detect gastric cancer in an early stage. However, the skill among endoscopists varies greatly. Here, we aim to develop a deep learning-based system named ENDOANGEL-LD (lesio...

Robustifying Deep Networks for Medical Image Segmentation.

Journal of digital imaging
The purpose of this study is to investigate the robustness of a commonly used convolutional neural network for image segmentation with respect to nearly unnoticeable adversarial perturbations, and suggest new methods to make these networks more robus...

A Machine Learning Model for Evaluating Imported Disease Screening Strategies in Immigrant Populations.

The American journal of tropical medicine and hygiene
Given the high prevalence of imported diseases in immigrant populations, it has postulated the need to establish screening programs that allow their early diagnosis and treatment. We present a mathematical model based on machine learning methodologie...

Catheter position prediction using deep-learning-based multi-atlas registration for high-dose rate prostate brachytherapy.

Medical physics
PURPOSE: High-dose-rate (HDR) prostate brachytherapy involves treatment catheter placement, which is currently empirical and physician dependent. The lack of proper catheter placement guidance during the procedure has left the physicians to rely on a...

Renal Functional and Perioperative Outcomes of Retroperitoneal Robot-Assisted Versus Laparoscopic Partial Nephrectomy with Segmental Renal Artery Clamping.

Journal of laparoendoscopic & advanced surgical techniques. Part A
Retroperitoneal approach and segmental renal artery clamping in partial nephrectomy are techniques that facilitate postoperative recovery and renal function preservation. This study aimed to compare the renal function preservation and perioperative ...

Deep learning model to detect significant aortic regurgitation using electrocardiography.

Journal of cardiology
BACKGROUND: Aortic regurgitation (AR) is a common heart disease, with a relatively high prevalence of 4.9% in the Framingham Heart Study. Because the prevalence increases with advancing age, an upward shift in the age distribution may increase the bu...

Myosteatosis as a novel predictor of urinary incontinence after robot-assisted radical prostatectomy.

International journal of urology : official journal of the Japanese Urological Association
OBJECTIVES: To evaluate the impact of sarcopenia and myosteatosis on urinary incontinence after prostatectomy.

Diagnostic Test Accuracy of Deep Learning Detection of COVID-19: A Systematic Review and Meta-Analysis.

Academic radiology
RATIONALE AND OBJECTIVE: To perform a meta-analysis to compare the diagnostic test accuracy (DTA) of deep learning (DL) in detecting coronavirus disease 2019 (COVID-19), and to investigate how network architecture and type of datasets affect DL perfo...

Feasibility assessment of infectious keratitis depicted on slit-lamp and smartphone photographs using deep learning.

International journal of medical informatics
BACKGROUND: This study aims to investigate how infectious keratitis depicted on slit-lamp and smartphone photographs can be reliably assessed using deep learning.