AIMC Topic: Retrospective Studies

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Convolutional neural network based anatomical site identification for laryngoscopy quality control: A multicenter study.

American journal of otolaryngology
OBJECTIVES: Video laryngoscopy is an important diagnostic tool for head and neck cancers. The artificial intelligence (AI) system has been shown to monitor blind spots during esophagogastroduodenoscopy. This study aimed to test the performance of AI-...

Robot-assisted radical prostatectomy using a novel urethral reconstruction technique vs standard vesicourethral anastomosis. A retrospective cohort study.

World journal of urology
BACKGROUND: Urinary incontinence is a common postoperative complication of radical prostatectomy (RP). In order to improve postoperative urinary continence rate, we proposed a urethral reconstruction technique which can prevent functional urethra ret...

Explainability and controllability of patient-specific deep learning with attention-based augmentation for markerless image-guided radiotherapy.

Medical physics
BACKGROUND: We reported the concept of patient-specific deep learning (DL) for real-time markerless tumor segmentation in image-guided radiotherapy (IGRT). The method was aimed to control the attention of convolutional neural networks (CNNs) by artif...

A Single-Institution Comparison of Robot-Assisted and Conventional Laparoscopic Colorectal Surgeries.

The American surgeon
There has been ongoing discussion regarding the superiority of robotic laparoscopic surgery (RLS) over conventional laparoscopic surgery (CLS) in many surgical subspecialties. We therefore sought to elucidate if RLS is associated with more favorable ...

Ultrasound-based deep learning in the establishment of a breast lesion risk stratification system: a multicenter study.

European radiology
OBJECTIVES: To establish a breast lesion risk stratification system using ultrasound images to predict breast malignancy and assess Breast Imaging Reporting and Data System (BI-RADS) categories simultaneously.

Cost-effectiveness analysis of revisional Roux-en-Y gastric bypass: laparoscopic vs. robot assisted.

Updates in surgery
There is controversy over the possible advantages of the robotic technology in revisional bariatric surgery. The aim of this study is to report the experience of a high-volume bariatric center on revisional Roux-en-Y gastric bypass with robot-assiste...

Sarcopenia identified by computed tomography imaging using a deep learning-based segmentation approach impacts survival in patients with newly diagnosed multiple myeloma.

Cancer
BACKGROUND: Sarcopenia increases with age and is associated with poor survival outcomes in patients with cancer. By using a deep learning-based segmentation approach, clinical computed tomography (CT) images of the abdomen of patients with newly diag...

Deep learning-assisted sensitive detection of fentanyl using a bubbling-microchip.

Lab on a chip
Deep learning-enabled smartphone-based image processing has significant advantages in the development of point-of-care diagnostics. Conventionally, most deep-learning applications require task specific large scale expertly annotated datasets. Therefo...

Short-term outcomes of robot-assisted versus conventional laparoscopic surgery for mid and low rectal cancer after neoadjuvant chemoradiotherapy: a propensity score-matched analysis.

Journal of robotic surgery
The benefits of robot-assisted laparoscopic surgery (RALS) for rectal cancer remain controversial. Only a few studies have evaluated the safety and feasibility of RALS following neoadjuvant chemoradiotherapy (NCRT). This study aimed to compare the sh...

A multidomain fusion model of radiomics and deep learning to discriminate between PDAC and AIP based on F-FDG PET/CT images.

Japanese journal of radiology
PURPOSE: To explore a multidomain fusion model of radiomics and deep learning features based on F-fluorodeoxyglucose positron emission tomography/computed tomography (F-FDG PET/CT) images to distinguish pancreatic ductal adenocarcinoma (PDAC) and aut...