AIMC Topic: Retrospective Studies

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AI-based X-ray fracture analysis of the distal radius: accuracy between representative classification, detection and segmentation deep learning models for clinical practice.

BMJ open Jan 23, 2024
OBJECTIVES: To aid in selecting the optimal artificial intelligence (AI) solution for clinical application, we directly compared performances of selected representative custom-trained or commercial classification, detection and segmentation models fo...
Retrospective Studies Radius Deep Learning X-Rays Fractures, Bone Humans Artificial Intelligence
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Deep Learning-Based Detection and Classification of Bone Lesions on Staging Computed Tomography in Prostate Cancer: A Development Study.

Academic radiology Jan 22, 2024
RATIONALE AND OBJECTIVES: Efficiently detecting and characterizing metastatic bone lesions on staging CT is crucial for prostate cancer (PCa) care. However, it demands significant expert time and additional imaging such as PET/CT. We aimed to develop...
Humans Radiographic Image Interpretation, Computer-Assisted Tomography, X-Ray Computed Bone Neoplasms Retrospective Studies Middle Aged Aged Prostatic Neoplasms Deep Learning Male Neoplasm Staging
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Comparison of postoperative pain between transoral and conventional thyroidectomy: a propensity score-matched analysis.

Surgical endoscopy Jan 22, 2024
BACKGROUND: The extent of postoperative pain following transoral thyroidectomy is not well-understood and remains a subject of debate. This study aims to analyze and compare postoperative pain levels between patients undergoing transoral and conventi...
Humans Retrospective Studies Thyroidectomy Thyroid Neoplasms Robotic Surgical Procedures Robotics Propensity Score Pain, Postoperative Neck Dissection
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Detection of fibrosing interstitial lung disease-suspected chest radiographs using a deep learning-based computer-aided detection system: a retrospective, observational study.

BMJ open Jan 22, 2024
OBJECTIVES: To investigate the effectiveness of BMAX, a deep learning-based computer-aided detection system for detecting fibrosing interstitial lung disease (ILD) on chest radiographs among non-expert and expert physicians in the real-world clinical...
Allied Health Personnel Deep Learning Lung Diseases, Interstitial Humans Computers Retrospective Studies
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Unsupervised deep learning with convolutional neural networks for static parallel transmit design: A retrospective study.

Magnetic resonance in medicine Jan 21, 2024
PURPOSE: To mitigate inhomogeneity at 7T for multi-channel transmit arrays using unsupervised deep learning with convolutional neural networks (CNNs).
Humans Retrospective Studies Neural Networks, Computer Deep Learning Brain Magnetic Resonance Imaging
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An artificial intelligence system for chronic atrophic gastritis diagnosis and risk stratification under white light endoscopy.

Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver Jan 20, 2024
BACKGROUND AND AIMS: The diagnosis and stratification of gastric atrophy (GA) predict patients' gastric cancer progression risk and determine endoscopy surveillance interval. We aimed to construct an artificial intelligence (AI) system for GA endosco...
Gastroscopy Gastritis, Atrophic Adult Stomach Neoplasms Sensitivity and Specificity Retrospective Studies Male Female Humans Middle Aged Aged Artificial Intelligence Risk Assessment
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Deep learning-based multimodal segmentation of oropharyngeal squamous cell carcinoma on CT and MRI using self-configuring nnU-Net.

European radiology Jan 20, 2024
PURPOSE: To evaluate deep learning-based segmentation models for oropharyngeal squamous cell carcinoma (OPSCC) using CT and MRI with nnU-Net.
Aged Adult Male Multimodal Imaging Female Humans Middle Aged Carcinoma, Squamous Cell Image Interpretation, Computer-Assisted Retrospective Studies Deep Learning Reproducibility of Results Oropharyngeal Neoplasms Tomography, X-Ray Computed Magnetic Resonance Imaging
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Development and validation of a multimodal model in predicting severe acute pancreatitis based on radiomics and deep learning.

International journal of medical informatics Jan 20, 2024
OBJECTIVE: Aim to establish a multimodal model for predicting severe acute pancreatitis (SAP) using machine learning (ML) and deep learning (DL).
Pancreatitis Radiomics Deep Learning Humans Acute Disease Retrospective Studies
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Predicting 5-year recurrence risk in colorectal cancer: development and validation of a histology-based deep learning approach.

British journal of cancer Jan 20, 2024
BACKGROUND: Accurate estimation of the long-term risk of recurrence in patients with non-metastatic colorectal cancer (CRC) is crucial for clinical management. Histology-based deep learning is expected to provide more abundant information for risk st...
Humans Prognosis Retrospective Studies Neoplasm Recurrence, Local Risk Factors Colorectal Neoplasms Deep Learning
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Non-invasive fractional flow reserve estimation using deep learning on intermediate left anterior descending coronary artery lesion angiography images.

Scientific reports Jan 20, 2024
This study aimed to design an end-to-end deep learning model for estimating the value of fractional flow reserve (FFR) using angiography images to classify left anterior descending (LAD) branch angiography images with average stenosis between 50 and ...
Humans Retrospective Studies Coronary Vessels Predictive Value of Tests Coronary Stenosis Coronary Angiography Severity of Illness Index Fractional Flow Reserve, Myocardial Coronary Artery Disease Deep Learning
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