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…praising AI tools entering clinical practice, summarizing how machine learning, deep learning, and generative AI are being integrated into contemporary surgical workflows. P…

…d F1 scores of 0.9867 and 0.9863, respectively. This study introduces the first deep learning model for intraoral flaps and demonstrates the possibility of quantitative meas…

… classification problem, the highest overall accuracy of 80% was obtained using deep learning. Our HSI system was capable of intraoperative data acquisition and visualizatio…

Feature Tracking and Segmentation in Real Time via Deep Learning in Vitreoretinal Surgery: A Platform for Artificial Intelligence-Mediated Surgi…

Automated tool detection with deep learning for monitoring kinematics and eye-hand coordination in microsurgery.

[PURPOSE OF REVIEW] Artificial intelligence and deep learning have become important tools in extracting data from ophthalmic surgery to evalu…

Automated Vision-Based Microsurgical Skill Analysis in Neurosurgery Using Deep Learning: Development and Preclinical Validation.

…n of breast features with an ad hoc trained neural network. [METHODS] An ad hoc convolutional neural network was developed on the YOLOV3 platform to detect key features of the breast that …

Effect of Multichannel Convolutional Neural Network-Based Model on the Repair and Aesthetic Effect of Eye Plastic Surgery Patients.

An Automatic Framework for Nasal Esthetic Assessment by ResNet Convolutional Neural Network.

… Measurement of Nasal Landmark Locations by Digital 2D Photogrammetry Using the Convolutional Neural Network.

… equipment defects. In order to overcome these problems, we propose specialized convolutional neural network (CNN) architecture to accurately predict nasal measurement based on digital 2D …

…es of surgical success remain sparse. Therefore, we investigated the ability of convolutional neural networks (CNNs) to assess differences in perceived age before and after blepharoplasty …

…d to quantify the impact of brow lift and blepharoplasty on age as perceived by convolutional neural network (CNN) algorithms. [METHODS] A retrospective review was performed on patients wh…

…lable for assessing the success of facial rejuvenation after face lift surgery. Convolutional neural networks (CNNs) may be used for this type of measurement. The purpose of this investiga…

…change in artificial intelligence-assisted landmark identification (LI) using a convolutional neural network (CNN) algorithm in serial lateral cephalograms (Lat-cephs) of Class III (C-III)…

…ween glabellar muscles, skin, and subcutaneous tissue. AI frameworks, including convolutional neural networks and long short-term memory networks, were trained on 3D facial scan data captu…

Monocular suture needle pose detection using synthetic data augmented convolutional neural network.

…a HSI recordings. The best flap classification performance was observed using a convolutional neural network using HSI based perfusion parameters within 72 h after surgery, with an area un…

…anced segmentation performance over baseline (mIOU 0.6892 vs. 0.8869). Besides, Convolutional Neural Networks (CNNs) achieved a robust performance (mIOU 0.8917 vs. 0.8603) even when the tr…