15 research outputs found
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Enhancing Readability and Detection of Age-Related Macular Degeneration Using Optical Coherence Tomography Imaging: An AI Approach
Data Availability Statement:
The data presented in this study are openly available in: https://github.com/jodeiri/An-Ensemble-Deep-Learning-Model-for-AMD-Classification-using-OCT-images.git (accessed on 10 February 2024).Artificial intelligence has been used effectively in medical diagnosis. The objective of this project is to examine the application of a collective AI model using weighted fusion of predicted probabilities from different AI architectures to diagnose various retinal conditions based on optical coherence tomography (OCT). A publicly available Noor dataset, comprising 16,822, images from 554 retinal OCT scans of 441 patients, was used to predict a diverse spectrum of age-related macular degeneration (AMD) stages: normal, drusen, or choroidal neovascularization. These predictions were compared with predictions from ResNet, EfficientNet, and Attention models, respectively, using precision, recall, F1 score, and confusion matric and receiver operating characteristics curves. Our collective model demonstrated superior accuracy in classifying AMD compared to individual ResNet, EfficientNet, and Attention models, showcasing the effectiveness of using trainable weights in the ensemble fusion process, where these weights dynamically adapt during training rather than being fixed values. Specifically, our ensemble model achieved an accuracy of 91.88%, precision of 92.54%, recall of 92.01%, and F1 score of 92.03%, outperforming individual models. Our model also highlights the refinement process undertaken through a thorough examination of initially misclassified cases, leading to significant improvements in the model’s accuracy rate to 97%. This study also underscores the potential of AI as a valuable tool in ophthalmology. The proposed ensemble model, combining different mechanisms highlights the benefits of model fusion for complex medical image analysis.This research received no external funding
Prospective evaluation of the impact of sonography on the management and surgical intervention of neonates with necrotizing enterocolitis
Background/aimEstablished indications for surgery in necrotizing enterocolitis (NEC) are pneumoperitoneum and failure to improve or clinical deterioration with medical treatment alone. It has been proposed that infants with intestinal necrosis may benefit from surgery in the absence of one of these indications yet the diagnosis of definitive intestinal necrosis is challenging. Recent data suggest that abdominal ultrasound (US) examination focused on the gastrointestinal tract and the peritoneal cavity may be of utility in this regard. The aim of this study was to evaluate the ability of abdominal US to detect intestinal necrosis in infants with radiographically confirmed NEC.MethodsTwenty-six consecutive infants with Bell stage II or III NEC were prospectively included in the study between September 2013 and July 2014. Infants with a pre-existing indication for surgery were excluded. At least one abdominal US examination was performed in each patient using a standardized previously described method. Surgery was performed at the discretion of the attending surgeon based on clinical and imaging findings. Clinical, radiographic, US, and intra-operative data were recorded to allow comparison between US findings, surgical findings and outcome.ResultsUS demonstrated signs of intestinal necrosis in 5 of the 26 patients. All of these five had laparotomy. Intestinal necrosis requiring resection was confirmed in four and the other was found to have NEC but no necrosis was identified. In 21 patients US did not suggest intestinal necrosis. Of these, only one had surgery in whom NEC but no necrosis was identified. The remaining 20 responded to medical treatment for NEC and were assumed not to have had intestinal necrosis based on improvement without surgical intervention. The sensitivity, specificity, positive predictive value and negative predictive values of US for the detection of bowel necrosis were calculated as 100, 95.4, 80.0, and 100 %, respectively.ConclusionOur prospective findings suggest that abdominal US can identify those infants with NEC who may need surgery by detecting bowel necrosis (prior to the development of perforation or medical deterioration) with high sensitivity and specificity. Early surgical intervention in the clinical pathway of NEC may lead to improved outcomes