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Besides fracture detection, the CNN was also trained to localize the fracture and highlight it with a heatmap. The authors were able to demonstrate that the accuracy in fracture detection by emergency medicine clinicians could be significantly improved with the aid of mentioned CNN [17]. The group also presented their results with a subset of 36′408 wrist radiographs. The network had an AUC of 0.97, a specificity of 93% and sensitivity of 95%. After application of the inclusion/exclusion criteria and addition of supplementary search, 235 articles were included in the final review.
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A previous study37 showed that a pretrained clinical BERT model achieved the state-of-the-art performance and outperformed the baseline (InferSent72) by ~9% accuracy. We evaluated the GatorTron models on NLI using the MedNLI dataset71 and used accuracy for comparison. This study demonstrates the advantages of large pretrained transformer models in the medical domain. GatorTron models can be applied to many other NLP tasks through fine-tuning. We believe that GatorTron will improve the use of clinical narratives in developing various medical AI systems for better healthcare delivery and health outcomes. The task of NLI is to determine whether a conclusion can be inferred from a given sentence—a sentence-level NLP task.
kipper ai essay writer AI’s Essay Writer is a shining example of effectiveness in the field of academic writing. By offering an easy-to-use interface, students can start creating their essays with a simple click. Tecle et al. presented the use of a CNN to diagnose osteoporosis based on cortical thickness of the second metacarpal bone on anteroposterior radiographs of the hand. Furthermore, the presented algorithm was able to autonomically correct the laterality and vertical alignment of the radiographs for better image processing [21]. Kuok et al. developed a computer-aided soft tissue segmentation method using a deep convolutional neural network, to help distinguish tendon tissue from synovial sheath tissue in ultrasound images.
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