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Of the false negatives (n = 28), 89% were benign cysts (n = 25), most of which (n = 19) were < 10 mm in diameter; the remaining three consisted of a PNET, a case of chronic pancreatitis, and a lesion of undetermined type. Second real-world evaluation cohort...
Deep learning may require knowledge of many levels of terminology or data features, but such in-depth learning typically achieves excellent strength and flexibility when tackling complex real-world problems. Figure 1 shows our proposed methodology. Fig. 1 The framework of research methodology Full ...
Despite these limitations, we believe that our multinational validation confirms the potential for our approach while highlighting the real-world challenges in such studies. In conclusion, the CNN-based AI model trained using a privacy-protecting federated learning approach is effective in detecting CT ...
The most commonly used diagnostic tool for COVID-19 is real-time reverse transcriptase chain reaction (RT-PCR) on nasopharyngeal swab samples from subjects [2]. In addition, the researchers found that CT scan images of the chest of patients with confirmed COVID-19 had typical features such ...
In real-world scenarios, it is time-consuming or even impractical to collect data from each new target domain to fine-tune the model before deploying it. In future work, we will employ domain generalization technology to address the domain shift problem in multi-center study. The goal of ...
However, for the majority of real-life problems, data is not abundant. In fact, few are the situations where there is an abundance of data, such as the ImageNet [22] dataset. To overcome this issue, one could rely on two techniques: data augmentation and transfer learning. In this work...
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Overfitting, external validation & model interpretability: To gauge the generalizability and real-world applicability of our models, external validation using an independent dataset is imperative. The absence of external validation in this study could be considered as a limitation that restricts our abilit...
None of the models were validated using imaging-based or clinical-based assessment or simulated the evolution of synthetic or real stroke lesions on MR or CT images. None of these papers also included an MR or CT image of an ischemic stroke. In addition, these models used simplified ...