Journal of applied clinical medical physics
Apr 5, 2025
BACKGROUND: The use of deep learning-based auto-contouring algorithms in various treatment planning services is increasingly common. There is a notable deficit of commercially or publicly available models trained on large or diverse datasets containi...
OBJECTIVE: To develop an automated method for the joint and consistent evaluation of emphysema and mortality risk that provides quantification of data and model uncertainty.
Artificial intelligence makes strides in specialized diagnostics but faces challenges in complex clinical scenarios, such as rare disease diagnosis and emergency condition identification. To address these limitations, we develop Meta General Practiti...
IEEE journal of biomedical and health informatics
Apr 4, 2025
In the field of diagnosing lung diseases, the application of neural networks (NNs) in image classification exhibits significant potential. However, NNs are considered "black boxes," making it difficult to discern their decision-making processes, ther...
BACKGROUND: This study aimed to preoperatively predict Ki-67 proliferation levels in patients with pancreatic solid pseudopapillary neoplasm (pSPN) using radiomics features extracted from arterial phase helical CT images.
International journal of radiation oncology, biology, physics
Apr 3, 2025
PURPOSE: Bridging radiation therapy (BRT) is effective for local control in patients with relapsed or refractory large B cell lymphoma who are undergoing chimeric antigen receptor (CAR) T cell therapy. We hypothesized that adaptive BRT (ABRT), which ...
Radiomics allows extraction from medical images of quantitative features that are able to reveal tissue patterns that are generally invisible to human observers. Despite the challenges in visually interpreting radiomic features and the computational ...
OBJECTIVE: Distal radius fractures account for 12%-17% of all fractures, with accurate classification being crucial for proper treatment planning. Studies have shown that in emergency settings, the misdiagnosis rate of hand/wrist fractures can reach ...
BACKGROUND: Large language models (LLMs), such as ChatGPT, have demonstrated impressive capabilities in various natural language processing tasks, particularly in text generation. However, their effectiveness in summarizing radiology report impressio...
Multimodal Federated Learning (MFL) has emerged as a collaborative paradigm for training models across decentralized devices, harnessing various data modalities to facilitate effective learning while respecting data ownership. In this realm, notably,...
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