PURPOSE: This study aimed to develop and evaluate a machine learning model combining clinical, radiomics, and deep learning features derived from PET/CT imaging to predict lymph node metastasis (LNM) in patients with non-small cell lung cancer (NSCLC...
Current problems in diagnostic radiology
Dec 10, 2024
In academic and research settings, computer-aided nodule detection software has been shown to increase accuracy, efficiency, and throughput. However, radiologists need to be familiar with the spectrum of errors that can occur when these algorithms ar...
Journal of vascular and interventional radiology : JVIR
Dec 9, 2024
To assess the feasibility of utilizing a large language model (LLM) in extracting clinically relevant information from healthcare data in patients who have undergone microwave ablation for lung tumors. In this single-center retrospective study, radio...
BACKGROUND: Accurate detection of driver gene mutations is crucial for treatment planning and predicting prognosis for patients with lung cancer. Conventional genomic testing requires high-quality tissue samples and is time-consuming and resource-con...
BACKGROUND: Self-supervised learning (SSL) is an approach to extract useful feature representations from unlabeled data, and enable fine-tuning on downstream tasks with limited labeled examples. Self-pretraining is a SSL approach that uses curated do...
Cell communication and signaling : CCS
Dec 5, 2024
BACKGROUND: Epidermal growth factor receptor (EGFR) T790M mutation often occurs during long durational erlotinib treatment of non-small cell lung cancer (NSCLC) patients, leading to drug resistance and disease progression. Identification of new selec...
BACKGROUND: A growing body of research is using deep learning to explore the relationship between treatment biomarkers for lung cancer patients and cancer tissue morphology on digitized whole slide images (WSIs) of tumour resections. However, these W...
Cancer, a global health threat, demands effective diagnostic solutions to combat its impact on public health, particularly for breast, colon, and lung cancers. Early and accurate diagnosis is essential for successful treatment, prompting the rise of ...
BMC medical informatics and decision making
Dec 4, 2024
BACKGROUND: The digitisation of healthcare records has generated vast amounts of unstructured data, presenting opportunities for improvements in disease diagnosis when clinical coding falls short, such as in the recording of patient symptoms. This st...
Lung cancer (LC) remains one of the leading causes of cancer-related mortality worldwide. With recent technological advances, artificial intelligence (AI) has begun to play a crucial role in improving diagnostic and treatment methods. It is crucial t...
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