Diagnostic and interventional radiology (Ankara, Turkey)
Jan 16, 2025
PURPOSE: Patients with advanced non-small cell lung cancer (NSCLC) have varying responses to immunotherapy, but there are no reliable, accepted biomarkers to accurately predict its therapeutic efficacy. The present study aimed to construct individual...
IEEE transactions on bio-medical engineering
Jan 15, 2025
Data-driven methods for lesion generation are quickly emerging due to the need for realistic imaging targets for image quality assessment and virtual clinical trials. We proposed a generative adversarial network (GAN) architecture for conditional gen...
Predicting drug-target interactions (DTIs) is a crucial step in the development of new drugs and drug repurposing. In this paper, we propose a novel drug-target prediction model called MCF-DTI. The model utilizes the SMILES representation of drugs an...
Deep learning (DL) methods have demonstrated remarkable effectiveness in assisting with lung cancer risk prediction tasks using computed tomography (CT) scans. However, the lack of comprehensive comparison and validation of state-of-the-art (SOTA) mo...
OBJECTIVES: To evaluate the image quality and lung nodule detectability of ultralow-dose CT (ULDCT) with adaptive statistical iterative reconstruction-V (ASiR-V) post-processed using a deep learning image reconstruction (DLIR)-based image domain comp...
Non-small cell lung adenocarcinoma (LUAD) is a markedly heterogeneous disease, with its underlying molecular mechanisms and prognosis prediction presenting ongoing challenges. In this study, we integrated data from multiple public datasets, including...
BACKGROUND: Thoracic SMARCA4-deficient undifferentiated tumors (SMARCA4-UT) exhibit a notably aggressive phenotype, which is associated with poor patient survival outcomes. These tumors are generally resistant to conventional cytotoxic chemotherapy, ...
OBJECTIVE: The LungFlag risk prediction model uses individualized clinical variables to identify individuals at high-risk of non-small cell lung cancer (NSCLC) for screening with low-dose computed tomography (LDCT). This study evaluates the cost-effe...
Clinical decision-making is driven by multimodal data, including clinical notes and pathological characteristics. Artificial intelligence approaches that can effectively integrate multimodal data hold significant promise in advancing clinical care. H...
OBJECTIVES: The pairing of immunotherapy and radiotherapy in the treatment of locally advanced nonsmall cell lung cancer (NSCLC) has shown promise. By combining radiotherapy with immunotherapy, the synergistic effects of these modalities not only bol...
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