AI-Enhanced Lung Cancer Prediction: A Hybrid Model's Precision Triumph

Information Science, Computer Science, Artificial Intelligence, Medicine, Respiratory System, Medical Imaging, Oncology,
lung cancer   deep learning   convolutional neural network   bidirectional long short-term memory network   text classification   natural language processing   precision medicine  

Background Introduction Lung cancer, as one of the most prevalent and deadly malignant tumors worldwide, continues to pose many challenges in modern healthcare. According to literature statistics, the five-year survival rate for lung cancer patients is extremely low, consistently ranking it among the top three causes of cancer death globally. Due t...

Partial Domain Adaptation for Building Borehole Lithology Model Under Weaker Geological Prior

Earth Sciences, Geochemistry, Geology, Geophysics, Information Science, Automation, Artificial Intelligence,
lithology identification   partial domain adaptation   sample transferability weighting   convolutional neural network   channel attention mechanism   target sample reconstruction   geological exploration  

Report on the Paper: “Partial Domain Adaptation for Building Borehole Lithology Model Under Weaker Geological Prior” Background and Research Problem Lithology identification plays a critical role in stratigraphic characterization and reservoir exploration. However, existing AI and machine learning-based lithology identification methods face substan...

Identification and Validation of a Prognostic Model Based on Three TLS-Related Genes in Oral Squamous Cell Carcinoma

Medicine, Oral Sciences, Medical Imaging, Oncology, Life Sciences, Biochemistry, Immunology, Genetics,
oral squamous cell carcinoma   tertiary lymphoid structure   prognostic model   immune infiltration   convolutional neural network  

Research Report: Validation and Analysis of a Prognostic Model for Oral Squamous Cell Carcinoma Constructed with TLS-Related Genes Background and Research Motivation Oral Squamous Cell Carcinoma (OSCC) is the most common subtype of Head and Neck Squamous Cell Carcinoma (HNSCC), exhibiting a high tendency for lymph node metastasis, especially to the...

Auto-Segmentation of Neck Nodal Metastases Using Self-Distilled Masked Image Transformer on Longitudinal MR Images

Auto-Segmentation of Neck Nodal Metastases Using Self-Distilled Masked Image Transformer on Longitudinal MR Images

Information Science, Artificial Intelligence, Medicine, Medical Imaging, Oncology,
deep learning   convolutional neural network   neck nodal metastases   auto-segmentation   self-supervised learning   vision transformers  

Potential of Self-Distilling Masked Image Transformer in Longitudinal MRI - Automatic Segmentation of Cervical Lymph Node Metastases Report Introduction In tumor radiotherapy, automatic segmentation technology promises to improve speed and reduce inter-reader variability caused by manual segmentation. In radiotherapy clinical practice, accurate and...

Noninvasive Grading of Glioma by Knowledge Distillation Based Lightweight Convolutional Neural Network

Information Science, Artificial Intelligence, Medicine, Neurosurgery, Oncology,
knowledge distillation   glioma grading   convolutional neural network   lightweight model   image classification  

Review of Non-Invasive Glioma Grading Research: Lightweight Convolutional Neural Networks Based on Knowledge Distillation Background Gliomas are the main tumors of the central nervous system, and early detection is crucial. The World Health Organization (WHO) classifies gliomas from grade I to IV, with grades I and II being low-grade gliomas (LGG) ...