The benign and malignant discrimination of pulmonary nodules plays a very important role in diagnosing the extent of lung cancer lesions. There are many methods using Convolutional neural network (CNN) for benign and malignant classification of pulmo...
Compared with histological examination of lung cancer, cytology is less invasive and provides better preservation of complete morphology and detail. However, traditional cytological diagnosis requires an experienced pathologist to evaluate all sectio...
Tumor cellularity (TC) in lung adenocarcinoma slides submitted for molecular testing is important in identifying actionable mutations, but lack of best practice guidelines results in high interobserver variability in TC assessments. An artificial int...
INTRODUCTION: AI software in the form of deep learning-based automatic detection (DLAD) algorithms for chest X-ray (CXR) interpretation have shown success in early detection of lung cancer (LC), however, there remains uncertainty related to clinical ...
PURPOSE: The largest cause of cancer-related fatalities worldwide is lung cancer. The dimensions and positioning of the primary tumor, the presence of lesions, the type of lung cancer like malignant or benign, and the good mental health diagnosis all...
AIM: To develop and validate a machine learning (ML) model based on positron emission tomography/computed tomography (PET/CT) multi-modality fusion radiomics to improve the prediction efficiency of mediastinal-hilar lymph node metastasis (LNM).
AI decision support systems can assist clinicians in planning adaptive treatment strategies that can dynamically react to individuals' cancer progression for effective personalized care. However, AI's imperfections can lead to suboptimal therapeutics...
Journal of X-ray science and technology
Jan 28, 2025
ObjectiveThe goal of this study is to assess the effectiveness of a hybrid deep learning model that combines 3D Auto-encoders with attention mechanisms to detect lung cancer early from CT scan images. The study aims to improve diagnostic accuracy, se...
An efficient novel approach is introduced to predict the effectiveness of chemotherapy treatment in lung cancer by monitoring the serum N-glycome of patients combined with artificial intelligence-based data analysis. The study involved thirty-three l...
The rapid development of artificial intelligence (AI) based tools in pathology laboratories has brought forward unlimited opportunities for pathologists. Promising AI applications used for accomplishing diagnostic, prognostic and predictive tasks are...
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