AIMC Topic: Neoplasm Grading
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F-FDG PET/CT-based deep learning models and a clinical-metabolic nomogram for predicting high-grade patterns in lung adenocarcinoma.
BMC medical imaging
Apr 28, 2025
BACKGROUND: To develop and validate deep learning (DL) and traditional clinical-metabolic (CM) models based on 18 F-FDG PET/CT images for noninvasively predicting high-grade patterns (HGPs) of invasive lung adenocarcinoma (LUAD).
Artificial intelligence based vision transformer application for grading histopathological images of oral epithelial dysplasia: a step towards AI-driven diagnosis.
BMC cancer
Apr 25, 2025
BACKGROUND: This study aimed to classify dysplastic and healthy oral epithelial histopathological images, according to WHO and binary grading systems, using the Vision Transformer (ViT) deep learning algorithm-a state-of-the-art Artificial Intelligen...
The Role of Artificial Intelligence in the Evaluation of Prostate Pathology.
Pathology international
Apr 14, 2025
Artificial intelligence (AI) is an emerging tool in diagnostic pathology, including prostate pathology. This review summarizes the possibilities offered by AI and also discusses the challenges and risks. AI has the potential to assist in the diagnosi...
A CNN-transformer fusion network for predicting high-grade patterns in stage IA invasive lung adenocarcinoma.
Medical physics
Apr 1, 2025
BACKGROUND: Invasive lung adenocarcinoma (LUAD) with the high-grade patterns (HGPs) has the potential for rapid metastasis and frequent recurrence. Therefore, accurately predicting the presence of high-grade components is crucial for doctors to devel...
Construction of enhanced MRI-based radiomics models using machine learning algorithms for non-invasive prediction of IL7R expression in high-grade gliomas and its prognostic value in clinical practice.
Journal of translational medicine
Mar 31, 2025
BACKGROUND: High-grade gliomas are among the most aggressive and deadly brain tumors, highlighting the critical need for improved prognostic markers and predictive models. Recent studies have identified the expression of IL7R as a significant risk fa...
Interleukin-7 Receptor alpha Subunit
Brain Neoplasms
Proportional Hazards Models
Female
Humans
Glioma
Male
Aged
Multivariate Analysis
Support Vector Machine
Middle Aged
Machine Learning
Adult
Kaplan-Meier Estimate
ROC Curve
Magnetic Resonance Imaging
Algorithms
Radiomics
Receptors, Interleukin-7
Neoplasm Grading
Prognosis
Clinical implications of deep learning based image analysis of whole radical prostatectomy specimens.
Scientific reports
Mar 31, 2025
Prostate cancer (PCa) diagnosis faces significant challenges due to its complex pathological characteristics and insufficient pathologist resources. While deep learning-based image analysis (DLIA) shows promise in enhancing diagnostic accuracy, its a...
Artificial intelligence-based multimodal prediction for nuclear grading status and prognosis of clear cell renal cell carcinoma: a multicenter cohort study.
International journal of surgery (London, England)
Mar 28, 2025
BACKGROUND: The assessment of the International Society of Urological Pathology (ISUP) nuclear grade is crucial for the management and treatment of clear cell renal cell carcinoma (ccRCC). This study aimed to explore the value of using integrated mul...
Deep learning informed multimodal fusion of radiology and pathology to predict outcomes in HPV-associated oropharyngeal squamous cell carcinoma.
EBioMedicine
Mar 22, 2025
BACKGROUND: We aim to predict outcomes of human papillomavirus (HPV)-associated oropharyngeal squamous cell carcinoma (OPSCC), a subtype of head and neck cancer characterized with improved clinical outcome and better response to therapy. Pathology an...
Deep learning based on intratumoral heterogeneity predicts histopathologic grade of hepatocellular carcinoma.
BMC cancer
Mar 18, 2025
OBJECTIVES: The potential of medical imaging to non-invasively assess intratumoral heterogeneity (ITH) is increasingly being recognized. This study aimed to investigate the value of the ITH-based deep learning model for preoperative prediction of his...
A Preoperative CT-based Multiparameter Deep Learning and Radiomic Model with Extracellular Volume Parameter Images Can Predict the Tumor Budding Grade in Rectal Cancer Patients.
Academic radiology
Mar 6, 2025
RATIONALE AND OBJECTIVES: To investigate a computed tomography (CT)-based multiparameter deep learning-radiomic model (DLRM) for predicting the preoperative tumor budding (TB) grade in patients with rectal cancer.
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