AIMC Topic: Neoplasm Invasiveness

Clear Filters Showing 21 to 30 of 198 articles

Development of a MVI associated HCC prognostic model through single cell transcriptomic analysis and 101 machine learning algorithms.

Scientific reports Mar 7, 2025
Hepatocellular carcinoma (HCC) is an exceedingly aggressive form of cancer that often carries a poor prognosis, especially when it is complicated by the presence of microvascular invasion (MVI). Identifying patients at high risk of MVI is crucial for...
Humans Machine Learning Precision Medicine Carcinoma, Hepatocellular Single-Cell Gene Expression Analysis Immunotherapy Gene Expression Regulation, Neoplastic Treatment Outcome Prognosis Clinical Decision-Making Biomarkers, Tumor Risk Assessment Liver Neoplasms Datasets as Topic Kaplan-Meier Estimate Microvessels Immune Checkpoint Proteins Neoplasm Invasiveness Liver Meta-Analysis as Topic Mutation
View on PubMed DOI

GALR1 and PENK serve as potential biomarkers in invasive non-functional pituitary neuroendocrine tumours.

Gene Feb 28, 2025
BACKGROUND: Some nonfunctioning pituitary neuroendocrine tumor (NFPitNET) can show invasive growth, which increases the difficulty of surgery and indicates a poor prognosis. However, the molecular mechanism related to invasiveness remains to be furth...
Pituitary Neoplasms Neuroendocrine Tumors Protein Interaction Maps Machine Learning Humans Gene Regulatory Networks Biomarkers, Tumor Gene Expression Regulation, Neoplastic Gene Expression Profiling Signal Transduction Cell Line, Tumor Neoplasm Invasiveness
View on PubMed DOI

Preoperative diagnosis of meningioma sinus invasion based on MRI radiomics and deep learning: a multicenter study.

Cancer imaging : the official publication of the International Cancer Imaging Society Feb 28, 2025
OBJECTIVE: Exploring the construction of a fusion model that combines radiomics and deep learning (DL) features is of great significance for the precise preoperative diagnosis of meningioma sinus invasion.
Cranial Sinuses Humans Retrospective Studies Neoplasm Invasiveness Male Female Preoperative Care Middle Aged Aged Meningioma Deep Learning Adult Meningeal Neoplasms ROC Curve Radiomics Magnetic Resonance Imaging
View on PubMed DOI

Accelerated Multi-b-Value DWI Using Deep Learning Reconstruction: Image Quality Improvement and Microvascular Invasion Prediction in BCLC Stage A Hepatocellular Carcinoma.

Academic radiology Feb 17, 2025
RATIONALE AND OBJECTIVES: To investigate the effect of accelerated deep-learning (DL) multi-b-value DWI (Mb-DWI) on acquisition time, image quality, and predictive ability of microvascular invasion (MVI) in BCLC stage A hepatocellular carcinoma (HCC)...
Female Aged Adult Male Middle Aged Humans Prospective Studies Quality Improvement Image Interpretation, Computer-Assisted Signal-To-Noise Ratio Diffusion Magnetic Resonance Imaging Microvessels Deep Learning Liver Neoplasms Carcinoma, Hepatocellular Neoplasm Invasiveness Neoplasm Staging
View on PubMed DOI

Machine learning model based on preoperative contrast-enhanced CT and clinical features to predict perineural invasion in gallbladder carcinoma patients.

European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology Feb 16, 2025
BACKGROUND: Perineural invasion (PNI) is an independent prognostic risk factor for gallbladder carcinoma (GBC). However, there is currently no reliable method for the preoperative noninvasive prediction of PNI.
Female Risk Factors Aged Adult Male Middle Aged Contrast Media Neoplasm Invasiveness Neoplasm Staging Humans Peripheral Nerves Machine Learning Gallbladder Neoplasms Retrospective Studies Tomography, X-Ray Computed
View on PubMed DOI

Radiomics integration based on intratumoral and peritumoral computed tomography improves the diagnostic efficiency of invasiveness in patients with pure ground-glass nodules: a machine learning, cross-sectional, bicentric study.

Journal of cardiothoracic surgery Feb 11, 2025
BACKGROUND: Radiomics has shown promise in the diagnosis and prognosis of lung cancer. Here, we investigated the performance of computed tomography-based radiomic features, extracted from gross tumor volume (GTV), peritumoral volume (PTV), and GTV + ...
Prognosis Radiomics Cross-Sectional Studies Retrospective Studies Neoplasm Invasiveness Humans Male Tomography, X-Ray Computed Adenocarcinoma of Lung Machine Learning Middle Aged Female Lung Neoplasms Aged
View on PubMed DOI

Identifying invasiveness to aid lung adenocarcinoma diagnosis using deep learning and pathomics.

Scientific reports Feb 10, 2025
Most classification efforts for primary subtypes of lung adenocarcinoma (LUAD) have not yet been integrated into clinical practice. This study explores the feasibility of combining deep learning and pathomics to identify tumor invasiveness in LUAD pa...
ROC Curve Humans Lung Neoplasms Retrospective Studies Neoplasm Invasiveness Female Aged Area Under Curve Male Adenocarcinoma of Lung Middle Aged Deep Learning
View on PubMed DOI

A Deep Reinforcement Learning-Based Feature Selection Method for Invasive Disease Event Prediction Using Imbalanced Follow-Up Data.

IEEE journal of biomedical and health informatics Feb 10, 2025
The machine learning-based model is a promising paradigm for predicting invasive disease events (iDEs) in breast cancer. Feature selection (FS) is an essential preprocessing technique employed to identify the pertinent features for the prediction mod...
Neoplasm Invasiveness Datasets as Topic Reinforcement Machine Learning Humans Prognosis Female Breast Neoplasms
View on PubMed DOI

Deep learning and radiomics for gastric cancer serosal invasion: automated segmentation and multi-machine learning from two centers.

Journal of cancer research and clinical oncology Feb 3, 2025
OBJECTIVE: The objective of this study is to develop an automated method for segmenting spleen computed tomography (CT) images using a deep learning model. This approach is intended to address the limitations of manual segmentation, which is known to...
Neoplasm Invasiveness Spleen Middle Aged Deep Learning Image Processing, Computer-Assisted Nomograms Humans Machine Learning Tomography, X-Ray Computed Female Aged Adult Stomach Neoplasms Radiomics Male
View on PubMed DOI

Integration of MRI radiomics and clinical data for preoperative prediction of vascular invasion in breast cancer: A deep learning approach.

Magnetic resonance imaging Jan 27, 2025
BACKGROUND: Accurate preoperative prediction of vascular invasion in breast cancer is crucial for surgical planning and patient management. MRI radiomics has shown promise in enhancing diagnostic precision. This study aims to evaluate the effectivene...
Deep Learning Adult Image Processing, Computer-Assisted Contrast Media Neoplasm Invasiveness Sensitivity and Specificity Magnetic Resonance Imaging Humans Breast Breast Neoplasms Image Interpretation, Computer-Assisted Retrospective Studies Radiomics Preoperative Care Female Diffusion Magnetic Resonance Imaging Middle Aged Aged
View on PubMed DOI
Popular Topics
Recent Journals