- Non|invasive multimodal CT deep learning biomarker to predict ...🔍
- CT|based multimodal deep learning for non|invasive overall survival ...🔍
- Journal for ImmunoTherapy of Cancer on X🔍
- Deep learning–radiomics integrated noninvasive detection of ...🔍
- Multimodal deep learning for personalized renal cell carcinoma ...🔍
- Integrating deep learning CT|scan model🔍
- Deep|Learning|Based Predictive Imaging Biomarker Model ...🔍
- Deep learning provides a new computed tomography|based ...🔍
Non|invasive multimodal CT deep learning biomarker to predict ...
Non-invasive multimodal CT deep learning biomarker to predict ...
By extracting deep learning features from contrast enhanced and non-contrast enhanced CT, we constructed the LUNAI-fCT model as an imaging ...
Non-invasive multimodal CT deep learning biomarker to predict ...
We constructed the LUNAI-fCT model as an imaging biomarker, which can non-invasively predict pathological complete response in neoadjuvant immunochemotherapy ...
CT-based multimodal deep learning for non-invasive overall survival ...
To develop a deep learning model combining CT scans and clinical information to predict overall survival in advanced hepatocellular ...
CT-based multimodal deep learning for non-invasive overall survival ...
To develop a deep learning model combining CT scans and clinical information to predict overall survival in advanced hepatocellular ...
Non-invasive multimodal CT deep learning biomarker to predict ...
Dive into the research topics of 'Non-invasive multimodal CT deep learning biomarker to predict pathological complete response of non-small cell lung cancer ...
Journal for ImmunoTherapy of Cancer on X: "Check out the recent ...
... invasive multimodal CT deep learning biomarker to predict pathological complete response of non-small cell lung cancer following ...
Journal for ImmunoTherapy of Cancer on X: "New #JITC Article: Non ...
New #JITC Article: Non-invasive multimodal CT deep learning biomarker to predict pathological complete response of non-small cell lung ...
Deep learning–radiomics integrated noninvasive detection of ...
This study focused on a novel strategy that combines deep learning and radiomics to predict epidermal growth factor receptor (EGFR) ...
Multimodal deep learning for personalized renal cell carcinoma ...
Methods: The proposed framework comprises three modules: a 3D image feature extractor, clinical variable selection, and survival prediction.
Integrating deep learning CT-scan model, biological and clinical ...
We show that neural network analysis of CT-scans brings unique prognosis information, although it is correlated with other markers of severity ( ...
Deep-Learning-Based Predictive Imaging Biomarker Model ... - MDPI
The semantic features extracted from CT images also contributed to accurate predictions. The study suggests that this AI-based model in combination with CT ...
Deep learning provides a new computed tomography-based ...
Original Article. Deep learning provides a new computed tomography-based prognostic biomarker for recurrence prediction in high-grade serous ovarian cancer.
The future of multimodal artificial intelligence models for integrating ...
Leveraging the MIMIC database, they demonstrate improvement in predicting various healthcare operations including lung lesion detection, 48-hour mortality, and ...
Preoperative CT-based Deep Learning Model for Predicting ...
Deep learning models have the potential for lung cancer prognostication, but model output as an independent prognostic factor must be validated ...
Artificial intelligence for multimodal data integration in oncology
mutation estimation in colorectal cancer using a deep learning method based · on ct ... Multimodal deep learning models for the prediction of ...
Deep Learning with Multimodal Integration for Predicting ... - MDPI
Data passed through the convolutional neural network (CNN) is non-linearly mapped throughout the transformation linking the input and output spaces of networks, ...
Non-invasive multimodal CT deep learning biomarker to predict ...
Non-invasive multimodal CT deep learning biomarker to predict pathological complete response of non-small cell lung cancer following neoadjuvant ...
(PDF) CT-based multimodal deep learning for non-invasive overall ...
An AI-based prognostic model was developed for advanced HCC using multi-national patients. ... The model extracts spatial-temporal information ...
Survival prediction in diffuse large B-cell lymphoma patients
Their PET and CT images were fused to construct the multimodal PET-CT images using a deep learning fusion network. Then the deep features were ...
Real-world and clinical trial validation of a deep learning radiomic ...
Methods: We developed and validated a deep learning radiomic biomarker using an internally curated real-world dataset (RWD) of 2,010 stage IV ...