AIMC Topic: Deep Learning
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Development and validation of MRI-derived deep learning score for non-invasive prediction of PD-L1 expression and prognostic stratification in head and neck squamous cell carcinoma.
Cancer imaging : the official publication of the International Cancer Imaging Society
Feb 16, 2025
BACKGROUND: Immunotherapy has revolutionized the treatment landscape for head and neck squamous cell carcinoma (HNSCC) and PD-L1 combined positivity score (CPS) scoring is recommended as a biomarker for immunotherapy. Therefore, this study aimed to d...
Advanced prognostic modeling with deep learning: assessing long-term outcomes in liver transplant recipients from deceased and living donors.
Journal of translational medicine
Feb 16, 2025
BACKGROUND: Predicting long-term outcomes in liver transplantation remain a challenging endeavor. This research aims to harness the power of deep learning to develop an advanced prognostic model for assessing long-term outcomes, with a specific focus...
RNA-protein interaction prediction using network-guided deep learning.
Communications biology
Feb 16, 2025
Accurate computational determination of RNA-protein interactions remains challenging, particularly when encountering unknown RNAs and proteins. The limited number of RNAs and their flexibility constrained the effectiveness of the deep-learning models...
A practical deep learning model for core temperature prediction of specialized workers in high-temperature environments.
Journal of thermal biology
Feb 16, 2025
The health issues of hazardous operations in high-temperature environments are increasing concerns to the public, especially since global warming and extreme weather conditions have made the high-temperature work more frequent and harsher. The abnorm...
Learning temporal regularized spatial-aware deep correlation filter tracking via adaptive channel selection.
Neural networks : the official journal of the International Neural Network Society
Feb 15, 2025
In recent years, deep correlation filters have demonstrated outstanding performance in robust object tracking. Nevertheless, the correlation filters encounter challenges in managing huge occlusion, target deviation, and background clutter due to the ...
CT-Based Deep Learning Predicts Prognosis in Esophageal Squamous Cell Cancer Patients Receiving Immunotherapy Combined with Chemotherapy.
Academic radiology
Feb 15, 2025
RATIONALE AND OBJECTIVES: Immunotherapy combined with chemotherapy has improved outcomes for some esophageal squamous cell carcinoma (ESCC) patients, but accurate pre-treatment risk stratification remains a critical gap. This study constructed a deep...
Breaking barriers: noninvasive AI model for BRAF mutation identification.
International journal of computer assisted radiology and surgery
Feb 15, 2025
OBJECTIVE: BRAF is the most common mutation found in thyroid cancer and is particularly associated with papillary thyroid carcinoma (PTC). Currently, genetic mutation detection relies on invasive procedures. This study aimed to extract radiomic featu...
Identifying RNA-small Molecule Binding Sites Using Geometric Deep Learning with Language Models.
Journal of molecular biology
Feb 15, 2025
RNAs are emerging as promising therapeutic targets, yet identifying small molecules that bind to them remains a significant challenge in drug discovery. This underscores the crucial role of computational modeling in predicting RNA-small molecule bind...
Neighbor-aware calibration of segmentation networks with penalty-based constraints.
Medical image analysis
Feb 15, 2025
Ensuring reliable confidence scores from deep neural networks is of paramount significance in critical decision-making systems, particularly in real-world domains such as healthcare. Recent literature on calibrating deep segmentation networks has res...
Adaptable graph neural networks design to support generalizability for clinical event prediction.
Journal of biomedical informatics
Feb 15, 2025
OBJECTIVE: While many machine learning and deep learning-based models for clinical event prediction leverage various data elements from electronic healthcare records such as patient demographics and billing codes, such models face severe challenges w...
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