head and neck cancer
PulseAugur coverage of head and neck cancer — every cluster mentioning head and neck cancer across labs, papers, and developer communities, ranked by signal.
2 day(s) with sentiment data
-
Specialized LMM shows promise for PET/CT cancer diagnosis
Researchers have developed a specialized Large Multimodal Model (LMM) by fine-tuning LLaVA-NeXT to interpret PET/CT scans for head and neck cancer. This specialized model significantly outperformed generalist models lik…
-
New AI Network Improves Head and Neck Cancer Radiology Reports
Researchers have developed SGRNet, a novel network designed to improve the accuracy of radiological reports for head and neck cancer. This system addresses challenges like hallucination risks and data scarcity by reform…
-
New Bayesian network method improves cancer prognosis modeling
A new research paper published on arXiv proposes a method called the Survival-Aware Bayesian network to improve clinical prognostic modeling. This approach addresses the limitations of binarizing survival outcomes, a co…
-
Foundation models improve head and neck cancer metastasis prediction
Researchers have developed a new method for predicting distant metastasis in head and neck cancer using foundation model-derived embeddings from computed tomography (CT) scans. This approach, which requires minimal prep…
-
Foundation models show promise in cancer prediction but face generalization challenges
Researchers are exploring the use of foundation models for predicting head and neck cancer recurrence, comparing their performance against traditional radiomics and deep learning methods. One study found that a foundati…
-
AI synthesizes PET images from CT scans for head and neck cancer
Researchers have developed a novel deep learning framework designed to synthesize PET-like images from standard CT scans for head and neck cancer patients. This dual-path system combines a regression U-Net for quantitat…
-
AI model predicts dysphagia risk in cancer patients using patient-reported data
Researchers have developed a novel two-stage stacking model to predict the risk of dysphagia, a common side effect of head and neck cancer treatment. This model integrates patient-reported outcomes (PROs) with structure…
-
New AI frameworks enhance clinical survival prediction and interpretability · 4 sources tracked
Researchers have developed two new frameworks for improving survival prediction in clinical settings. ChronoSurv utilizes a heterogeneous hierarchical directed graph to model patient care as a progression-aware clinical…