UWB-Fat estimates subcutaneous fat thickness with 0.63 mm RMSE using UWB radar signals and a physics-inspired model on 15 participants, as a non-intrusive caliper replacement.
A systematic review of quantum machine learning for digital health
3 Pith papers cite this work. Polarity classification is still indexing.
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The work develops a reflective LLM-based storytelling agent for older adults that integrates argumentation schemes and argument mining with knowledge graphs and user modeling to generate and inspect personalized health narratives, evaluated through expert design and user studies showing recognition,
A Pretty Good Measurement classifier reformulates multi-class radiomics as quantum state discrimination and achieves competitive performance on NSCLC subtyping and PCa risk tasks.
citing papers explorer
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UWB-Fat: Non-Intrusive Body Fat Measurement Using Commodity Ultra-Wideband Radar
UWB-Fat estimates subcutaneous fat thickness with 0.63 mm RMSE using UWB radar signals and a physics-inspired model on 15 participants, as a non-intrusive caliper replacement.
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A Reflective Storytelling Agent for Older Adults: Integrating Argumentation Schemes and Argument Mining in LLM-Based Personalised Narratives
The work develops a reflective LLM-based storytelling agent for older adults that integrates argumentation schemes and argument mining with knowledge graphs and user modeling to generate and inspect personalized health narratives, evaluated through expert design and user studies showing recognition,
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Pretty Good Measurement for Radiomics: A Quantum-Inspired Multi-Class Classifier for Lung Cancer Subtyping and Prostate Cancer Risk Stratification
A Pretty Good Measurement classifier reformulates multi-class radiomics as quantum state discrimination and achieves competitive performance on NSCLC subtyping and PCa risk tasks.