arXiv:2506.20157
Integrating Pharmacokinetics and Pharmacodynamics Modeling with Quantum Regression for Predicting Herbal Compound Toxicity
원문 초록
Herbal compounds present complex toxicity profiles that are often influenced by both intrinsic chemical properties and pharmacokinetics (PK) governing absorption and clearance. In this study, we develop a quantum regression model to predict acute toxicity severity for herbal-derived compounds by integrating toxicity data from NICEATM with pharmacological features from TCMSP.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Near-Polynomially Competitive Active Logistic Regression
Active Learning for Manifold Gaussian Process Regression
Vector Contrastive Learning For Pixel-Wise Pretraining In Medical Vision
GRASP: Grouped Regression with Adaptive Shrinkage Priors
CAWR: Corruption-Averse Advantage-Weighted Regression for Robust Policy Optimization
Scaling-Up the Pretraining of the Earth Observation Foundation Model PhilEO to the MajorTOM Dataset
토론
이 논문과 연결된 포럼 글이 아직 없습니다.