324 results on '"Patterson, Tucker A."'
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2. QSAR models for predicting in vivo reproductive toxicity
3. List of contributors
4. Decision forest—a machine learning algorithm for QSAR modeling
5. Determining high priority disinfection byproducts based on experimental aquatic toxicity data and predictive models: Virtual screening and in vivo study
6. Machine Learning for Predicting Gas Adsorption Capacities of Metal Organic Framework
7. Machine Learning for Predicting Organ Toxicity
8. Mold2 Descriptors Facilitate Development of Machine Learning and Deep Learning Models for Predicting Toxicity of Chemicals
9. Analyzing 3D structures of the SARS-CoV-2 main protease reveals structural features of ligand binding for COVID-19 drug discovery
10. Machine Learning for Predicting Gas Adsorption Capacities of Metal Organic Framework
11. Mold2 Descriptors Facilitate Development of Machine Learning and Deep Learning Models for Predicting Toxicity of Chemicals
12. Machine Learning for Predicting Organ Toxicity
13. The NMDA Receptor System and Developmental Neurotoxicity
14. BERT-based language model for accurate drug adverse event extraction from social media: implementation, evaluation, and contributions to pharmacovigilance practices
15. Machine Learning Models for Predicting Liver Toxicity
16. Phencyclidine (PCP)-induced neurotoxicity and behavioral deficits
17. AI-powered drug repurposing for developing COVID-19 treatments
18. Fingerprinting Interactions between Proteins and Ligands for Facilitating Machine Learning in Drug Discovery
19. Machine learning and deep learning approaches for enhanced prediction of hERG blockade: a comprehensive QSAR modeling study
20. Decoding the κ Opioid Receptor (KOR): Advancements in Structural Understanding and Implications for Opioid Analgesic Development.
21. BERT-based language model for accurate drug adverse event extraction from social media: implementation, evaluation, and contributions to pharmacovigilance practices.
22. Application of Nonhuman Primate Models in the Studies of Pediatric Anesthesia Neurotoxicity
23. Machine learning and deep learning for brain tumor MRI image segmentation
24. Review of machine learning and deep learning models for toxicity prediction
25. Developing a SARS-CoV-2 main protease binding prediction random forest model for drug repurposing for COVID-19 treatment
26. Informing selection of drugs for COVID-19 treatment through adverse events analysis
27. The NMDA Receptor System and Developmental Neurotoxicity
28. Protective Effects of Xenon on Propofol-Induced Neurotoxicity in Human Neural Stem Cell-Derived Models
29. Effects of Xenon-Based Anesthetic Exposure on the Expression Levels of Polysialic Acid Neural Cell Adhesion Molecule (PSA-NCAM) on Human Neural Stem Cell–Derived Neurons
30. Lipidomics reveals a systemic energy deficient state that precedes neurotoxicity in neonatal monkeys after sevoflurane exposure
31. Chapter 4 - Decision forest—a machine learning algorithm for QSAR modeling
32. Chapter 19 - EADB—A database providing curated data for developing QSAR models to facilitate the assessment of endocrine activity
33. Chapter 23 - QSAR models for predicting in vivo reproductive toxicity
34. Three-Dimensional Structural Insights Have Revealed the Distinct Binding Interactions of Agonists, Partial Agonists, and Antagonists with the µ Opioid Receptor
35. Preface: 2022 International Conference on Neuroprotective Agents
36. Development of a primate model to evaluate the effects of ketamine and surgical stress on the neonatal brain
37. Relationship between ketamine-induced developmental neurotoxicity and NMDA receptor-mediated calcium influx in neural stem cell-derived neurons
38. Neural Cell Adhesion Molecules in Normal and Abnormal Neural Development
39. List of Contributors
40. Neurite Development and Neurotoxicity
41. Machine learning models for rat multigeneration reproductive toxicity prediction
42. Protective effect of acetyl-l-carnitine on propofol-induced toxicity in embryonic neural stem cells
43. Astrocytes
44. Oligodendrocytes [Myelin-related Glial Cells in the Central Nervous System (CNS)]
45. Schwann Cells
46. Neurons-Nerve Cells
47. Neuroendocrine Cells
48. Ketamine-Induced Toxicity in Neurons Differentiated from Neural Stem Cells
49. Machine Learning Models for Predicting Cytotoxicity of Nanomaterials
50. The Effects of Taurine in a Rodent Model of Aging
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