Predicting Nanoparticle Delivery to Tumors Using Machine Learning and Artificial Intelligence Approaches.
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| Title: | Predicting Nanoparticle Delivery to Tumors Using Machine Learning and Artificial Intelligence Approaches. |
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| Authors: | Lin Z; Department of Environmental and Global Health, College of Public Health and Health Professions, University of Florida, Gainesville, FL, USA.; Center for Environmental and Human Toxicology, University of Florida, Gainesville, FL, USA.; Institute of Computational Comparative Medicine, Kansas State University, Manhattan, KS, USA.; Department of Anatomy and Physiology, College of Veterinary Medicine, Kansas State University, Manhattan, KS, USA., Chou WC; Department of Environmental and Global Health, College of Public Health and Health Professions, University of Florida, Gainesville, FL, USA.; Center for Environmental and Human Toxicology, University of Florida, Gainesville, FL, USA.; Institute of Computational Comparative Medicine, Kansas State University, Manhattan, KS, USA.; Department of Anatomy and Physiology, College of Veterinary Medicine, Kansas State University, Manhattan, KS, USA., Cheng YH; Institute of Computational Comparative Medicine, Kansas State University, Manhattan, KS, USA.; Department of Anatomy and Physiology, College of Veterinary Medicine, Kansas State University, Manhattan, KS, USA., He C; Department of Biostatistics, College of Public Health and Health Professions, University of Florida, Gainesville, FL, USA., Monteiro-Riviere NA; Nanotechnology Innovation Center of Kansas State, Kansas State University, Manhattan, KS, USA.; Center for Chemical Toxicology Research and Pharmacokinetics, North Carolina State University, Raleigh, NC, USA., Riviere JE; Center for Chemical Toxicology Research and Pharmacokinetics, North Carolina State University, Raleigh, NC, USA.; 1Data Consortium, Kansas State University, Olathe, KS, USA. |
| Source: | International journal of nanomedicine [Int J Nanomedicine] 2022 Mar 24; Vol. 17, pp. 1365-1379. Date of Electronic Publication: 2022 Mar 24 (Print Publication: 2022). |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: DOVE Medical Press Country of Publication: New Zealand NLM ID: 101263847 Publication Model: eCollection Cited Medium: Internet ISSN: 1178-2013 (Electronic) Linking ISSN: 11769114 NLM ISO Abbreviation: Int J Nanomedicine Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 1178-2013 |
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| DOI: | 10.2147/IJN.S344208 |
