| Drug-induced liver injury severity and toxicity (DILIst): binary classification of 1279 drugs by human hepatotoxicity S Thakkar, T Li, Z Liu, L Wu, R Roberts, W Tong Drug discovery today 25 (1), 201-208, 2020 | 115 | 2020 |
| DeepDILI: deep learning-powered drug-induced liver injury prediction using model-level representation T Li, W Tong, R Roberts, Z Liu, S Thakkar Chemical research in toxicology 34 (2), 550-565, 2020 | 68 | 2020 |
| DeepCarc: Deep learning-powered carcinogenicity prediction using model-level representation T Li, W Tong, R Roberts, Z Liu, S Thakkar Frontiers in artificial intelligence 4, 757780, 2021 | 38 | 2021 |
| Deep learning on high-throughput transcriptomics to predict drug-induced liver injury T Li, W Tong, R Roberts, Z Liu, S Thakkar Frontiers in bioengineering and biotechnology 8, 562677, 2020 | 37 | 2020 |
| DICTrank: The largest reference list of 1318 human drugs ranked by risk of drug-induced cardiotoxicity using FDA labeling Y Qu, T Li, Z Liu, D Li, W Tong Drug Discovery Today 28 (11), 103770, 2023 | 13 | 2023 |
| Adaptability of AI for safety evaluation in regulatory science: A case study of drug-induced liver injury S Connor, T Li, R Roberts, S Thakkar, Z Liu, W Tong Frontiers in artificial intelligence 5, 1034631, 2022 | 13 | 2022 |
| DeepAmes: A deep learning-powered Ames test predictive model with potential for regulatory application T Li, Z Liu, S Thakkar, R Roberts, W Tong Regulatory Toxicology and Pharmacology 144, 105486, 2023 | 12 | 2023 |
| Scoring matrix for unstandardized data in entity resolution X Li, JR Talburt, T Li 2018 International Conference on Computational Science and Computational …, 2018 | 11 | 2018 |
| Generation of a drug-induced renal injury list to facilitate the development of new approach methodologies for nephrotoxicity S Connor, T Li, Y Qu, RA Roberts, W Tong Drug discovery today, 103938, 2024 | 10 | 2024 |
| Evaluation of QSAR models for predicting mutagenicity: outcome of the Second Ames/QSAR international challenge project A Furuhama, A Kitazawa, J Yao, CE Matos Dos Santos, J Rathman, ... SAR and QSAR in Environmental Research 34 (12), 983-1001, 2023 | 10 | 2023 |
| TransOrGAN: an artificial intelligence mapping of rat transcriptomic profiles between organs, ages, and sexes T Li, R Roberts, Z Liu, W Tong Chemical Research in Toxicology 36 (6), 916-925, 2023 | 10 | 2023 |
| Brain cortical structure and executive function in children may be influenced by parental choices of infant diets T Li, TM Badger, BJ Bellando, ST Sorensen, X Lou, X Ou American Journal of Neuroradiology 41 (7), 1302-1308, 2020 | 7 | 2020 |
| Cortical Morphometry is Associated with Neuropsychological Function in Healthy 8‐Year‐Old Children T Li, GS McCorkle, DK Williams, TM Badger, X Ou Journal of Neuroimaging 30 (6), 833-842, 2020 | 6 | 2020 |
| Dice: a drug indication classification and encyclopedia for ai-based indication extraction A Bhatt, R Roberts, XI Chen, T Li, S Connor, Q Hatim, M Mikailov, W Tong, ... Frontiers in Artificial Intelligence 4, 711467, 2021 | 5 | 2021 |
| Best practice and reproducible science are required to advance artificial intelligence in real-world applications Z Liu, T Li, S Connor, S Thakkar, R Roberts, W Tong Briefings in bioinformatics 23 (4), bbac237, 2022 | 3 | 2022 |
| When entity resolution meets deep learning, is similarity measure necessary? X Li, JR Talburt, T Li, X Liu Advances in Artificial Intelligence and Applied Cognitive Computing …, 2021 | 3 | 2021 |
| Correlations between sleep disturbance and brain cortical morphometry in healthy children X Na, T Li, LJ Larson-Prior, CE Baldwin, TM Badger, X Ou Sleep Science and Practice 5, 1-8, 2021 | 2 | 2021 |
| Scoring matrix combined with machine learning for heterogeneously structured entity resolution X Li, JR Talburt, T Li, X Liu Journal of Computing Sciences in Colleges 34 (7), 38-45, 2019 | 2 | 2019 |
| Bridging organ transcriptomics for advancing multiple organ toxicity assessment with a generative AI approach T Li, X Chen, W Tong NPJ Digital Medicine 7 (1), 310, 2024 | 1 | 2024 |
| Assessing the performance of large language models in literature screening for pharmacovigilance: a comparative study D Li, L Wu, M Zhang, S Shpyleva, YC Lin, HY Huang, T Li, J Xu Frontiers in Drug Safety and Regulation 4, 1379260, 2024 | 1 | 2024 |
