Harrison Bai

Research output

Research output per year 2011 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024

• 98 Article
• 39 Letter
• 15 Review article
• 12 Comment/debate
• 9 More
  • 4 Conference contribution
  • 4 Editorial
  • 1 Chapter

Research output per year

Research output per year

Search results

• 2024

  MMGK: Multimodality Multiview Graph Representations and Knowledge Embedding for Mild Cognitive Impairment Diagnosis

  Liu, J., Du, H., Guo, R., Bai, H. X., Kuang, H. & Wang, J., Feb 1 2024, In: IEEE Transactions on Computational Social Systems. 11, 1, p. 389-398 10 p.

  Research output: Contribution to journal › Article › peer-review

  • Multimodality 100%
  • Graph Representation 90%
  • multimodality 87%
  • cognitive impairment 83%
  • Knowledge 51%
• 2023

  AC-E Network: Attentive Context-Enhanced Network for Liver Segmentation

  Li, Y., Zou, B., Dai, P., Liao, M., Bai, H. X. & Jiao, Z., Aug 1 2023, In: IEEE Journal of Biomedical and Health Informatics. 27, 8, p. 4052-4061 10 p.

  Research output: Contribution to journal › Article › peer-review

  • Liver 100%
  • Computerized tomography 25%
  • Liver Diseases 23%
  • Datasets 22%
  • Costs and Cost Analysis 17%

• Artificial intelligence and body composition

  Santhanam, P., Nath, T., Peng, C., Bai, H., Zhang, H., Ahima, R. S. & Chellappa, R., Mar 2023, In: Diabetes and Metabolic Syndrome: Clinical Research and Reviews. 17, 3, 102732.

  Research output: Contribution to journal › Review article › peer-review

  • Artificial Intelligence 100%
  • Body Composition 74%
  • Metabolic Diseases 26%
  • Electrocardiography 20%
  • Deep Learning 17%

• Beyond antioxidation: Harnessing the CeO₂ nanoparticles as a renoprotective contrast agent for in vivo spectral CT angiography

  Feng, C., Xiong, Z., Sun, X., Zhou, H., Wang, T., Wang, Y., Bai, H. X., Lei, P. & Liao, W., Aug 2023, In: Biomaterials. 299, 122164.

  Research output: Contribution to journal › Article › peer-review

  • Renoprotective 100%
  • Angiography 68%
  • Cerium oxide 66%
  • Contrast Medium 58%
  • Computed Tomography Angiography 54%

• Brain Tumor Segmentation for Multi-Modal MRI with Missing Information

  Feng, X., Ghimire, K., Kim, D. D., Chandra, R. S., Zhang, H., Peng, J., Han, B., Huang, G., Chen, Q., Patel, S., Bettagowda, C., Sair, H. I., Jones, C., Jiao, Z., Yang, L. & Bai, H., Oct 2023, In: Journal of Digital Imaging. 36, 5, p. 2075-2087 13 p.

  Research output: Contribution to journal › Article › peer-review

  • Magnetic resonance imaging 100%
  • Tumors 97%
  • Brain Neoplasms 89%
  • Brain 78%
  • Neoplasms 30%

• Deep learning-based radiomic nomogram to predict risk categorization of thymic epithelial tumors: A multicenter study

  Zhou, H., Bai, H. X., Jiao, Z., Cui, B., Wu, J., Zheng, H., Yang, H. & Liao, W., Nov 2023, In: European Journal of Radiology. 168, 111136.

  Research output: Contribution to journal › Article › peer-review

  • Thymic epithelial tumor 100%
  • Deep Learning 86%
  • Nomograms 76%
  • Multicenter Studies 54%
  • Area Under Curve 15%

• Editorial: Advances of radiomics and artificial intelligence in the management of patients with central nervous system tumors

  Chen, Z., Zhang, H., Zhang, P. J. Z., Bai, H. X. & Li, X., Jan 19 2023, In: Frontiers in Oncology. 13, 1081301.

  Research output: Contribution to journal › Editorial › peer-review

  Open Access

• Ethiodized oil as an imaging biomarker after conventional transarterial chemoembolization

  Mendiratta-Lala, M., Aslam, A., Bai, H. X., Chapiro, J., De Baere, T., Miyayama, S., Chernyak, V., Matsui, O., Vilgrain, V. & Fidelman, N., 2023, (Accepted/In press) In: European radiology.

  Research output: Contribution to journal › Review article › peer-review

  Open Access

  • Ethiodized Oil 100%
  • Biomarkers 48%
  • Therapeutics 12%
  • Oils 11%
  • Drug Therapy 10%

• Head and neck tumor segmentation convolutional neural network robust to missing PET/CT modalities using channel dropout

  Zhao, L. M., Zhang, H., Kim, D. D., Ghimire, K., Hu, R., Kargilis, D. C., Tang, L., Meng, S., Chen, Q., Liao, W. H., Bai, H., Jiao, Z. & Feng, X., May 7 2023, In: Physics in medicine and biology. 68, 9, 095011.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  • Positron Emission Tomography Computed Tomography 100%
  • Head and Neck Neoplasms 91%
  • Deep Learning 83%
  • Neck 69%
  • Head 66%

• Improving Outcome Prediction of Pulmonary Embolism by De-biased Multi-modality Model

  Zhong, Z., Li, J., Kulkarni, S., Li, Y., Fayad, F. H., Zhang, H., Ahn, S. H., Bai, H., Gao, X., Atalay, M. K. & Jiao, Z., 2023, Medical Image Computing and Computer Assisted Intervention – MICCAI 2023 - 26th International Conference, Proceedings. Greenspan, H., Greenspan, H., Madabhushi, A., Mousavi, P., Salcudean, S., Duncan, J., Syeda-Mahmood, T. & Taylor, R. (eds.). Springer Science and Business Media Deutschland GmbH, p. 515-525 11 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 14224 LNCS).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Multimodality 100%
  • Biased 63%
  • Prediction 54%
  • Healthcare 49%
  • Model 22%

• Radiation hematologic toxicity prediction for locally advanced rectal cancer using dosimetric and radiomics features

  Yue, H., Geng, J., Gong, L., Li, Y., Windsor, G., Liu, J., Pu, Y., Du, Y., Wang, R., Wu, H., Jiao, Z., Bai, H. & Jing, B., Aug 2023, In: Medical physics. 50, 8, p. 4993-5001 9 p.

  Research output: Contribution to journal › Article › peer-review

  • Rectal Neoplasms 100%
  • Radiation 73%
  • Datasets 38%
  • Bone Marrow 21%
  • Radiotherapy 20%

• Relative survival analysis in patients with stage I-II Merkel cell carcinoma treated with Mohs micrographic surgery or wide local excision

  Su, C., Bai, H. X. & Christensen, S., Mar 2023, In: Journal of the American Academy of Dermatology. 88, 3, p. e131-e132

  Research output: Contribution to journal › Letter › peer-review

• The Role of Federated Learning Models in Medical Imaging

  Kwak, L. & Bai, H., May 2023, In: Radiology: Artificial Intelligence. 5, 3, e230136.

  Research output: Contribution to journal › Comment/debate › peer-review

• Trends in clinical validation and usage of US Food and Drug Administration-cleared artificial intelligence algorithms for medical imaging

  Khunte, M., Chae, A., Wang, R., Jain, R., Sun, Y., Sollee, J. R., Jiao, Z. & Bai, H. X., Feb 2023, In: Clinical Radiology. 78, 2, p. 123-129 7 p.

  Research output: Contribution to journal › Article › peer-review

  • Artificial Intelligence 100%
  • Diagnostic Imaging 77%
  • United States Food and Drug Administration 74%
  • Equipment and Supplies 45%
  • Data Science 14%

• Using Machine Learning to Predict Response to Image-guided Therapies for Hepatocellular Carcinoma

  Hsieh, C., Laguna, A., Ikeda, I., Maxwell, A. W. P., Chapiro, J., Nadolski, G., Jiao, Z. & Bai, H. X., Nov 2023, In: RADIOLOGY. 309, 2, e222891.

  Research output: Contribution to journal › Review article › peer-review

  • Machine Learning 100%
  • Hepatocellular Carcinoma 71%
  • Artificial Intelligence 46%
  • Biomarkers 34%
  • Patient Selection 30%
• 2022

  A dynamic multi-modal fusion network for ovarian tumor differentiation

  Li, Y., Zou, B., Wu, J., Dai, Y., Bai, H. X. & Jiao, Z., 2022, Proceedings - 2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022. Adjeroh, D., Long, Q., Shi, X., Guo, F., Hu, X., Aluru, S., Narasimhan, G., Wang, J., Kang, M., Mondal, A. M. & Liu, J. (eds.). Institute of Electrical and Electronics Engineers Inc., p. 767-772 6 p. (Proceedings - 2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Tumor 100%
  • Fusion 81%
  • Module 73%
  • Tumors 71%
  • Fusion reactions 56%

• An automated COVID-19 triage pipeline using artificial intelligence based on chest radiographs and clinical data

  Kim, C. K., Choi, J. W., Jiao, Z., Wang, D., Wu, J., Yi, T. Y., Halsey, K. C., Eweje, F., Tran, T. M. L., Liu, C., Wang, R., Sollee, J., Hsieh, C., Chang, K., Yang, F. X., Singh, R., Ou, J. L., Huang, R. Y., Feng, C., Feldman, M. D., & 13 othersLiu, T., Gong, J. S., Lu, S., Eickhoff, C., Feng, X., Kamel, I., Sebro, R., Atalay, M. K., Healey, T., Fan, Y., Liao, W. H., Wang, J. & Bai, H. X., Dec 2022, In: npj Digital Medicine. 5, 1, 5.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  • Artificial Intelligence 100%
  • Triage 83%
  • Artificial intelligence 65%
  • Pipelines 57%
  • Thorax 52%

• Artificial intelligence for medical image analysis in epilepsy

  Sollee, J., Tang, L., Igiraneza, A. B., Xiao, B., Bai, H. X. & Yang, L., May 2022, In: Epilepsy Research. 182, 106861.

  Research output: Contribution to journal › Review article › peer-review

  • Artificial Intelligence 100%
  • Epilepsy 63%
  • Deep Learning 34%
  • Workflow 27%
  • Clinical Decision-Making 26%

• Artificial intelligence for prediction of COVID-19 progression using CT imaging and clinical data

  Wang, R., Jiao, Z., Yang, L., Choi, J. W., Xiong, Z., Halsey, K., Tran, T. M. L., Pan, I., Collins, S. A., Feng, X., Wu, J., Chang, K., Shi, L. B., Yang, S., Yu, Q. Z., Liu, J., Fu, F. X., Jiang, X. L., Wang, D. C., Zhu, L. P., & 14 othersYi, X. P., Healey, T. T., Zeng, Q. H., Liu, T., Hu, P. F., Huang, R. Y., Li, Y. H., Sebro, R. A., Zhang, P. J. L., Wang, J., Atalay, M. K., Liao, W. H., Fan, Y. & Bai, H. X., Jan 2022, In: European radiology. 32, 1, p. 205-212 8 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  • Artificial Intelligence 100%
  • Coronavirus 94%
  • Disease Progression 60%
  • Critical Illness 40%
  • Thorax 8%

• Automated machine learning for differentiation of hepatocellular carcinoma from intrahepatic cholangiocarcinoma on multiphasic MRI

  Hu, R., Li, H., Horng, H., Thomasian, N. M., Jiao, Z., Zhu, C., Zou, B. & Bai, H. X., Dec 2022, In: Scientific reports. 12, 1, 7924.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  • Cholangiocarcinoma 100%
  • Machine Learning 97%
  • Hepatocellular Carcinoma 69%
  • Liver Neoplasms 28%
  • Artificial Intelligence 19%

• Brain Tumor Segmentation with Patch-Based 3D Attention UNet from Multi-parametric MRI

  Feng, X., Bai, H., Kim, D., Maragkos, G., Machaj, J. & Kellogg, R., 2022, Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries - 7th International Workshop, BrainLes 2021, Held in Conjunction with MICCAI 2021, Revised Selected Papers. Crimi, A. & Bakas, S. (eds.). Springer Science and Business Media Deutschland GmbH, p. 90-96 7 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 12963 LNCS).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Brain Tumor 100%
  • Segmentation 75%
  • Patch 66%
  • Magnetic resonance imaging 65%
  • Tumors 64%

• Correction to: COVID-19 mortality prediction in the intensive care unit with deep learning based on longitudinal chest X-rays and clinical data (European Radiology, (2022), 32, 7, (4446-4456), 10.1007/s00330-022-08588-8)

  Cheng, J., Sollee, J., Hsieh, C., Yue, H., Vandal, N., Shanahan, J., Choi, J. W., Tran, T. M. L., Halsey, K., Iheanacho, F., Warren, J., Ahmed, A., Eickhoff, C., Feldman, M., Barbosa, E. M., Kamel, I., Lin, C. T., Yi, T., Healey, T., Zhang, P., & 5 othersWu, J., Atalay, M., Bai, H. X., Jiao, Z. & Wang, J., Jul 2022, In: European radiology. 32, 7, p. 5034 1 p.

  Research output: Contribution to journal › Comment/debate › peer-review

  Open Access

  • Deep Learning 100%
  • Radiology 72%
  • Intensive Care Units 60%
  • China 58%
  • X-Rays 56%

• COVID-19 mortality prediction in the intensive care unit with deep learning based on longitudinal chest X-rays and clinical data

  Cheng, J., Sollee, J., Hsieh, C., Yue, H., Vandal, N., Shanahan, J., Choi, J. W., Tran, T. M. L., Halsey, K., Iheanacho, F., Warren, J., Ahmed, A., Eickhoff, C., Feldman, M., Mortani Barbosa, E., Kamel, I., Lin, C. T., Yi, T., Healey, T., Zhang, P., & 5 othersWu, J., Atalay, M., Bai, H. X., Jiao, Z. & Wang, J., Jul 2022, In: European radiology. 32, 7, p. 4446-4456 11 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  • Deep Learning 100%
  • Intensive Care Units 60%
  • X-Rays 56%
  • Thorax 50%
  • Area Under Curve 42%

• DARC: Deep adaptive regularized clustering for histopathological image classification

  Li, J., Liu, J., Yue, H., Cheng, J., Kuang, H., Bai, H., Wang, Y. & Wang, J., Aug 2022, In: Medical image analysis. 80, 102521.

  Research output: Contribution to journal › Article › peer-review

  • Image classification 100%
  • Cluster Analysis 84%
  • Deep learning 83%
  • Neural networks 56%
  • Labeled data 55%

• Deep learning-based automatic tumor burden assessment of pediatric high-grade gliomas, medulloblastomas, and other leptomeningeal seeding tumors

  Peng, J., Kim, D. D., Patel, J. B., Zeng, X., Huang, J., Chang, K., Xun, X., Zhang, C., Sollee, J., Wu, J., Dalal, D. J., Feng, X., Zhou, H., Zhu, C., Zou, B., Jin, K., Wen, P. Y., Boxerman, J. L., Warren, K. E., Poussaint, T. Y., & 5 othersStates, L. J., Kalpathy-Cramer, J., Yang, L., Huang, R. Y. & Bai, H. X., Feb 1 2022, In: Neuro-oncology. 24, 2, p. 289-299 11 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  • Deep Learning 100%
  • Medulloblastoma 88%
  • Tumor Burden 69%
  • Glioma 67%
  • Pediatrics 46%

• Discriminative error prediction network for semi-supervised colon gland segmentation

  Zhang, Z., Tian, C., Bai, H. X., Jiao, Z. & Tian, X., Jul 2022, In: Medical image analysis. 79, 102458.

  Research output: Contribution to journal › Article › peer-review

  • Colon 100%
  • Error correction 47%
  • Semi-supervised learning 27%
  • Masks 26%
  • Quality Improvement 24%

• Dynamic prototypical feature representation learning framework for semi-supervised skin lesion segmentation

  Zhang, Z., Tian, C., Gao, X., Wang, C., Feng, X., Bai, H. X. & Jiao, Z., Oct 1 2022, In: Neurocomputing. 507, p. 369-382 14 p.

  Research output: Contribution to journal › Article › peer-review

  • Skin 54%
  • Labels 53%
  • Learning 32%
  • Dermoscopy 12%
  • Pixels 11%

• End-to-end artificial intelligence platform for the management of large vessel occlusions: A preliminary study

  Meng, S., Tran, T. M. L., Hu, M., Wang, P. P., Yi, T., Zhong, Z., Wang, L., Vogt, B., Jiao, Z., Barman, A., Cetintemel, U., Chang, K., Nguyen, D. T., Hui, F. K., Pan, I., Xiao, B., Yang, L., Zhou, H. & Bai, H. X., Nov 2022, In: Journal of Stroke and Cerebrovascular Diseases. 31, 11, 106753.

  Research output: Contribution to journal › Article › peer-review

  • Artificial Intelligence 100%
  • Computed Tomography Angiography 79%
  • Thrombectomy 45%
  • Area Under Curve 30%
  • Deep Learning 25%

• Machine intelligence in non-invasive endocrine cancer diagnostics

  Thomasian, N. M., Kamel, I. R. & Bai, H. X., Feb 2022, In: Nature Reviews Endocrinology. 18, 2, p. 81-95 15 p.

  Research output: Contribution to journal › Review article › peer-review

  Open Access

  • Endocrine Gland Neoplasms 100%
  • Artificial Intelligence 84%
  • Machine Learning 28%
  • Systems Integration 18%
  • Workflow 13%

• MLDRL: Multi-loss disentangled representation learning for predicting esophageal cancer response to neoadjuvant chemoradiotherapy using longitudinal CT images

  Yue, H., Liu, J., Li, J., Kuang, H., Lang, J., Cheng, J., Peng, L., Han, Y., Bai, H., Wang, Y., Wang, Q. & Wang, J., Jul 2022, In: Medical image analysis. 79, 102423.

  Research output: Contribution to journal › Article › peer-review

  • Chemoradiotherapy 100%
  • Esophageal Neoplasms 49%
  • Learning 35%
  • Datasets 15%
  • Information fusion 6%

• Myosteatosis predicting risk of transition to severe COVID-19 infection

  Yi, X., Liu, H., Zhu, L., Wang, D., Xie, F., Shi, L., Mei, J., Jiang, X., Zeng, Q., Hu, P., Li, Y., Pang, P., Liu, J., Peng, W., Bai, H. X., Liao, W. & Chen, B. T., Dec 2022, In: Clinical Nutrition. 41, 12, p. 3007-3015 9 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  • Coronavirus 100%
  • Nomograms 48%
  • Skeletal Muscle 47%
  • Infections 37%
  • Fats 29%

• Parameter-Free Latent Space Transformer for Zero-Shot Bidirectional Cross-modality Liver Segmentation

  Li, Y., Zou, B., Dai, Y., Zhu, C., Yang, F., Li, X., Bai, H. X. & Jiao, Z., 2022, Medical Image Computing and Computer Assisted Intervention – MICCAI 2022 - 25th International Conference, Proceedings. Wang, L., Dou, Q., Fletcher, P. T., Speidel, S. & Li, S. (eds.). Springer Science and Business Media Deutschland GmbH, p. 619-628 10 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 13434 LNCS).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Liver 100%
  • Transformer 97%
  • Segmentation 89%
  • Modality 86%
  • Convolutional neural networks 67%

• Prediction of Glioma Grade Using Intratumoral and Peritumoral Radiomic Features From Multiparametric MRI Images

  Cheng, J., Liu, J., Yue, H., Bai, H., Pan, Y. & Wang, J., 2022, In: IEEE/ACM Transactions on Computational Biology and Bioinformatics. 19, 2, p. 1084-1095 12 p.

  Research output: Contribution to journal › Article › peer-review

  • Multiparametric Magnetic Resonance Imaging 100%
  • Magnetic resonance imaging 74%
  • Glioma 65%
  • Prediction 56%
  • IPTV 46%

• Prediction of lung malignancy progression and survival with machine learning based on pre-treatment FDG-PET/CT

  Huang, B., Sollee, J., Luo, Y. H., Reddy, A., Zhong, Z., Wu, J., Mammarappallil, J., Healey, T., Cheng, G., Azzoli, C., Korogodsky, D., Zhang, P., Feng, X., Li, J., Yang, L., Jiao, Z. & Bai, H. X., Aug 2022, In: EBioMedicine. 82, 104127.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  • Machine Learning 100%
  • Statistical Ensemble 87%
  • Survival 49%
  • Lung 47%
  • Forests 35%

• Proceedings from the Society of Interventional Radiology Foundation Research Consensus Panel on Artificial Intelligence in Interventional Radiology: From Code to Bedside

  Chapiro, J., Allen, B., Abajian, A., Wood, B., Kothary, N., Daye, D., Bai, H., Sedrakyan, A., Diamond, M., Simonyan, V., McLennan, G., Abi-Jaoudeh, N. & Pua, B., Sep 2022, In: Journal of Vascular and Interventional Radiology. 33, 9, p. 1113-1120 8 p.

  Research output: Contribution to journal › Editorial › peer-review

  • Artificial Intelligence 100%
  • Interventional Radiology 96%
  • Consensus 71%
  • Technology 16%
  • Patient Care 12%

• Radiomics-Based Machine Learning for Outcome Prediction in a Multicenter Phase II Study of Programmed Death-Ligand 1 Inhibition Immunotherapy for Glioblastoma

  George, E., Flagg, E., Chang, K., Bai, H. X., Aerts, H. J., Vallières, M., Reardon, D. A. & Huang, R. Y., May 1 2022, In: American Journal of Neuroradiology. 43, 5, p. 675-681 7 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  • Machine Learning 100%
  • Glioblastoma 87%
  • Immunotherapy 77%
  • Ligands 62%
  • Progression-Free Survival 53%

• Translatability Analysis of National Institutes of Health-Funded Biomedical Research That Applies Artificial Intelligence

  Eweje, F. R., Byun, S., Chandra, R., Hu, F., Kamel, I., Zhang, P., Jiao, Z. & Bai, H. X., 2022, (Accepted/In press) In: JAMA Network Open. p. E2144742

  Research output: Contribution to journal › Article › peer-review

  Open Access

  • Artificial Intelligence 100%
  • National Institutes of Health (U.S.) 78%
  • Biomedical Research 75%
  • Natural Language Processing 24%
  • Organized Financing 19%
• 2021

  Analysis of morphological characteristics of IDH-mutant/wildtype brain tumors using whole-lesion phenotype analysis

  Snyder, J. M., Huang, R. Y., Bai, H., Rao, V. R., Cornes, S., Barnholtz-Sloan, J. S., Gutman, D., Fasano, R., Van Meir, E. G., Brat, D., Eschbacher, J., Quackenbush, J., Wen, P. Y. & Lee, J. W., Jan 1 2021, In: Neuro-Oncology Advances. 3, 1, vdab088.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  • Brain Neoplasms 100%
  • Phenotype 64%
  • Neoplasms 34%
  • Cluster Analysis 27%
  • Mutation 8%

• Chronic liver disease not a significant comorbid condition for COVID-19

  Lin, J., Bao, B., Khurram, N. A., Halsey, K., Choi, J. W., Wang, L., Tran, T. M. L., Liao, W. H., Feldman, M. D., Zhang, P. J., Wu, J. & Bai, H. X., Dec 2021, In: Scientific reports. 11, 1, 11734.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  • Liver Diseases 100%
  • Chronic Disease 87%
  • Liver 43%
  • Autopsy 28%
  • Wounds and Injuries 24%

• Correction to: Evaluation of a convolutional neural network for ovarian tumor differentiation based on magnetic resonance imaging (European Radiology, (2021), 31, 7, (4960-4971), 10.1007/s00330-020-07266-x)

  Wang, R., Cai, Y., Lee, I. K., Hu, R., Purkayastha, S., Pan, I., Yi, T., Tran, T. M. L., Lu, S., Liu, T., Chang, K., Huang, R. Y., Zhang, P. J., Zhang, Z., Xiao, E., Wu, J. & Bai, H. X., Nov 2021, In: European radiology. 31, 11, p. 8816 1 p.

  Research output: Contribution to journal › Comment/debate › peer-review

  Open Access

  • Radiology 100%
  • Magnetic Resonance Imaging 66%
  • Neoplasms 32%

• COVID-19 imaging: What we know now and what remains unknown

  Kanne, J. P., Bai, H., Bernheim, A., Chung, M., Haramati, L. B., Kallmes, D. F., Little, B. P., Rubin, G. & Sverzellati, N., Jun 2021, In: RADIOLOGY. 299, 3, p. E262-E279

  Research output: Contribution to journal › Review article › peer-review

  • Pandemics 100%
  • SARS Virus 69%
  • Thorax 64%
  • Artificial Intelligence 62%
  • Asymptomatic Diseases 60%

• Deep Learning for Classification of Bone Lesions on Routine MRI

  Eweje, F. R., Bao, B., Wu, J., Dalal, D., Liao, W. H., He, Y., Luo, Y., Lu, S., Zhang, P., Peng, X., Sebro, R., Bai, H. X. & States, L., Jun 2021, In: EBioMedicine. 68, 103402.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  • Deep Learning 100%
  • Statistical Ensemble 72%
  • Magnetic Resonance Imaging 48%
  • Bone and Bones 43%
  • Area Under Curve 29%

• Deep learning for differentiation of benign and malignant solid liver lesions on ultrasonography

  Xi, I. L., Wu, J., Guan, J., Zhang, P. J., Horii, S. C., Soulen, M. C., Zhang, Z. & Bai, H. X., Feb 2021, In: Abdominal Radiology. 46, 2, p. 534-543 10 p.

  Research output: Contribution to journal › Article › peer-review

  • Deep Learning 100%
  • Ultrasonography 56%
  • Liver 37%
  • Datasets 23%
  • Triage 16%

• Development of Brain Metastases in Patients with Non–Small Cell Lung Cancer and No Brain Metastases at Initial Staging Evaluation: Cumulative Incidence and Risk Factor Analysis

  Kim, M., Suh, C. H., Lee, S. M., Park, J. E., Kim, H. C., Kim, S. O., Aizer, A. A., Yanagihara, T. K., Bai, H. X., Guenette, J. P., Huang, R. Y. & Kim, H. S., Nov 2021, In: American Journal of Roentgenology. 217, 5, p. 1184-1193 10 p.

  Research output: Contribution to journal › Article › peer-review

  • Brain Neoplasms 100%
  • Non-Small Cell Lung Carcinoma 96%
  • Statistical Factor Analysis 95%
  • Neoplasm Metastasis 66%
  • Brain 52%

• DICOM Image ANalysis and Archive (DIANA): an Open-Source System for Clinical AI Applications

  Yi, T., Pan, I., Collins, S., Chen, F., Cueto, R., Hsieh, B., Hsieh, C., Smith, J. L., Yang, L., Liao, W. H., Merck, L. H., Bai, H. & Merck, D., Dec 2021, In: Journal of Digital Imaging. 34, 6, p. 1405-1413 9 p.

  Research output: Contribution to journal › Article › peer-review

  • Digital Imaging and Communications in Medicine (DICOM) 100%
  • Artificial Intelligence 98%
  • Image analysis 70%
  • Artificial intelligence 64%
  • Radiology Information Systems 36%

• Encephalopathy at admission predicts adverse outcomes in patients with SARS-CoV-2 infection

  Tang, L., Liu, S., Xiao, Y., Tran, T. M. L., Choi, J. W., Wu, J., Halsey, K., Huang, R. Y., Boxerman, J., Patel, S. H., Kung, D., Liu, R., Feldman, M. D., Danoski, D. D., Liao, W. H., Kasner, S. E., Liu, T., Xiao, B., Zhang, P. J., Reznik, M., & 2 othersBai, H. X. & Yang, L., Oct 2021, In: CNS Neuroscience and Therapeutics. 27, 10, p. 1127-1135 9 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  • Severe Acute Respiratory Syndrome 90%
  • Brain Diseases 66%
  • Ventilation 20%
  • Coronavirus 19%
  • Intensive Care Units 19%

• Erratum: Deep learning-based automatic tumor burden assessment of pediatric high-grade gliomas, medulloblastomas, and other leptomeningeal seeding tumors (Neuro Oncol (2021) DOI: 10.1093/neuonc/noab151)

  Peng, J., Kim, D. D., Patel, J. B., Zeng, X., Huang, J., Chang, K., Xun, X., Zhang, C., Sollee, J., Wu, J., Dalal, D. J., Feng, X., Zhou, H., Zhu, C., Zou, B., Jin, K., Wen, P. Y., Boxerman, J. L., Warren, K. E., Poussaint, T. Y., & 5 othersStates, L. J., Kalpathy-Cramer, J., Yang, L., Huang, R. Y. & Bai, H. X., Dec 1 2021, In: Neuro-oncology. 23, 12, p. 2124 1 p.

  Research output: Contribution to journal › Comment/debate › peer-review

  Open Access

  • Deep Learning 100%
  • Medulloblastoma 88%
  • Tumor Burden 69%
  • Glioma 67%
  • Pediatrics 46%

• Evaluation of a convolutional neural network for ovarian tumor differentiation based on magnetic resonance imaging

  Wang, R., Cai, Y., Lee, I. K., Hu, R., Purkayastha, S., Pan, I., Yi, T., Tran, T. M. L., Lu, S., Liu, T., Chang, K., Huang, R. Y., Zhang, P. J., Zhang, Z., Xiao, E., Wu, J. & Bai, H. X., Jul 2021, In: European radiology. 31, 7, p. 4960-4971 12 p.

  Research output: Contribution to journal › Article › peer-review

  • Radiologists 100%
  • Magnetic Resonance Imaging 71%
  • Deep Learning 59%
  • Neoplasms 34%
  • Artificial Intelligence 28%

• Machine Learning-Based Prediction of COVID-19 Severity and Progression to Critical Illness Using CT Imaging and Clinical Data

  Purkayastha, S., Xiao, Y., Jiao, Z., Thepumnoeysuk, R., Halsey, K., Wu, J., Tran, T. M. L., Hsieh, B., Choi, J. W., Wang, D., Vallières, M., Wang, R., Collins, S., Feng, X., Feldman, M., Zhang, P. J., Atalay, M., Sebro, R., Yang, L., Fan, Y., & 2 othersLiao, W. H. & Bai, H. X., Jul 1 2021, In: Korean journal of radiology. 22, 7, p. 1213-1224 12 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  • Coronavirus 100%
  • Machine Learning 89%
  • Critical Illness 73%
  • Area Under Curve 51%
  • ROC Curve 40%

• Performance of automatic machine learning versus radiologists in the evaluation of endometrium on computed tomography

  Li, D., Hu, R., Li, H., Cai, Y., Zhang, P. J., Wu, J., Zhu, C. & Bai, H. X., Nov 2021, In: Abdominal Radiology. 46, 11, p. 5316-5324 9 p.

  Research output: Contribution to journal › Article › peer-review

  • Machine Learning 100%
  • Endometrium 92%
  • Endometrial Neoplasms 90%
  • Radiologists 81%
  • Tomography 60%