Saltz, Joel

Spatial organization and molecular correlation of tumor-infiltrating lymphocytes using deep learning on pathology images

Saltz, J., Gupta, R., Hou, L., Kurc, T., Singh, P., Nguyen, V., Samaras, D., Shroyer, K. R., Zhao, T., Batiste, R., et al. (2018) · Cell Reports

AI in cancer detectionCancer Immunotherapy and Biomarkers

Cited by 1,027

AI in Medical Imaging Informatics: Current Challenges and Future Directions

Panayides, A. S., Amini, A., Filipovic, N. D., Sharma, A., Tsaftaris, S. A., Young, A., Foran, D., Do, N., Golemati, S., Kurc, T., et al. (2020) · IEEE Journal of Biomedical and Health Informatics

Artificial Intelligence in Healthcare and EducationMedical Image Segmentation Techniques

Cited by 713

Caveats for the Use of Operational Electronic Health Record Data in Comparative Effectiveness Research

Hersh, W. R., Weiner, M. G., Embi, P. J., Logan, J. R., Payne, P. R. O., Bernstam, E. V., Lehmann, H. P., Hripcsak, G., Hartzog, T. H., Cimino, J. J., et al. (2013) · Medical Care

Electronic Health Records SystemsMedical Coding and Health Information

Cited by 567

The National COVID Cohort Collaborative (N3C): Rationale, design, infrastructure, and deployment

Haendel, M. A., Chute, C. G., Bennett, T. D., Eichmann, D. A., Guinney, J., Kibbe, W. A., Payne, P. R. O., Pfaff, E. R., Robinson, P. N., Saltz, J. H., et al. (2021) · Journal of the American Medical Informatics Association

Research Data Management PracticesElectronic Health Records Systems

Cited by 553

Federated learning enables big data for rare cancer boundary detection

Pati, S., Baid, U., Edwards, B., Sheller, M., Wang, S.-H., Reina, G. A., Foley, P., Gruzdev, A., Karkada, D., Davatzikos, C., et al. (2022) · Nature Communications

Privacy-Preserving Technologies in DataBrain Tumor Detection and Classification

Cited by 394

Twenty Years of Digital Pathology: An Overview of the Road Travelled, What is on the Horizon, and the Emergence of Vendor-Neutral Archives

Pantanowitz, L., Sharma, A., Carter, A. B., Kurc, T., Sussman, A., & Saltz, J. (2018) · Journal of Pathology Informatics

AI in cancer detectionArtificial Intelligence in Healthcare and Education

Cited by 282

Characterizing long COVID: deep phenotype of a complex condition

Deer, R. R., Rock, M. A., Vasilevsky, N., Carmody, L., Rando, H., Anzalone, A. J., Basson, M. D., Bennett, T. D., Bergquist, T., Boudreau, E. A., et al. (2021) · EBioMedicine

Long-Term Effects of COVID-19Biomedical Text Mining and Ontologies

Cited by 200

ImageMiner: a software system for comparative analysis of tissue microarrays using content-based image retrieval, high-performance computing, and grid technology

Foran, D. J., Yang, L., Chen, W., Hu, J., Goodell, L. A., Reiss, M., Wang, F., Kurc, T., Pan, T., Sharma, A., et al. (2011) · Journal of the American Medical Informatics Association

AI in cancer detectionImage Retrieval and Classification Techniques

Cited by 65

A Containerized Software System for Generation, Management, and Exploration of Features from Whole Slide Tissue Images

Saltz, J., Sharma, A., Iyer, G., Bremer, E., Wang, F., Jasniewski, A., DiPrima, T., Almeida, J. S., Gao, Y., Zhao, T., et al. (2017) · Cancer Research

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

Cited by 60

A national strategy to develop pragmatic clinical trials infrastructure

Concannon, T. W., Guise, J., Dolor, R. J., Meissner, P., Tunis, S., Krishnan, J. A., Pace, W. D., Saltz, J., Hersh, W. R., Michener, L., et al. (2014) · Clinical and Translational Science

Health Policy Implementation ScienceHealth and Medical Research Impacts

Cited by 31

Effective active learning in digital pathology: A case study in tumor infiltrating lymphocytes

Meirelles, A. L., Kurc, T., Saltz, J., & Teodoro, G. (2022) · Computer Methods and Programs in Biomedicine

AI in cancer detectionMachine Learning and Algorithms

Cited by 17