Dr. El-Baz is a Professor, University Scholar, and Chair of the Bioengineering Department at the University of Louisville, KY. Dr. El-Baz earned his bachelor's and master’s degrees in Electrical Engineering in 1997 and 2001, respectively. He earned his doctoral degree in electrical engineering from the University of Louisville in 2006. In 2009, Dr. El-Baz was named a Coulter Fellow for his contributions to the field of biomedical translational research. Dr. El-Baz has 15 years of hands-on experience in the fields of bio-imaging modeling and non-invasive computer-assisted diagnosis systems. He has authored or coauthored more than 450 technical articles (105 journals, 15 books, 50 book chapters, 175 refereed-conference papers, 100 abstracts, and 15 US patents). Dr. Jasjit Suri, PhD, MBA, is a renowned innovator and scientist. He received the Director General’s Gold Medal in 1980 and is a Fellow of several prestigious organizations, including the American Institute of Medical and Biological Engineering and the Institute of Electrical and Electronics Engineers. Dr. Suri has been honored with lifetime achievement awards from Marcus, NJ, USA, and Graphics Era University, India. He has published nearly 300 peer-reviewed AI articles, 100 books, and holds 100 innovations/trademarks, achieving an H-index of nearly 100 with about 43,000 citations. Dr. Suri has served as chairman of AtheroPoint, IEEE Denver section, and as an advisory board member to various healthcare industries and universities globally.

• 1. Computer Aided Detection of Abnormality in Mammography using Deep Object Detectors2. Detection of retinal abnormalities in fundus image using CNN Deep Learning Networks3. A survey of Deep Learning Based Methods for Cryo-electron Tomography Data Analysis4. Detection, Segmentation and Numbering of Teeth in Dental Panoramic Images with Mask RCNN5. Accurate Identification of Renal Transplant Rejection: Convolutional Neural Networks and Diffusion MRI6. Applications of the ESPNet Architecture in Medical Imaging7. Achievements of Neural Network in Skin Lesions Classification8. A Computer-aided-diagnosis System for Breast Cancer Molecular Subtypes Prediction in mammographic images9. Computer-Aided Diagnosis of Renal Masses10. Early Identification of Acute Rejection for Renal Allografts: A Machine Learning Approach11. Deep Learning for Computer-Aided Diagnosis in Ophthalmology: A Review12. Deep Learning for Ophthalmology using Optical Coherence Tomography13. Generative Adversarial Networks in Medical Imaging14. Deep Learning from Small Labeled Datasets Applied to Medical Image Analysis

Dr. El-Baz is a Professor, University Scholar, and Chair of the Bioengineering Department at the University of Louisville, KY. Dr. El-Baz earned his bachelor's and master’s degrees in Electrical Engineering in 1997 and 2001, respectively. He earned his doctoral degree in electrical engineering from the University of Louisville in 2006. In 2009, Dr. El-Baz was named a Coulter Fellow for his contributions to the field of biomedical translational research. Dr. El-Baz has 15 years of hands-on experience in the fields of bio-imaging modeling and non-invasive computer-assisted diagnosis systems. He has authored or coauthored more than 450 technical articles (105 journals, 15 books, 50 book chapters, 175 refereed-conference papers, 100 abstracts, and 15 US patents). Dr. Jasjit Suri, PhD, MBA, is a renowned innovator and scientist. He received the Director General’s Gold Medal in 1980 and is a Fellow of several prestigious organizations, including the American Institute of Medical and Biological Engineering and the Institute of Electrical and Electronics Engineers. Dr. Suri has been honored with lifetime achievement awards from Marcus, NJ, USA, and Graphics Era University, India. He has published nearly 300 peer-reviewed AI articles, 100 books, and holds 100 innovations/trademarks, achieving an H-index of nearly 100 with about 43,000 citations. Dr. Suri has served as chairman of AtheroPoint, IEEE Denver section, and as an advisory board member to various healthcare industries and universities globally.

• 1. Computer Aided Detection of Abnormality in Mammography using Deep Object Detectors2. Detection of retinal abnormalities in fundus image using CNN Deep Learning Networks3. A survey of Deep Learning Based Methods for Cryo-electron Tomography Data Analysis4. Detection, Segmentation and Numbering of Teeth in Dental Panoramic Images with Mask RCNN5. Accurate Identification of Renal Transplant Rejection: Convolutional Neural Networks and Diffusion MRI6. Applications of the ESPNet Architecture in Medical Imaging7. Achievements of Neural Network in Skin Lesions Classification8. A Computer-aided-diagnosis System for Breast Cancer Molecular Subtypes Prediction in mammographic images9. Computer-Aided Diagnosis of Renal Masses10. Early Identification of Acute Rejection for Renal Allografts: A Machine Learning Approach11. Deep Learning for Computer-Aided Diagnosis in Ophthalmology: A Review12. Deep Learning for Ophthalmology using Optical Coherence Tomography13. Generative Adversarial Networks in Medical Imaging14. Deep Learning from Small Labeled Datasets Applied to Medical Image Analysis

Dr. El-Baz is a Professor, University Scholar, and Chair of the Bioengineering Department at the University of Louisville, KY. Dr. El-Baz earned his bachelor's and master’s degrees in Electrical Engineering in 1997 and 2001, respectively. He earned his doctoral degree in electrical engineering from the University of Louisville in 2006. In 2009, Dr. El-Baz was named a Coulter Fellow for his contributions to the field of biomedical translational research. Dr. El-Baz has 15 years of hands-on experience in the fields of bio-imaging modeling and non-invasive computer-assisted diagnosis systems. He has authored or coauthored more than 450 technical articles (105 journals, 15 books, 50 book chapters, 175 refereed-conference papers, 100 abstracts, and 15 US patents). Dr. Jasjit Suri, PhD, MBA, is a renowned innovator and scientist. He received the Director General’s Gold Medal in 1980 and is a Fellow of several prestigious organizations, including the American Institute of Medical and Biological Engineering and the Institute of Electrical and Electronics Engineers. Dr. Suri has been honored with lifetime achievement awards from Marcus, NJ, USA, and Graphics Era University, India. He has published nearly 300 peer-reviewed AI articles, 100 books, and holds 100 innovations/trademarks, achieving an H-index of nearly 100 with about 43,000 citations. Dr. Suri has served as chairman of AtheroPoint, IEEE Denver section, and as an advisory board member to various healthcare industries and universities globally.

• 1. Computer Aided Detection of Abnormality in Mammography using Deep Object Detectors2. Detection of retinal abnormalities in fundus image using CNN Deep Learning Networks3. A survey of Deep Learning Based Methods for Cryo-electron Tomography Data Analysis4. Detection, Segmentation and Numbering of Teeth in Dental Panoramic Images with Mask RCNN5. Accurate Identification of Renal Transplant Rejection: Convolutional Neural Networks and Diffusion MRI6. Applications of the ESPNet Architecture in Medical Imaging7. Achievements of Neural Network in Skin Lesions Classification8. A Computer-aided-diagnosis System for Breast Cancer Molecular Subtypes Prediction in mammographic images9. Computer-Aided Diagnosis of Renal Masses10. Early Identification of Acute Rejection for Renal Allografts: A Machine Learning Approach11. Deep Learning for Computer-Aided Diagnosis in Ophthalmology: A Review12. Deep Learning for Ophthalmology using Optical Coherence Tomography13. Generative Adversarial Networks in Medical Imaging14. Deep Learning from Small Labeled Datasets Applied to Medical Image Analysis