SUMMARY
Jaidip M. Jagtap, Ph.D., focuses on the application of artificial intelligence in medical imaging and digital pathology. His research centers on the creation of artificial intelligence-driven tools to improve diagnostic and therapeutic understanding of complicated conditions such as chronic kidney disease, carpal tunnel syndrome, Barrett esophagus and many malignancies.
Dr. Jagtap has more than nine years of experience participating in many National Institutes of Health-funded projects. He combines an expertise in radiology, biomedical engineering, optics and deep learning to study computerized tomography, magnetic resonance imaging, ultrasound, dermatology and digital pathology images. Dr. Jagtap's research improves accuracy in clinical decision-making and patient outcomes.
Focus areas
- Artificial intelligence for medical image segmentation and analysis. Dr. Jagtap uses deep learning and machine learning methods to segment and analyze medical images across many fields. These medical areas range from radiological images to skin melanoma categorization, allowing him to create dependable and automated medical solutions.
- Pathological imaging in nephrectomies. In cooperation with nephrologists, Dr. Jagtap applies artificial intelligence algorithms to nephrectomy pathology images to examine segmental regions having glomerular, tubular and interstitial fibrosis. He received the Innovation in Aging Award, to support research into age-related kidney tissue changes, for developing advanced metrics for chronic kidney disease risk and tissue health assessment.
- Risk stratification in Barrett esophagus. Dr. Jagtap works with gastrointestinal healthcare professionals in using machine learning to improve risk stratification in Barrett esophagus. His research focuses on evaluating imaging and biomarker data to speed up the early discovery of unusual cell growth and esophageal cancer. This imaging and biomarker data uses noninvasive artificial intelligence tools for quick, therapeutic intervention.
- Diagnosis of carpal tunnel syndrome. Dr. Jagtap uses ultrasound imaging to create artificial intelligence-driven U-Net models for the segmentation and quantification of the median nerve. U-Net is a U-shaped, noninvasive network model used to improve images and decision-making for carpal tunnel syndrome treatment.
- Biomarkers for polycystic kidney disease. Dr. Jagtap advances biomarker development for polycystic kidney disease. He improves biomarker advancement by using automated segmentation of polycystic kidney disease-associated features in magnetic resonance imaging and ultrasound images. These biomarkers improve the measurement of kidney volume and lesion analysis, thus improving the early diagnosis and monitoring of polycystic kidney disease.
- Fluorescence imaging and near-infrared instrumentation. In the early stages of his work, Dr. Jagtap created near-infrared fluorescence imaging systems to study vascular and lymphatic changes in preclinical models. This research resulted in real-time imaging systems that aid in deciding therapeutic success and illness advancement in animal models.
Significance to patient care
Dr. Jagtap studies artificial intelligence to improve the accuracy and success of image-based diagnostics for illnesses including kidney conditions, carpal tunnel syndrome and cancer. By making tools that correctly figure out medical images, healthcare professionals may make better choices and tailor treatment to each patient's given situation. His artificial intelligence-driven segmentation in carpal tunnel syndrome offers a noninvasive method to view nerve changes, possibly decreasing the need for surgery. These advances help healthcare professionals in the early discovery of illnesses, the monitoring for temporal changes and the improvement of overall patient care.
Professional highlights
- Associate editor, BMC Medicine, 2023-present.
- Associate editor, Journal of Imaging Informatics in Medicine, 2022-present.
- Innovation in Aging Award, Mayo Clinic Center for Clinical and Translational Science and Robert and Arlene Kogod Center on Aging, 2024.
- Invited speaker, National Science Day Workshop, University of Rajasthan, India, 2022.
- Keynote speaker, International Conference of Computer Science and Renewable Energies, Agadir, Morocco, 2022.
- Invited speaker, Correlation Optics Conference, Chernivtsi National University, Ukraine, 2021.
- Invited speaker, International Meeting, Vaibhav Summit, New Delhi, 2020.
- Best Scientific Abstract Award, World Conference of Interventional Oncology, Boston, 2016, 2017.
- Travel Award, World Molecular Imaging Society, New York, 2016.
- Travel grant, Department of Science and Technology, Society of Photographic Instrumentation Engineers Photonics West, 2011, 2013.