Dr. Snehal Patel is a molecular pathologist and machine learning engineer with expertise in next-generation sequencing, cancer genomics, and artificial intelligence applications in pathology. He completed his MD/PhD at the University of Illinois, followed by AP/CP residency and MGP fellowship at Cedars-Sinai Medical Center and AI research fellowship at Michigan State University. Dr. Patel's research focuses on developing computational methods to improve cancer diagnosis and treatment selection, with a particular interest in integrating multi-modal data to enhance precision medicine approaches.
Education:
- B.Eng. - Math (honors) and Biomedical Engineering (cum laude), Vanderbilt University, Nashville, TN (2001)
- MD, PhD - Biochemistry, Medical Scholars Program, University of Illinois, Urbana, IL (2011)
- Executive Certficate in Entrepreneurship - Entrepreneurship & Venture Challenge Program, Eastern Michigan University, Ypsilanti, MI (2022)
Board Certification(s):
- Molecular Genetic Pathology
- Anatomic and Clinical Pathology
Residency:
- Anatomic and Clinical Pathology - Department of Pathology & Laboratory Medicine, Cedars-Sinai Medical Center, Los Angeles, CA (2011-2015)
Fellowship:
- Research Fellowship in Artificial Intelligence & Machine Learning - Institute for Quantitative Health Science & Engineering, Michigan State University, East Lansing, MI (2021-2023)
- Clinical Fellowship in Molecular Genetic Pathology - Department of Pathology & Laboratory Medicine, Cedars-Sinai Medical Center, Los Angeles, CA (2015-2016)
- Clinical Scholar, Clinical Scholars Program, Cedars-Sinai Medical Center, Los Angeles, CA (2015-2016)
Clinical/Research Interests:
Dr. Patel's current research focuses on developing artificial intelligence technology to bring precision and efficiency to molecular diagnostic laboratory processes to provide the best patient experience.
Select Honors and Accomplishments:
- Recognized by ABPath for Item Contribution to CertLink (2021, 2022)
- Ann Arbor SPARK Pitch Competition Winner, Topic: GenomixReporter: Automated sequencing variant interpretation & reporting, $25,000 award (2021)
Select Publications:
- Arda Pekis, Vignesh Kannan, Evandros Kaklamanos, Anu Antony, Snehal Patel, Tyler Earnest, "Seeing beyond cancer: multi-institutional validation of object localization and 3D semantic segmentation using deep learning for breast MRI," Proc. SPIE 12927, Medical Imaging 2024: Computer-Aided Diagnosis, 129270H (3 April 2024); https://doi.org/10.1117/12.3009341
- Cook D, Biancalana M, Liadis N, Lopez Ramos D, Zhang Y, Patel S, Peterson JR, Pfeiffer JR, Cole JA, Antony AK. Next generation immuno-oncology tumor profiling using a rapid, non-invasive, computational biophysics biomarker in early-stage breast cancer. Front Artif Intell. 2023 Apr 17;6:1153083. doi: 10.3389/frai.2023.1153083. PMID: 37138891; PMCID: PMC10149754.
- Agrawal T, Xi L, Navarro W, Raffeld M, Patel SB, Roth MJ, Klubo-Gwiezdzinska J, Filie AC. An effective approach for BRAF V600E mutation analysis of routine thyroid fine needle aspirates. Cytopathology. 2022 May;33(3):344-349. doi: 10.1111/cyt.13093. Epub 2022 Feb 16. PMID: 34957617.
- Patel SB, Bookstein R, Farahani N, Chevarie-Davis M, Pao A, Aguiluz A, Riley C, Hodge JC, Alkan S, Liu Z, Deng N, Lopategui JR. Recommendations for Specimen and Therapy Selection in Colorectal Cancer. Oncol Ther. 2021 Dec;9(2):451-469. doi: 10.1007/s40487-021-00151-7. Epub 2021 Apr 25. PMID: 33895946; PMCID: PMC8593092.
- Patel SB, McCormack C, Hodge JC. Non-fusion mutations in endometrial stromal sarcomas: what is the potential impact on tumourigenesis through cell cycle dysregulation? J Clin Pathol. 2020 Dec;73(12):830-835. doi: 10.1136/jclinpath-2020-206432. Epub 2020 May 8. PMID: 32385140.