Arief A. Suriawinata, MD
Title(s)
Professor of Pathology and Laboratory Medicine
Additional Titles/Positions/Affiliations
Interim Chair, Department of Pathology and Laboratory Medicine
Diplomate of the American Board of Pathology in Anatomic and Clinical Pathology, and in Clinical Informatics
Department(s)
Pathology and Laboratory Medicine
Education
Univ. Indonesia, Faculty of Medicine, MD 1995
Anatomic and Clinical Pathology Residency, The Mount Sinai Medical Center, 1996-2000
Oncologic Pathology Fellowship, Memorial Sloan-Kettering Cancer Center, 2000-2001
Gastrointestinal Oncologic Pathology Fellowship, Memorial Sloan-Kettering Cancer Center, 2001-2002
Programs
Norris Cotton Cancer Center
Websites
www.liverpathology.net
Academic Analytics
View Profile
Contact Information
Department of Pathology and Laboratory Medicine
Dartmouth-Hitchcock Medical Center
One Medical Center Drive
Lebanon NH 03756
Office: Borwell, Level 4
Phone: 603-650-7048
Fax: 603-650-4845
Email: Arief.A.Suriawinata@hitchcock.org
Assistant: Meg Parker
Asst. Phone: 603-650-8693
Professional Interests
Gastrointestinal, Liver, Pancreas and Transplant
Surgical Pathology
Pathology and Clinical Informatics
Rotations and Thesis Projects
Gastrointestinal and Liver Pathology
Courses Taught
Gastrointestinal and Liver Pathology
Large-scale validation study of an improved semiautonomous urine cytology assessment tool: AutoParis-X. Pancreatic acinar metaplasia at the gastroesophageal junction is associated with protective effect against intestinal metaplasia in patients with gastroesophageal reflux disease. Examining longitudinal markers of bladder cancer recurrence through a semiautonomous machine learning system for quantifying specimen atypia from urine cytology. MHAttnSurv: Multi-head attention for survival prediction using whole-slide pathology images. Graph Convolutional Neural Networks for Histologic Classification of Pancreatic Cancer. Detection of Colorectal Adenocarcinoma and Grading Dysplasia on Histopathologic Slides Using Deep Learning. Bladder cancer prognosis using deep neural networks and histopathology images. Uncovering additional predictors of urothelial carcinoma from voided urothelial cell clusters through a deep learning-based image preprocessing technique. Predicting oncogene mutations of lung cancer using deep learning and histopathologic features on whole-slide images. Iron and iron-related proteins in COVID-19. |
|