Louis J Vaickus, MD, PhD
Title(s):
Assistant Professor of Pathology and Laboratory Medicine
Additional Titles/Positions/Affiliations:
Medical Director of Pathology Informatics
Department(s):
Pathology and Laboratory Medicine
Education:
BA, Hamilton College, Clinton NY, 2001-2005
MD, Boston University School of Medicine, Boston MA, 2005-2012
PhD, Boston University School of Medicine, Boston MA, 2005-2012
Anatomic Pathology Residency, Massachusetts General Hospital, Boston MA, 2012-2016
Cytopathology Fellowship, Massachusetts General Hospital, Boston MA, 2014-2015
Contact Information:
1 Medical Center Drive
Lebanon NH 03766
Office: Borwell 4
Phone: 53844
Email: Louis.J.Vaickus@Dartmouth.edu
Professional Interests:
Informatics
Deep learning
Medical image analysis
Automation
Programming
Grant Information:
SYNERGY Clinical Research Fellow, 2018-2019
Selected Publications: |
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Evaluation of a Deep Neural Network for Automated Classification of Colorectal Polyps on Histopathologic Slides. A machine learning algorithm for simulating immunohistochemistry: development of SOX10 virtual IHC and evaluation on primarily melanocytic neoplasms. PathFlowAI: A High-Throughput Workflow for Preprocessing, Deep Learning and Interpretation in Digital Pathology. Pathologist-level classification of histologic patterns on resected lung adenocarcinoma slides with deep neural networks. Automating the Paris System for urine cytopathology-A hybrid deep-learning and morphometric approach. Pancreatic mixed acinar-neuroendocrine carcinoma, a unique diagnostic challenge on FNA cytology: A small series of two cases with literature review. Identifying aerosolized cyanobacteria in the human respiratory tract: A proposed mechanism for cyanotoxin-associated diseases. Young investigator challenge: Comparison of 2 different methods of manual slide screening in semiautomated gynecologic cytology. Impact of reclassifying noninvasive follicular variant of papillary thyroid carcinoma on the risk of malignancy in The Bethesda System for Reporting Thyroid Cytopathology. Young investigator challenge: The accuracy of the nuclear-to-cytoplasmic ratio estimation among trained morphologists. |
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