NLM DIR Seminar Schedule
UPCOMING SEMINARS
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April 8, 2025 Jaya Srivastava
TBD -
April 15, 2025 Pascal Mutz
TBD -
April 18, 2025 Valentina Boeva, Department of Computer Science, ETH Zurich
Decoding tumor heterogeneity: computational methods for scRNA-seq and spatial omics -
April 22, 2025 Stanley Liang
TBD -
April 29, 2025 MG Hirsch
TBD
RECENT SEMINARS
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April 1, 2025 Roman Kogay
Horizontal transfer of bacterial operons into eukaryote genomes -
March 25, 2025 Yifan Yang
Adversarial Manipulation and Data Memorization in Large Language Models for Medicine -
March 11, 2025 Sofya Garushyants
Tmn – bacterial anti-phage defense system -
March 4, 2025 Sanasar Babajanyan
Evolution of antivirus defense in prokaryotes depending on the environmental virus load -
Feb. 25, 2025 Zhizheng Wang
GeneAgent: Self-verification Language Agent for Gene Set Analysis using Domain Databases
Scheduled Seminars on June 7, 2022
Contact NLMDIRSeminarScheduling@mail.nih.gov with questions about this seminar.
Abstract:
The technique of deep learning, or artificial intelligence (AI) broadly, has been employed in a lot of medical informatics research driven by imaging data. Topics such as classification and object detection have been actively studied in the field. It is well known that deep learning is data hungry technique. However, a higher data quantity doesn’t always guarantee higher performance. Data quality is also important for training of a robust deep learning model. In our studies using medical imaging data, quality factors include image sharpness, resolution, image labeling, specular reflection, data noise, etc. In this talk, several deep learning techniques will be introduced for dataset filtering, data augmentation, data enhancement, etc. These techniques are used to recode our cervical cancer datasets to achieve higher data quality.