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Found 7 papers, 1 papers with code
A Smart System to Generate and Validate Question Answer Pairs for COVID-19 Literature
Automatically generating question answer (QA) pairs from the rapidly growing coronavirus-related literature is of great value to the medical community.
FAIR Enough: How Can We Develop and Assess a FAIR-Compliant Dataset for Large Language Models' Training?
The rapid evolution of Large Language Models (LLMs) highlights the necessity for ethical considerations and data integrity in AI development, particularly emphasizing the role of FAIR (Findable, Accessible, Interoperable, Reusable) data principles.
MLHOps: Machine Learning for Healthcare Operations
We cover the foundational concepts of general machine learning operations, describe the initial setup of MLHOps pipelines (including data sources, preparation, engineering, and tools).
Bringing the State-of-the-Art to Customers: A Neural Agent Assistant Framework for Customer Service Support
Building Agent Assistants that can help improve customer service support requires inputs from industry users and their customers, as well as knowledge about state-of-the-art Natural Language Processing (NLP) technology.
An Experimental Evaluation of Transformer-based Language Models in the Biomedical Domain
With the growing amount of text in health data, there have been rapid advances in large pre-trained models that can be applied to a wide variety of biomedical tasks with minimal task-specific modifications.
A Computer Vision Approach to Combat Lyme Disease
Lyme disease is an infectious disease transmitted to humans by a bite from an infected Ixodes species (blacklegged ticks).
Evaluating Knowledge Transfer in Neural Network for Medical Images
To address this issue, we propose a teacher-student learning framework to transfer knowledge from a carefully pre-trained convolutional neural network (CNN) teacher to a student CNN.
