Sex and gender analysis improves science and engineering
The goal of sex and gender analysis is to promote rigorous, reproducible and responsible
science. Incorporating sex and gender analysis into experimental design has enabled …
science. Incorporating sex and gender analysis into experimental design has enabled …
On the opportunities and risks of foundation models
AI is undergoing a paradigm shift with the rise of models (eg, BERT, DALL-E, GPT-3) that are
trained on broad data at scale and are adaptable to a wide range of downstream tasks. We …
trained on broad data at scale and are adaptable to a wide range of downstream tasks. We …
Data shapley: Equitable valuation of data for machine learning
A Ghorbani, J Zou - International conference on machine …, 2019 - proceedings.mlr.press
As data becomes the fuel driving technological and economic growth, a fundamental
challenge is how to quantify the value of data in algorithmic predictions and decisions. For …
challenge is how to quantify the value of data in algorithmic predictions and decisions. For …
The revival of the notes field: leveraging the unstructured content in electronic health records
Problem: Clinical practice requires the production of a time-and resource-consuming great
amount of notes. They contain relevant information, but their secondary use is almost …
amount of notes. They contain relevant information, but their secondary use is almost …
FasTag: Automatic text classification of unstructured medical narratives
Unstructured clinical narratives are continuously being recorded as part of delivery of care in
electronic health records, and dedicated tagging staff spend considerable effort manually …
electronic health records, and dedicated tagging staff spend considerable effort manually …
Machine learning for syndromic surveillance using veterinary necropsy reports
The use of natural language data for animal population surveillance represents a valuable
opportunity to gather information about potential disease outbreaks, emerging zoonotic …
opportunity to gather information about potential disease outbreaks, emerging zoonotic …
Using artificial intelligence to predict survivability likelihood and need for surgery in horses presented with acute abdomen (colic)
MA Fraiwan, SM Abutarbush - Journal of equine veterinary science, 2020 - Elsevier
Artificial intelligence and machine learning have promising applications in several medical
fields of diagnosis, imaging, and laboratory testing procedures. However, the use of this …
fields of diagnosis, imaging, and laboratory testing procedures. However, the use of this …
VetTag: improving automated veterinary diagnosis coding via large-scale language modeling
Unlike human medical records, most of the veterinary records are free text without standard
diagnosis coding. The lack of systematic coding is a major barrier to the growing interest in …
diagnosis coding. The lack of systematic coding is a major barrier to the growing interest in …
PetBERT: automated ICD-11 syndromic disease coding for outbreak detection in first opinion veterinary electronic health records
Effective public health surveillance requires consistent monitoring of disease signals such
that researchers and decision-makers can react dynamically to changes in disease …
that researchers and decision-makers can react dynamically to changes in disease …
Text mining for disease surveillance in veterinary clinical data: part one, the language of veterinary clinical records and searching for words
H Davies, G Nenadic, G Alfattni… - Frontiers in Veterinary …, 2024 - frontiersin.org
The development of natural language processing techniques for deriving useful information
from unstructured clinical narratives is a fast-paced and rapidly evolving area of machine …
from unstructured clinical narratives is a fast-paced and rapidly evolving area of machine …