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Found 5 papers, 1 papers with code
Helpful or Harmful? Exploring the Efficacy of Large Language Models for Online Grooming Prevention
Powerful generative Large Language Models (LLMs) are becoming popular tools amongst the general public as question-answering systems, and are being utilised by vulnerable groups such as children.
Text generation for dataset augmentation in security classification tasks
Security classifiers, designed to detect malicious content in computer systems and communications, can underperform when provided with insufficient training data.
Correspondence on ACMG STATEMENT: ACMG SF v3.0 list for reporting of secondary findings in clinical exome and genome sequencing: a policy statement of the American College of Medical Genetics and Genomics (ACMG) by Miller et al
We were interested to read the recent update on recommendations for reporting of secondary findings in clinical sequencing1, and the accompanying updated list of genes in which secondary findings should be sought (ACMG SF v3. 0)2.
EigenRank by Committee: A Data Subset Selection and Failure Prediction paradigm for Robust Deep Learning based Medical Image Segmentation
Translation of fully automated deep learning based medical image segmentation technologies to clinical workflows face two main algorithmic challenges.
Extreme Augmentation : Can deep learning based medical image segmentation be trained using a single manually delineated scan?
In the extreme, we observed that a model trained on patches extracted from just one scan, with each patch augmented 50 times; achieved a Dice score of 0. 73 in a validation set of 40 cases.
