462 research outputs found
Computing Individual Risks based on Family History in Genetic Disease in the Presence of Competing Risks
When considering a genetic disease with variable age at onset (ex: diabetes ,
familial amyloid neuropathy, cancers, etc.), computing the individual risk of
the disease based on family history (FH) is of critical interest both for
clinicians and patients. Such a risk is very challenging to compute because: 1)
the genotype X of the individual of interest is in general unknown; 2) the
posterior distribution P(X|FH, T > t) changes with t (T is the age at disease
onset for the targeted individual); 3) the competing risk of death is not
negligible. In this work, we present a modeling of this problem using a
Bayesian network mixed with (right-censored) survival outcomes where hazard
rates only depend on the genotype of each individual. We explain how belief
propagation can be used to obtain posterior distribution of genotypes given the
FH, and how to obtain a time-dependent posterior hazard rate for any individual
in the pedigree. Finally, we use this posterior hazard rate to compute
individual risk, with or without the competing risk of death. Our method is
illustrated using the Claus-Easton model for breast cancer (BC). This model
assumes an autosomal dominant genetic risk factor such as non-carriers
(genotype 00) have a BC hazard rate 0 (t) while carriers (genotypes
01, 10 and 11) have a (much greater) hazard rate 1 (t). Both hazard
rates are assumed to be piecewise constant with known values (cuts at 20, 30,.
.. , 80 years). The competing risk of death is derived from the national French
registry
La Bibliothèque Fantastique
"La Bibliothèque Fantastique is an artist’s books virtual publisher. Our books are free and downloadable from the internet so that you can print them at home. Most of our books are exclusive productions. The others are reeditions of works who are free of any kind of rights. The purpose of LBF is to offer a view on books expressed by books themselves. Its works are made of excerpts of other works, with pages, sentences and words met in a stroke of good fortune. La Bibliothèque Fantastique is a minimalist publisher in the sense that all the superfluous has been removed. Indeed, the books of LBF have no predetermined physical existence, they exist in a state of potentiality on the web, awaiting to become. They cost nothing, you can get them without spending a penny. They have no ISBN either, because they are works of art. They have no color, so that they can be printed in any printer. That's what LBF books don’t have, which is almost more important than what they do, because our approach is conceived as a negative of that which is habitually proposed by the market spectacle society. The idea is to show various poetic singularities as opposed to the flashy commodities which our society feeds us." -- Publisher's website
Alloprof: a new French question-answer education dataset and its use in an information retrieval case study
Teachers and students are increasingly relying on online learning resources
to supplement the ones provided in school. This increase in the breadth and
depth of available resources is a great thing for students, but only provided
they are able to find answers to their queries. Question-answering and
information retrieval systems have benefited from public datasets to train and
evaluate their algorithms, but most of these datasets have been in English text
written by and for adults. We introduce a new public French question-answering
dataset collected from Alloprof, a Quebec-based primary and high-school help
website, containing 29 349 questions and their explanations in a variety of
school subjects from 10 368 students, with more than half of the explanations
containing links to other questions or some of the 2 596 reference pages on the
website. We also present a case study of this dataset in an information
retrieval task. This dataset was collected on the Alloprof public forum, with
all questions verified for their appropriateness and the explanations verified
both for their appropriateness and their relevance to the question. To predict
relevant documents, architectures using pre-trained BERT models were fine-tuned
and evaluated. This dataset will allow researchers to develop
question-answering, information retrieval and other algorithms specifically for
the French speaking education context. Furthermore, the range of language
proficiency, images, mathematical symbols and spelling mistakes will
necessitate algorithms based on a multimodal comprehension. The case study we
present as a baseline shows an approach that relies on recent techniques
provides an acceptable performance level, but more work is necessary before it
can reliably be used and trusted in a production setting
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