6 research outputs found
A Text Mining Pipeline Using Active and Deep Learning Aimed at Curating Information in Computational Neuroscience
The curation of neuroscience entities is crucial to ongoing efforts in neuroinformatics and computational neuroscience, such as those being deployed in the context of continuing large-scale brain modelling projects. However, manually sifting through thousands of articles for new information about modelled entities is a painstaking and low-reward task. Text mining can be used to help a curator extract relevant information from this literature in a systematic way. We propose the application of text mining methods for the neuroscience literature. Specifically, two computational neuroscientists annotated a corpus of entities pertinent to neuroscience using active learning techniques to enable swift, targeted annotation. We then trained machine learning models to recognise the entities that have been identified. The entities covered are Neuron Types, Brain Regions, Experimental Values, Units, Ion Currents, Channels, and Conductances and Model organisms. We tested a traditional rule-based approach, a conditional random field and a model using deep learning named entity recognition, finding that the deep learning model was superior. Our final results show that we can detect a range of named entities of interest to the neuroscientist with a macro average precision, recall and F1 score of 0.866, 0.817 and 0.837 respectively. The contributions of this work are as follows: 1) We provide a set of Named Entity Recognition (NER) tools that are capable of detecting neuroscience entities with performance above or similar to prior work. 2) We propose a methodology for training NER tools for neuroscience that requires very little training data to get strong performance. This can be adapted for any sub-domain within neuroscience. 3) We provide a small corpus with annotations for multiple entity types, as well as annotation guidelines to help others reproduce our experiments
Sur l'identification expérimentale de l'amortissement dans les stratifiés carbone/epoxy ― Effets sur la stabilité des rotors composites
ISBN : 978-2877170901International audienceCe travail s'intéresse à l'identification et la modélisation de l'amortissement dans les matériaux carbone/époxy, puis à l'effet de cette modélisation sur la stabilité des rotors composites. L'identification de l'amortissement est issue de deux expériences réalisées au LaMCoS et deux autres effectuées au LMA. Celles-ci sont réalisées sur plusieurs poutres carbone/époxy en conditions encastré-libre ou libre-libre. Les éprouvettes étudiées ([0°]10, [90°]10, [+45°/,-45°]3s en G947/M18) permettent d'obtenir l'ensemble des facteurs d'amortissement du pli sous un état de contraintes planes. Le comportement identifié est proche du modèle hystérétique. L'effet de cet amortissement est ensuite abordé via différents modèles de rotors comparativement à un exemple expérimental
Challenges in Facing the Lung Cancer Epidemic and Treating Advanced Disease in Latin America
Latin America will soon be facing a lung cancer epidemic. The region is not prepared to deal with the amount of patients and the resources needed to give the patients proper state of the art molecular diagnosis and access to targeted therapies. In this paper, we review the current management of lung cancer in Latin America from the clinician's perspective.
Lung cancer, the deadliest cancer worldwide, is of particular concern in Latin America. The rising incidence poses a myriad of challenges for the region, which struggles with limited resources to meet the health care needs of its low- and middle-income populations. In this environment, we are concerned that governments are relatively unaware of the pressing need to implement effective strategies for screening, diagnosis, and treatment of lung cancer. The region has also been slow in adopting molecularly-based therapies in the treatment of advanced disease: testing for epidermal growth factor receptor mutations and anaplastic lymphoma kinase rearrangements are not routine, and access to targeted agents such as monoclonal antibodies and tyrosine kinase inhibitors is problematic. In this paper, we review the current situation in the management of lung cancer in Latin America, hoping that this initiative will help physicians, patient associations, industry, governments, and other stakeholders better face this epidemic in the near future
A Reduced-Order Model of Detuned Cyclic Dynamical Systems With Geometric Modifications Using a Basis of Cyclic Modes
Salami et alv�olite allergique extrins�que: Une nouvelle pathologie professionnelle en Suisse
Nivolumab versus everolimus in patients with advanced renal cell carcinoma: Updated results with long‐term follow‐up of the randomized, open‐label, phase 3 CheckMate 025 trial
Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/156483/3/cncr33033_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/156483/2/cncr33033.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/156483/1/cncr33033-sup-0004-Revprot07.pd