After human genome mapping, omics revolution and empowering sequencing technologies developed at the turn of the century, new deals are to switch from population medicine to individual therapies, from curing the disease to preventing it. This review by the pharmacogenetics and predictive medicine working group of the French clinical biology society (SFBC) aims at placing into perspective the notions of tailored medicine, pharmacogenetics, genetics and genomics, emphasizing their interactions and discussing their signifiance according to researchers and to clinicians.
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http://dx.doi.org/10.1684/abc.2012.0767 | DOI Listing |
Psychon Bull Rev
January 2025
Université Grenoble Alpes, Université Savoie Mont Blanc, CNRS, LPNC, 38000, Grenoble, France.
It is striking that visual attention, the process by which attentional resources are allocated in the visual field so as to locally enhance visual perception, is a pervasive component of models of eye movements in reading, but is seldom considered in models of isolated word recognition. We describe BRAID, a new Bayesian word-Recognition model with Attention, Interference and Dynamics. As most of its predecessors, BRAID incorporates three sensory, perceptual, and orthographic knowledge layers together with a lexical membership submodel.
View Article and Find Full Text PDFJ Psycholinguist Res
January 2025
Department of Linguistics, University of Potsdam, Potsdam, Germany.
Rhythm perception in speech and non-speech acoustic stimuli has been shown to be affected by general acoustic biases as well as by phonological properties of the native language of the listener. The present paper extends the cross-linguistic approach in this field by testing the application of the iambic-trochaic law as an assumed general acoustic bias on rhythmic grouping of non-speech stimuli by speakers of three languages: Arabic, Hebrew and German. These languages were chosen due to relevant differences in their phonological properties on the lexical level alongside similarities on the phrasal level.
View Article and Find Full Text PDFFront Psychol
December 2024
School of Psychology, Korea University, Seoul, Republic of Korea.
Introduction: This investigation aimed to explore interhemispheric interactions in visual word processing with a focus on proficiency development. Given the asymmetrical specialization in visual word processing across hemispheres, the study hypothesized that the primary hemisphere predominantly regulates interhemispheric interactions. The familiarity effect, serving as a measure of visual word processing proficiency, was examined to determine how proficiency influences these interactions.
View Article and Find Full Text PDFSci Rep
December 2024
Department of Electrical, Electronic, and Computer Engineering, University of Ulsan, Ulsan, Republic of Korea.
Semantic processing is an essential mechanism in human language comprehension and has profound implications for speech brain-computer interface technologies. Despite recent advances in brain imaging techniques and data analysis algorithms, the mechanisms underlying human brain semantic representations remain a topic of debate, specifically whether this occurs through the activation of selectively separated cortical regions or via a network of distributed and overlapping regions. This study investigates spatiotemporal neural representation during the perception of semantic words related to faces, numbers, and animals using electroencephalography.
View Article and Find Full Text PDFPeerJ Comput Sci
June 2024
Institute of Medical Information, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China.
Background: To make the question text represent more information and construct an end-to-end text clustering model, we propose a double-target self-supervised clustering with multi-feature fusion (MF-DSC) for texts which describe questions related to the medical field. Since medical question-and-answer data are unstructured texts and characterized by short characters and irregular language use, the features extracted by a single model cannot fully characterize the text content.
Methods: Firstly, word weights were obtained based on term frequency, and word vectors were generated according to lexical semantic information.
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