38 research outputs found

    A Kernel to Exploit Informative Missingness in Multivariate Time Series from EHRs

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    A large fraction of the electronic health records (EHRs) consists of clinical measurements collected over time, such as lab tests and vital signs, which provide important information about a patient's health status. These sequences of clinical measurements are naturally represented as time series, characterized by multiple variables and large amounts of missing data, which complicate the analysis. In this work, we propose a novel kernel which is capable of exploiting both the information from the observed values as well the information hidden in the missing patterns in multivariate time series (MTS) originating e.g. from EHRs. The kernel, called TCKIM_{IM}, is designed using an ensemble learning strategy in which the base models are novel mixed mode Bayesian mixture models which can effectively exploit informative missingness without having to resort to imputation methods. Moreover, the ensemble approach ensures robustness to hyperparameters and therefore TCKIM_{IM} is particularly well suited if there is a lack of labels - a known challenge in medical applications. Experiments on three real-world clinical datasets demonstrate the effectiveness of the proposed kernel.Comment: 2020 International Workshop on Health Intelligence, AAAI-20. arXiv admin note: text overlap with arXiv:1907.0525

    Track D Social Science, Human Rights and Political Science

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    Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/138414/1/jia218442.pd

    Le droit médical en Nouvelle-Calédonie

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    Le droit médical en Nouvelle-Calédonie

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    Discourse macrolinguistic impairment as a marker of linguistic and extralinguistic functions decline in early Alzheimer's disease

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    International audienceAbstract Background Alzheimer's disease is characterized by macrolinguistic changes. This decline is often analyzed with quantitative scales. Aims To analyze discourse production in early Alzheimer's disease (AD) and to identify qualitative markers of macrolinguistic decline. Methods & Procedures We analyzed macrolinguistic features of a clinical narrative task along with patients’ cognitive changes. To do so, 17 early AD participants and 17 healthy controls were recruited and given a full neuropsychological and language assessment. Narrative discourses produced during the language assessment were transcribed and macrolinguistic features were qualitatively analyzed (i.e., local and global coherence marks and discourse informativeness). Inter‐group comparison was complemented by intra‐group correlation. As some inter‐group comparisons revealed the existence of subgroups of patients, permutation tests were used to investigate how these subgroups differed vis‐à‐vis cognitive measures. Outcomes & Results Overall, the results indicate that AD participants presented declines in informativeness and global coherence, correlated with declines in memory and executive functions. Permutation tests showed that participants with AD producing referential errors or misinterpretations had a deeper lexical–executive decline and a lower Mini‐Mental State Evaluation (MMSE). Conclusions & Implications This study shows that two clinically relevant, qualitative signs differ in discourse production between typical ageing and early AD, namely information units and modalizing discourse. It also shows that macrolinguistic assessment is a useful tool for revealing impaired communication and cognition in early AD. Although lexical processing decline probably contributes to patients’ macrolinguistic impairment, implications of extralinguistic functioning should be further investigated

    Polymer-Based Honeycomb Films on Bioactive Glass : Toward a Biphasic Material for Bone Tissue Engineering Applications

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    The development of innovative materials for bone tissue engineering to promote bone regeneration while avoiding fibrous tissue infiltration is of paramount importance. Here, we combined the known osteopromotive properties of bioactive glasses (BaGs) with the biodegradability, biocompatibility, and ease to shape/handle of poly-l-co-d,l-lactic acid (PLDLA) into a single biphasic material. The aim of this work was to unravel the role of the surface chemistry and topography of BaG surfaces on the stability of a PLDLA honeycomb membrane, in dry and wet conditions. The PLDLA honeycomb membrane was deposited using the breath figure method (BFM) on the surface of untreated BaG discs (S53P4 and 13-93B20), silanized with 3-aminopropyltriethoxysilane (APTES) or conditioned (immersed for 24 h in TRIS buffer solution). The PLDLA membranes deposited onto the BaG discs, regardless of their composition or surface treatments, exhibited a honeycomb-like structure with pore diameter ranging from 1 to 5 ÎŒm. The presence of positively charged amine groups (APTES grafting) or the precipitation of a CaP layer (conditioned) significantly improved the membrane resistance to shear as well as its stability upon immersion in the TRIS buffer solution. The obtained results demonstrated that the careful control of the substrate surface chemistry enabled the deposition of a stable honeycomb membrane at their surface. This constitutes a first step toward the development of new biphasic materials enabling osteostimulation (BaG) while preventing migration of fibrous tissue inside the bone defect (honeycomb polymer membrane).publishedVersionPeer reviewe
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