A supervised cooperative learning system for early detection of language disorders

The Quality of Life of a person may depend on early attention to his neurodevel-opment disorders in childhood. Identification of language disorders under the age of six years old can speed up required diagnosis and/or treatment processes. This paper details the enhancement of a Clinical Decision Support System (CDSS) aimed to assist pediatricians and language therapists at early identification and re-ferral of language disorders. The system helps to fine tune the Knowledge Base of Language Delays (KBLD) that was already developed and validated in clinical routine with 146 children. Medical experts supported the construction of Gades CDSS by getting scientific consensus from literature and fifteen years of regis-tered use cases of children with language disorders. The current research focuses on an innovative cooperative model that allows the evolution of the KBLD of Gades through the supervised evaluation of the CDSS learnings with experts¿ feedback. The deployment of the resulting system is being assessed under a mul-tidisciplinary team of seven experts from the fields of speech therapist, neonatol-ogy, pediatrics, and neurology.

Classifying GABAergic interneurons with semi-supervised projected model-based clustering

Objectives: A recently introduced pragmatic scheme promises to be a useful catalog of interneuron names.We sought to automatically classify digitally reconstructed interneuronal morphologies according tothis scheme. Simultaneously, we sought to discover possible subtypes of these types that might emergeduring automatic classification (clustering). We also investigated which morphometric properties weremost relevant for this classification.Materials and methods: A set of 118 digitally reconstructed interneuronal morphologies classified into thecommon basket (CB), horse-tail (HT), large basket (LB), and Martinotti (MA) interneuron types by 42 of theworld?s leading neuroscientists, quantified by five simple morphometric properties of the axon and fourof the dendrites. We labeled each neuron with the type most commonly assigned to it by the experts. Wethen removed this class information for each type separately, and applied semi-supervised clustering tothose cells (keeping the others? cluster membership fixed), to assess separation from other types and lookfor the formation of new groups (subtypes). We performed this same experiment unlabeling the cells oftwo types at a time, and of half the cells of a single type at a time. The clustering model is a finite mixtureof Gaussians which we adapted for the estimation of local (per-cluster) feature relevance. We performedthe described experiments on three different subsets of the data, formed according to how many expertsagreed on type membership: at least 18 experts (the full data set), at least 21 (73 neurons), and at least26 (47 neurons).Results: Interneurons with more reliable type labels were classified more accurately. We classified HTcells with 100% accuracy, MA cells with 73% accuracy, and CB and LB cells with 56% and 58% accuracy,respectively. We identified three subtypes of the MA type, one subtype of CB and LB types each, andno subtypes of HT (it was a single, homogeneous type). We got maximum (adapted) Silhouette widthand ARI values of 1, 0.83, 0.79, and 0.42, when unlabeling the HT, CB, LB, and MA types, respectively,confirming the quality of the formed cluster solutions. The subtypes identified when unlabeling a singletype also emerged when unlabeling two types at a time, confirming their validity. Axonal morphometricproperties were more relevant that dendritic ones, with the axonal polar histogram length in the [pi, 2pi) angle interval being particularly useful.Conclusions: The applied semi-supervised clustering method can accurately discriminate among CB, HT, LB, and MA interneuron types while discovering potential subtypes, and is therefore useful for neuronal classification. The discovery of potential subtypes suggests that some of these types are more heteroge-neous that previously thought. Finally, axonal variables seem to be more relevant than dendritic ones fordistinguishing among the CB, HT, LB, and MA interneuron types.

Chaperone-supervised conversion of prion protein to its protease-resistant form

Transmissible spongiform encephalopathies (TSEs) are lethal, infectious disorders of the mammalian nervous system. A TSE hallmark is the conversion of the cellular protein PrPC to disease-associated PrPSc (named for scrapie, the first known TSE). PrPC is protease-sensitive, monomeric, detergent soluble, and primarily α-helical; PrPSc is protease-resistant, polymerized, detergent insoluble, and rich in β-sheet. The “protein-only” hypothesis posits that PrPSc is the infectious TSE agent that directly converts host-encoded PrPC to fresh PrPSc, harming neurons and creating new agents of infection. To gain insight on the conformational transitions of PrP, we tested the ability of several protein chaperones, which supervise the conformational transitions of proteins in diverse ways, to affect conversion of PrPC to its protease-resistant state. None affected conversion in the absence of pre-existing PrPSc. In its presence, only two, GroEL and Hsp104 (heat shock protein 104), significantly affected conversion. Both promoted it, but the reaction characteristics of conversions with the two chaperones were distinct. In contrast, chemical chaperones inhibited conversion. Our findings provide new mechanistic insights into nature of PrP conversions, and provide a new set of tools for studying the process underlying TSE pathogenesis.

Costs as an aid to management as operated in plants supervised by S.K.F. Industries, Inc.

Mode of access: Internet.

Supervised study in mathematics and science,

Bibliography: p. 229-231.

Postoperative Analgesia Following Sciatic Nerve Blockade Administered by Nurse Anesthetists Supervised by Regional Anesthesia Faculty in an Academic Hospital

Introduction: Assessment of expertise in regional anesthesia techniques is traditionally based upon quota fulfillment of procedures during training. Validation of practitioner proficiency in performing procedures in surgical specialties has moved from simple measurement of technical skills to evaluation of global patient outcomes. Complete absence of pain as a result of nerve blockade is the most important clinical endpoint but patient, technical and procedural factors influence results. The purpose of this study was to measure the postoperative pain scores and associated analgesic medication requirements for patients administered sciatic nerve blockade by nurse anesthetists and determine patient or procedural factors that influenced this outcome. Methods: Either nerve stimulator or ultrasound guided sciatic nerve blockade was administered by nurse anesthetists under the supervision of regional anesthesia faculty. Patient demographic data that was collected included gender, body mass index, surgical procedure, and pre-existing chronic pain with associated opioid use. Patient self-reported pain scores and opioid analgesic dosages in the preoperative, intraoperative, immediate postoperative and 24 hour post procedure intervals were recorded. Results: 22 nurse anesthetists administered sciatic nerve blockade to 48 patients during a 36 month interval. Transition from a nerve stimulator to ultrasound guided sciatic nerve block technique resulted in lower mean pain scores. Patients reporting chronic opioid use were observed to have elevated perioperative opioid analgesic requirements and pain scores compared to opioid naïve patients. Conclusion: Effective analgesia is a prime measure for assessing expertise in regional anesthesia and continuous evaluation of this outcome in everyday practice is proposed.

Parent Engagement in Supported Supervised Visitation in Child Welfare

Thesis (Master's)--University of Washington, 2016-06

Graph-based Semi-Supervised Learning in Acoustic Modeling for Automatic Speech Recognition

Thesis (Ph.D.)--University of Washington, 2016-06

Supervised stationary cycling versus supervised treadmill walking for patients with intermittent claudication: Preliminary results

Introduction: Walking programmes are recommended as part of the initial treatment for intermittent claudication (IC). However, for many patients factors such as frailty, the severe leg discomfort associated with walking and safety concerns about exercising in public areas reduce compliance to such prescription. Thus, there is a need to identify a mode of exercise that provides the same benefits as regular walking while also offering convenience and comfort for these patients. The present study aims to provide evidence for the first time of the efficacy of a supervised cycle training programme compared with a conventional walking programme for the treatment of IC. Methods: Thus far 33 patients have been randomized to: a treadmill-training group (n = 12); a cycle-training group (n = 11); or a control group (n = 10). Training groups participated in three sessions of supervised training per week for a period of 6 weeks. Control patients received no experimental intervention. Maximal incremental treadmill testing was performed at baseline and after the 6 weeks of training. Measures included pain-free (PFWT) and maximal walking time (MWT), continuous heart rate and gas-analysis recording, and ankle-brachial index assessment. Results: In the treadmill trained group MWT increased significantly from 1016.7 523.7 to 1255.2 432.2 s (P < 0.05). MWT tended to increase with cycle training (848.72 333.18 to 939.54 350.35 s, P = 0.14), and remained unchanged in the control group (1555.1 683.23 to 1534.7 689.87 s). For PFWT, there was a non-significant increase in the treadmill-training group from 414.4 262.3 to 592.9 381.9 s, while both the cycle training and control groups displayed no significant change in this time (226.7 147.1 s to 192.3 56.8 and 499.4 503.7 s to 466.0 526.1 s, respectively). Conclusions: These preliminary results might suggest that, unlike treadmill walking, cycling has no clear effect on walking performance in patients with IC. Thus the current recommendations promoting walking based programmes appear appropriate. The present study was funded by the National Heart Foundation of Australia.

Semi-supervised construction of general visualization hierarchies

We have recently developed a principled approach to interactive non-linear hierarchical visualization [8] based on the Generative Topographic Mapping (GTM). Hierarchical plots are needed when a single visualization plot is not sufficient (e.g. when dealing with large quantities of data). In this paper we extend our system by giving the user a choice of initializing the child plots of the current plot in either interactive, or automatic mode. In the interactive mode the user interactively selects ``regions of interest'' as in [8], whereas in the automatic mode an unsupervised minimum message length (MML)-driven construction of a mixture of GTMs is used. The latter is particularly useful when the plots are covered with dense clusters of highly overlapping data projections, making it difficult to use the interactive mode. Such a situation often arises when visualizing large data sets. We illustrate our approach on a data set of 2300 18-dimensional points and mention extension of our system to accommodate discrete data types.