Development of a Knowledge Base for smart screening of language disorders in primary care

Monitoring of neuro-evolutive development from birth until the age of six is a decisive factor in a child's quality of life. Early detection of development disorders in early childhood can facilitate necessary diagnosis and/or treatment. Primary-care pediatricians play a key role in early detection of development alterations as they can undertake the preventive and therapeutic actions necessary in the interest of a child's optimal development. The focus of this research paper is the construction of a Knowledge Base for smart screening aimed to assist pediatricians in processes of early referral in language disorders. The proposed model provides health professionals with a decision-making tool that supports referral processes. In this way, essential diagnostic and/or therapeutic actions are triggered for a comprehensive individual development. The resulting system was developed on the basis of an analysis and verification of 21 cases of children with language disorders

A review of the methodological features of systematic reviews in maternal medicine

Background In maternal medicine, research evidence is scattered making it difficult to access information for clinical decision making. Systematic reviews of good methodological quality are essential to provide valid inferences and to produce usable evidence summaries to guide management. This review assesses the methodological features of existing systematic reviews in maternal medicine, comparing Cochrane and non-Cochrane reviews in maternal medicine. Methods Medline, Embase, Database of Reviews of Effectiveness (DARE) and Cochrane Database of Systematic Reviews (CDSR) were searched for relevant reviews published between 2001 and 2006. We selected those reviews in which a minimum of two databases were searched and the primary outcome was related to the maternal condition. The selected reviews were assessed for information on framing of question, literature search and methods of review. Results Out of 2846 citations, 68 reviews were selected. Among these, 39 (57%) were Cochrane reviews. Most of the reviews (50/68, 74%) evaluated therapeutic interventions. Overall, 54/68 (79%) addressed a focussed question. Although 64/68 (94%) reviews had a detailed search description, only 17/68 (25%) searched without language restriction. 32/68 (47%) attempted to include unpublished data and 11/68 (16%) assessed for the risk of missing studies quantitatively. The reviews had deficiencies in the assessment of validity of studies and exploration for heterogeneity. When compared to Cochrane reviews, other reviews were significantly inferior in specifying questions (OR 20.3, 95% CI 1.1–381.3, p = 0.04), framing focussed questions (OR 30.9, 95% CI 3.7- 256.2, p = 0.001), use of unpublished data (OR 5.6, 95% CI 1.9–16.4, p = 0.002), assessment for heterogeneity (OR 38.1, 95%CI 2.1, 688.2, p = 0.01) and use of meta-analyses (OR 3.7, 95% CI 1.3–10.8, p = 0.02). Conclusion This study identifies areas which have a strong influence on maternal morbidity and mortality but lack good quality systematic reviews. Overall quality of the existing systematic reviews was variable. Cochrane reviews were of better quality as compared to other reviews. There is a need for good quality systematic reviews to inform practice in maternal medicine

Validation tool for smart screening of language disorders in pediatrics care

Primary-care pediatricians could play a key role in early detection of development disorders as quick as they might have enough time and knowledge for suitable screenings at clinical routine. This research paper focuses on the development and validation of a knowledge-based web tool whose aim is to support a smart detection of developmental disorders in early childhood. Thus, the use of the system can trigger the necessary preventive and therapeutic actions from birth until the age of six. The platform was designed on the basis of an analysis of significant 21 cases of children with language disorders that supported the creation of a specific knowledge base, its ontology and a set of description logic relations. The resulting system is being validated in a scalable approach with a team of seven experts from the fields of neonathology, pediatrics, neurology and language therapy

Deployment and validation of a smart system for screening of language disorders in primary care

Neuro-evolutive development from birth until the age of six years is a decisive factor in a child?s quality of life. Early detection of development disorders in early childhood can facilitate necessary diagnosis and/or treatment. Primary-care pediatricians play a key role in its detection as they can undertake the preventive and therapeutic actions requested to promote a child?s optimal development. However, the lack of time and little specific knowledge at primary-care avoid to applying continuous early-detection anomalies procedures. This research paper focuses on the deployment and evaluation of a smart system that enhances the screening of language disorders in primary care. Pediatricians get support to proceed with early referral of language disorders. The proposed model provides them with a decision-support tool for referral actions to trigger essential diagnostic and/or therapeutic actions for a comprehensive individual development. The research was conducted by starting from a sample of 60 cases of children with language disorders. Validation was carried out through two complementary steps: first, by including a team of seven experts from the fields of neonatology, pediatrics, neurology and language therapy, and, second, through the evaluation of 21 more previously diagnosed cases. The results obtained show that therapist positively accepted the system proposal in 18 cases (86%) and suggested system redesign for single referral to a speech therapist in three remaining cases

Increasing the Effectiveness and Efficiency of Existing Public Investments in Early Childhood Education: Recommendations to Boost Program Outcomes and Efficiency

Proposes ten reforms to maximize the impact of Head Start, Child Care Development Block Grants, and other existing funding streams, including working with states to align standards, improving provider quality, and enhancing data collection and reporting

Use of nonintrusive sensor-based information and communication technology for real-world evidence for clinical trials in dementia

Cognitive function is an important end point of treatments in dementia clinical trials. Measuring cognitive function by standardized tests, however, is biased toward highly constrained environments (such as hospitals) in selected samples. Patient-powered real-world evidence using information and communication technology devices, including environmental and wearable sensors, may help to overcome these limitations. This position paper describes current and novel information and communication technology devices and algorithms to monitor behavior and function in people with prodromal and manifest stages of dementia continuously, and discusses clinical, technological, ethical, regulatory, and user-centered requirements for collecting real-world evidence in future randomized controlled trials. Challenges of data safety, quality, and privacy and regulatory requirements need to be addressed by future smart sensor technologies. When these requirements are satisfied, these technologies will provide access to truly user relevant outcomes and broader cohorts of participants than currently sampled in clinical trials

A Cooperative Decison Support System for Children's Neurodevelopment Monitoring.

Decision Support Systems can enhance e-Health monitoring and IoT scenarios on the early detection of neurodevelopmental disorders in children. Thus, Ambient Intelligence could support innovative application domains like motor or cognitive impairments? detection at the home environment. The paper describes the design of an innovative cooperative system (Galatea) that supports the refinement process of a Knowledge Base expressed as an OWL ontology. The ontology supports decision-making process and is the core of: (1) a Web-Based Smart System aimed to enhance the screening of language disorders at medical centers and schools by fostering the identification of a developmental disorders before 4 years old of age; (2) a set of child smart care services that use Ambient Intelligent paradigm for early attention of motor impairments in children who are often not diagnosed or treated by health care entities

North Carolina's ABCD Program: Using Community Care Networks to Improve the Delivery of Childhood Developmental Screening and Referral to Early Intervention Services

Profiles community care networks' approaches to implementing the Assuring Better Child Health and Development (ABCD) program. Examines activities to increase screening for and interventions in developmental disabilities and delays, impact, and insights

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

Tests for predicting complications of pre-eclampsia: A protocol for systematic reviews

Background Pre-eclampsia is associated with several complications. Early prediction of complications and timely management is needed for clinical care of these patients to avert fetal and maternal mortality and morbidity. There is a need to identify best testing strategies in pre eclampsia to identify the women at increased risk of complications. We aim to determine the accuracy of various tests to predict complications of pre-eclampsia by systematic quantitative reviews. Method We performed extensive search in MEDLINE (1951–2004), EMBASE (1974–2004) and also will also include manual searches of bibliographies of primary and review articles. An initial search has revealed 19500 citations. Two reviewers will independently select studies and extract data on study characteristics, quality and accuracy. Accuracy data will be used to construct 2 × 2 tables. Data synthesis will involve assessment for heterogeneity and appropriately pooling of results to produce summary Receiver Operating Characteristics (ROC) curve and summary likelihood ratios. Discussion This review will generate predictive information and integrate that with therapeutic effectiveness to determine the absolute benefit and harm of available therapy in reducing complications in women with pre-eclampsia