Results 131 to 140 of about 191,564 (306)

Advancing cardio‐obstetric care through digital health technologies: A narrative review

ESC Heart Failure, EarlyView.
Telehealth has enhanced prenatal and post‐partum care by improving access, continuity, and equity, particularly for high‐risk and underserved populations, without compromising maternal or fetal outcomes. Wearable and digital health technologies (e.g., electrocardiogram sensors, remote BP monitoring, mobile interventions) show strong potential to ...
Toluwalase Awoyemi, Oluwaremilekun Zeth Tolu‐Akinnawo, Arun Mahtani, Inderbir Padda, Kayode Emmanuel Ogunniyi, Ikeoluwapo Kendra Bolakale‐Rufai, Abiola Olusanya, Adeleke Oluwaseun Dorcas, Chituru Believe Amarachi, Olumide Damilola Akinmoju, Christabel Ijeoma Uche‐Orji, Mina Fattah   +11 more
wiley   +1 more source

Feasibility report: Delivering case-study based learning using artificial intelligence and gaming technologies [PDF]

This document describes an investigation into the technical feasibility of a game to support learning based on case studies. Information systems students using the game will conduct fact-finding interviews with virtual characters.
Cresswell, Stephen, Prigmore, Martyn
core  

Computational linguistics and its use in real world [PDF]

, 1996
Michael Zock
openalex   +1 more source

Alignment and Differentiation: How Language and Network Proximity Drive Opinion‐Based Group Formation Online

European Journal of Social Psychology, EarlyView.
ABSTRACT This study examines the interplay between language and social connectedness in forming opinion‐based groups on social media. Drawing on small‐world theory and social identity theory, we propose a dual‐layer approach that combines semantic and network analysis to investigate the dynamics of group formation on X/Twitter during the 2021 COVID‐19 ...
Davide Morselli, Kevin Durrheim, Maite Beramendi, Melody Sepahpour‐Fard, Martin Mafunda, Andres Martinez Torres, Nnaemeka Ohamadike, Mike Quayle, Maria Schuld   +8 more
wiley   +1 more source

AI language model applications for early diagnosis of childhood epilepsy based on unstructured first‐visit patient narratives: A cohort study

Epileptic Disorders, EarlyView.
Abstract Objective Language serves as an indispensable source of information for diagnosing epilepsy, and its computational analysis is increasingly explored. This study assessed – and compared – the diagnostic value of different language model applications in extracting information.
Jitse Loyens, Geertruida Slinger, Nynke Doornebal, Kees P. J. Braun, Eric van Diessen, Willem M. Otte   +5 more
wiley   +1 more source

Performance analysis of ISC journals using Scopus and ISC indicators

International Journal of Information Science and Management, 2016
Journal performance metrics are designed to help users know the best journals in different scientific fields. In this article, some journals indexed in ISC database are compared using Scopus and ISC performance indicators.
Hamid Alizade
doaj  

Exploring the role of apolipoprotein ε4 in progressive myoclonic epilepsy type 1

Epileptic Disorders, EarlyView.
Abstract Objective Progressive myoclonic epilepsy type 1 (EPM1) is a neurodegenerative disease caused by biallelic variants in the cystatin B (CSTB) gene. Despite a progressive course, phenotype severity varies among patients, even within families. We studied the potential role of APOE ε4 in modifying phenotypic diversity in EPM1, given its established
Janina Gunnar, Yawu Liu, Henri Eronen, Tarja Joensuu, Marja Äikiä, Jelena Hyppönen, Katri Silvennoinen, Esa Mervaala, Juhana Hakumäki, Anna‐Elina Lehesjoki, Reetta Kälviäinen   +10 more
wiley   +1 more source

Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers)

, 2018

openalex   +1 more source

Proceedings of 52nd Annual Meeting of the Association for Computational Linguistics: System Demonstrations [PDF]

, 2014

openalex   +1 more source

Affective Dimensions in Maternal Voice During Child Feeding in Mothers With and Without Eating Disorder History—Findings From a Machine Learning Analysis of Speech Data

European Eating Disorders Review, EarlyView.
ABSTRACT Objective Eating disorder (ED) history may impact mother‐child communication during mealtimes and contribute to transgenerational transmission of ED. This study employed machine learning (ML) to identify speech characteristics during mother‐child feeding interactions, aiming for investigating whether vocalised affective characteristics differ ...
Jana Katharina Throm, Manuel Milling, Andreas Triantafyllopoulos, Alexander Kathan, Annica Franziska Dörsam, Johanna Löchner, Björn Schuller, Katrin Elisabeth Giel   +7 more
wiley   +1 more source