bluuebunny/crossref_metadata_2025_split huggingface dataset:
Use of Social Media Data Mining to Examine Needs, Concerns, and Experiences of People With Traumatic Brain Injury
Authors: Pei Yalian , O'Brien Katy H. 
Published: December 2023

Purpose:
Given the limited availability of topic-specific resources, many people turn to anonymous social media platforms such as Reddit to seek information and connect to others with similar experiences and needs. Mining of such data can therefore identify unmet needs within the community and allow speech-language pathologists to incorporate clients' real-life insights into clinical practices.

Method:
A mixed-method analysis was performed on 3,648 traumatic brain injury (TBI) subreddit posts created between 2013 and 2021. Sentiment analysis was used to determine the sentiment expressed in each post; topic modeling and qualitative content analysis were used to uncover the main topics discussed across posts. Subgroup analyses were conducted based on injury severity, chronicity, and whether the post was authored by a person with TBI or a close other.

Results:
There was no significant difference between the number of posts with positive sentiment and the number of posts with negative sentiment. Comparisons between subgroups showed significantly higher positive sentiment in posts by or about people with moderate-to-severe TBI (compared to mild TBI) and who were more than 1 month postinjury (compared to less than 1 month). Posts by close others had significantly higher positive sentiment than posts by people with TBI. Topic modeling identified three meta-themes: Recovery, Symptoms, and Medical Care. Qualitative content analysis further revealed that returning to productivity and life as well as sharing recovery tips were the primary focus under the Recovery theme. Symptom-related posts often discussed symptom management and validation of experiences. The Medical Care theme encompassed concerns regarding diagnosis, medication, and treatment.

Conclusions:
Concerns and needs shift over time following TBI, and they extend beyond health and functioning to participation in meaningful daily activities. The findings can inform the development of tailored educational resources and rehabilitative approaches, facilitating recovery and community building for individuals with TBI.

Supplemental Material:

https://doi.org/10.23641/asha.24881340
Personalized route recommendation for passengers in urban rail transit based on collaborative filtering algorithm
Authors: Li Wei , Li Zhiyuan , Luo Qin 
Published: December 2023

AbstractThe rapid advancements in information technology and intelligent systems within urban rail transit (URT) systems have highlighted the need for more personalized route recommendations that consider passengers’ travel habits. This study aims to address this issue by investigating passenger travel routes alongside other passengers who share similar travel preferences, utilizing collaborative filtering (CF) techniques. The approach involves analyzing historical card data to assess passenger travel profiles, including actual travel time under crowded conditions. By considering both individual passenger preferences and the preferences of similar passengers, a CF algorithm is employed to offer personalized route recommendations. The Shenzhen metro is used as a case study to illustrate the proposed method. The results demonstrate that the proposed approach surpasses traditional route recommendation methods by providing tailored suggestions that align more closely with passengers’ travel preferences. These findings emphasize the value of incorporating passenger travel preferences into route recommendation models, thereby enhancing the accuracy and effectiveness of personalized route recommendations within URT systems.
Speaker identification using Ultra‐Wideband measurement of voice
Authors: Li Haoxuan , Tang Chong , Vishwakarma Shelly , Ge Yao , Li Wenda 
Published: December 2023

AbstractVoice identification is being increasingly adopted in various domains, including security infrastructures, intelligent home systems, and personalised digital assistants. Notably, it harbours significant promise in transforming healthcare, especially in electronic health record detecting and speech impairment monitoring such as aphasia. Current strategies such as acoustic models based on deep learning, voice bio‐metrics, and spectrogram analysis, have been identified with several drawbacks including vulnerability to altered voices, susceptibility to ambient noise, and the necessity for significant computational power. In response to these issues, the authors introduce a ground‐breaking method of voice identification using Ultra‐Wideband (UWB) technology. This method capitalises on the micro‐Doppler shifts associated with movements of the laryngeal prominence. The distinctive nature of these bio‐metric traits related to speech production provides superior resistance against common pitfalls of voice identification. The proposed model leverages the high‐resolution characteristics of UWB to register tiny variations in laryngeal movements produced during speech, thus forming a distinct voice profile for each speaker. Through rigorous testing, the proposed system demonstrated significant progress in voice identification, achieving close to 90% accuracy in controlled experimental settings. This breakthrough indicates that UWB‐enabled voice identification could have a profound effect on medical applications, providing potential improvements in diagnosing, monitoring, possibly treating speech disorders, and thereby shaping a future of enhanced and secured healthcare services.
How Participatory Health Informatics Catalyzes One Digital Health
Authors: Denecke Kerstin , Romero Octavio Rivera , Merolli Mark , Miron-Shatz Talya , Gabarron Elia , Petersen Carolyn 
Published: December 2023

Objective: To identify links between Participatory Health Informatics (PHI) and the One Digital Health framework (ODH) and to show how PHI could be used as a catalyst or contributor to ODH.
Methods: We have analyzed the addressed topics within the ODH framework in previous IMIA Yearbook contributions from our working group during the last 10 years. We have matched main themes with the ODH's framework three perspectives (individual health and wellbeing, population and society, and ecosystem).
Results: PHI catalysts ODH individual health and wellbeing perspective by providing a more comprehensive view on human health, attitudes, and relations between human health and animal health. Integration of specific behavior change techniques or gamification strategies in digital solutions are effective to change behaviors which address the P5 paradigm. PHI supports the population and society perspective through the engagement of the various stakeholders in healthcare. At the same time, PHI might increase a risk for health inequities due to technologies inaccessible to all equally and challenges associated with this. PHI is a catalyst for the ecosystem perspective by contributing data into the digital health data ecosystem allowing for analysis of interrelations between the various data which in turn might provide links among all components of the healthcare ecosystem.
Conclusion: Our results suggest that PHI can and will involve topics relating to ODH. As the ODH concept crystalizes and becomes increasingly influential, its themes will permeate and become embedded in PHI even more. We look forward to these developments and co-evolution of the two frameworks.
Exploring the Evolution of Social Media in Mental Health Interventions: A Mapping Review
Authors: Gabarron Elia , Reichenpfader Daniel , Denecke Kerstin 
Published: December 2023

Background: With the rise of social media, social media use for delivering mental health interventions has become increasingly popular. However, there is no comprehensive overview available on how this field developed over time.
Objectives: The objective of this paper is to provide an overview over time of the use of social media for delivering mental health interventions. Specifically, we examine which mental health conditions and target groups have been targeted, and which social media channels or tools have been used since this topic first appeared in research.
Methods: To provide an overview of the use of social media for mental health interventions, we conducted a search for studies in four databases (PubMed; ACM Digital Library; PsycInfo; and CINAHL) and two trial registries (Clinicaltrials.gov; and Cochranelibrary.com). A sample of representative keywords related to mental health and social media was used for that search. Automatic text analysis methods (e.g., BERTopic analysis, word clouds) were applied to identify topics, and to extract target groups and types of social media.
Results: A total of 458 studies were included in this review (n=228 articles, and n=230 registries). Anxiety and depression were the most frequently mentioned conditions in titles of both articles and registries. BERTopic analysis identified depression and anxiety as the main topics, as well as several addictions (including gambling, alcohol, and smoking). Mental health and women's research were highlighted as the main targeted topics of these studies. The most frequently targeted groups were “adults” (39.5%) and “parents” (33.4%). Facebook, WhatsApp, messenger platforms in general, Instagram, and forums were the most frequently mentioned tools in these interventions.
Conclusions: We learned that research interest in social media-based interventions in mental health is increasing, particularly in the last two years. A variety of tools have been studied, and trends towards forums and Facebook show that tools allowing for more content are preferred for mental health interventions. Future research should assess which social media tools are best suited in terms of clinical outcomes. Additionally, we conclude that natural language processing tools can help in studying trends in research on a particular topic.
Advancing Biomedicine with Graph Representation Learning: Recent Progress, Challenges, and Future Directions
Authors: Li Fang , Nian Yi , Sun Zenan , Tao Cui 
Published: December 2023

Objectives: Graph representation learning (GRL) has emerged as a pivotal field that has contributed significantly to breakthroughs in various fields, including biomedicine. The objective of this survey is to review the latest advancements in GRL methods and their applications in the biomedical field. We also highlight key challenges currently faced by GRL and outline potential directions for future research.
Methods: We conducted a comprehensive search of multiple databases, including PubMed, Web of Science, IEEE Xplore, and Google Scholar, to collect relevant publications from the past two years (2021-2022). The studies selected for review were based on their relevance to the topic and the publication quality.
Results: A total of 78 articles were included in our analysis. We identified three main categories of GRL methods and summarized their methodological foundations and notable models. In terms of GRL applications, we focused on two main topics: drug and disease. We analyzed the study frameworks and achievements of the prominent research. Based on the current state-of-the-art, we discussed the challenges and future directions.
Conclusions: GRL methods applied in the biomedical field demonstrated several key characteristics, including the utilization of attention mechanisms to prioritize relevant features, a growing emphasis on model interpretability, and the combination of various techniques to improve model performance. There are also challenges needed to be addressed, including mitigating model bias, accommodating the heterogeneity of large-scale knowledge graphs, and improving the availability of high-quality graph data. To fully leverage the potential of GRL, future efforts should prioritize these areas of research.
Representation of Environmental Concepts Associated with Health Impacts in Computer Standardized Clinical Terminologies
Authors: Block Lorraine J. , Lozada-Perezmitre Erika , Cho Hwayoung , Davies Shauna , Lee Jisan , Lokmic-Tomkins Zerina , Peltonen Laura-Maria , Pruinelli Lisiane , Reid Lisa , Song Jiyoun , Topaz Maxim , von Gerich Hanna , Vyas Pankaj 
Published: December 2023

Objective: To evaluate the representation of environmental concepts associated with health impacts in standardized clinical terminologies.
Methods: This study used a descriptive approach with methods informed by a procedural framework for standardized clinical terminology mapping. The United Nations Global Indicator Framework for the Sustainable Development Goals and Targets was used as the source document for concept extraction. The target terminologies were the Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT) and the International Classification for Nursing Practice (ICNP). Manual and automated mapping methods were utilized. The lists of candidate matches were reviewed and iterated until a final mapping match list was achieved.
Results: A total of 119 concepts with 133 mapping matches were added to the final SNOMED CT list. Fifty-three (39.8%) were direct matches, 37 (27.8%) were narrower than matches, 35 (26.3%) were broader than matches, and 8 (6%) had no matches. A total of 26 concepts with 27 matches were added to the final ICNP list. Eight (29.6%) were direct matches, 4 (14.8%) were narrower than, 7 (25.9%) were broader than, and 8 (29.6%) were no matches.
Conclusion: Following this evaluation, both strengths and gaps were identified. Gaps in terminology representation included concepts related to cost expenditures, affordability, community engagement, water, air and sanitation. The inclusion of these concepts is necessary to advance the clinical reporting of these environmental and sustainability indicators. As environmental concepts encoded in standardized terminologies expand, additional insights into data and health conditions, research, education, and policy-level decision-making will be identified.
Year 2022 in Medical Natural Language Processing: Availability of Language Models as a Step in the Democratization of NLP in the Biomedical Area
Authors: Grouin Cyril , Grabar Natalia ,   Section Editors for the IMIA Yearbook Section on Natural Language Processing
Published: December 2023

Objectives: To analyse the content of publications within the medical Natural Language Processing (NLP) domain in 2022.
Methods: Automatic and manual preselection of publications to be reviewed, and selection of the best NLP papers of the year. Analysis of the important issues.
Results: Three best papers have been selected. We also propose an analysis of the content of the NLP publications in 2022, stressing on some of the topics.
Conclusion: The main trend in 2022 is certainly related to the availability of large language models, especially those based on Transformers, and to their use by non-NLP researchers. This leads to the democratization of the NLP methods. We also observe the renewal of interest to languages other than English, the continuation of research on information extraction and prediction, the massive use of data from social media, and the consideration of needs and interests of patients.
Findings from the 2023 Yearbook Section on Health Information Exchange
Authors: Bloomrosen Meryl , Berner Eta S. ,   Section Editors for the IMIA Yearbook Section on Health Information Exchange
Published: December 2023

Objectives: To summarize the recent literature and research and present a selection of the best papers published in 2022 related to Health Information Exchange (HIE).
Methods: A systematic review of the literature was performed by the two section editors with the help of a medical librarian. We searched bibliographic databases for HIE-related papers using both MeSH headings and keywords in titles and abstracts. A shortlist of ten candidate best papers was first selected by section editors before being peer-reviewed by Yearbook editors and independent external reviewers.
Results: Major themes of the set of ten articles included factors influencing the organizational adoption of HIE and clinicians' use of the information, use of HIE in non-traditional settings, patients' perspectives on HIE, and outcomes of using HIE.
Conclusions: These studies provide suggestions for the research questions, theories, settings, methods, and outcomes that can be fruitfully used for further research on HIE.
Actualización en el tratamiento de las lesiones condrales trocleares a propósito de un caso clínico
Authors: Poblete David Figueroa , Bello Juan Pablo Riquelme , Berrios María Loreto Figueroa , Rodriguez Rafael Calvo 
Published: December 2023

ResumenLas lesiones osteocondrales de la tróclea femoral son lesiones de difícil y controvertido tratamiento. Dentro de las opciones de manejo, la técnica de microfracturas es una de las más utilizadas, con buenos resultados reportados a corto plazo, no obstante un deterioro evidente al largo plazo. Debido a esto, se han desarrollado distintas técnicas de aumentación que favorecerían una mejor calidad del fibrocartílago formado, para así mejorar los resultados a mediano y largo plazo.En este reporte se presenta un caso de un paciente de 44 años con una lesión osteocondral en la tróclea femoral manejada con técnica combinada de microfracturas y aumentación con matriz de aloinjerto de cartílago, con buenos resultados clínicos e imagenológicos a 18 meses de seguimiento, y posteriormente se realiza una revisión actualizada de la literatura respecto al tópico.
Estrategias de alineamiento en prótesis total de rodilla: La era robótica cambió el juego
Authors: Monge Sebastián , Figueroa David , Isla Jorge 
Published: December 2023

ResumenLa prótesis total de rodilla es una cirugía ampliamente utilizada en el tratamiento de la gonartrosis moderada y severa, con resultados en general favorables, pero con una controversial tasa de insatisfacción entre los pacientes. Se han estudiado las posibles múltiples causas de esta insatisfacción, tomando mucha fuerza en el último tiempo el debate en torno al tipo de alineamiento utilizado en cirugía protésica de rodilla, sobre todo, considerando el advenimiento y las ventajas que trajo consigo la cirugía robótica. El alineamiento mecánico, se ha considerado a lo largo de los años como el estándar de oro en prótesis de rodilla, pero durante el siglo XXI se han creado nuevas filosofías, muchas de ellas gracias a los avances en cirugía robótica. En el presente trabajo dividiremos los alineamientos en 3 grandes grupos, se comentarán las características generales de cada uno, así como también el enfoque actual utilizado en nuestra institución, donde creemos que la cirugía robótica llegó para cambiar el juego.
Real-time observation of polarization dependence of soft x-ray absorption spectrum during chemical reaction under near-ambient pressure conditions
Authors: Amemiya K. , Sakata K. 
Published: December 2023

The real-time observation of the polarization dependence of soft x-ray absorption spectra during chemical reactions is realized by combining the fluorescence-yield wavelength-dispersive x-ray absorption spectroscopy technique with a 10 Hz switching between horizontal and vertical polarizations. The soft x-ray absorption spectra for both the horizontal and vertical polarizations are recorded every 100 ms with a time difference of 50 ms, which enables the real-time observation of changes in the anisotropic structure around the surface. The technique is applied to the oxidation reaction of a cobalt thin film under an air pressure of up to 25 Pa, and it is suggested that an anisotropic structure appears during the growth of the cobalt oxide species. By using the developed technique, it is expected that the changes in the anisotropic structures, such as molecular orientations, are observed during chemical reactions under near-ambient pressure conditions, which gives a deeper insight into the understanding of the reaction mechanism.
Formation and dissociation of carbon dioxide hydrate in presence of (NH4)2SO4: experimental characterization of the inhibition produced on the process.
Authors: Gambelli Alberto Maria , Domenighini Piergiovanni , Gigliotti Giovanni , Rossi Federico 
Published: December 2023

Abstract
Gas hydrates are mainly known as potentially alternative energy source and the research is mainly focused in making this source accessible, competitive and carbon neutral, by accompanying the recovery of methane with the permanent disposal of carbon dioxide. However, hydrates formation and dissociation can be advantageously applied in several key processes, such as gas mixture separation, gas storage and transportation, cold energy storage, desalination and waste water treatment. This study deals with these wo latter processes. Carbon dioxide hydrates were formed and dissociated in a pure water mixed with (NH4)2SO4. Two different scopes were pursued: the thermodynamic characterization of the inhibiting action due to the presence of electrolytes diffused in the aqueous phase and the possibility of considering hydrates formation as a potential strategy for NH4
+ removal from water, since the formation of clathrate structures rarely involves ions and other particles diffused in water. A lab – scale apparatus was used for the production of hydrates.
Numerical modelling and process simulation of a post-combustion CO2 capture pilot plant based on a membrane contactor unit
Authors: Cremona Riccardo , Conversano Antonio , Gatti Manuele 
Published: December 2023

Abstract
Hollow fiber membrane contactors (HFMC) have gained prominence in post-combustion CO2 capture applications due to their potential for high mass transfer rates, compactness, modularity and versatility. In this work, two pilot plant design have been proposed, an innovative solution which foresees the membrane contactor as CO2 absorption reactor, and a conventional one based on a packed column absorber. A one-dimensional model based on the resistance-in-series method has been developed for the membrane module and validated against experimental data from literature. The other process units have been simulated in Aspen Plus V11. According to the model results the membrane contactor unit is able to guarantee same levels of CO2 removal rates with improved energy performances compared to the conventional packed column absorber. In particular, if the same reactor volume is considered for the two absorber configurations, a reduction in the specific reboiler duty (SRD) of 8.5% is estimated. On the other hand, if the same liquid-to-gas (L/G) ratio is applied, the HFMC is able to guarantee a required reactor volume almost halved (45% reduction). These substantial improvements of the CO2 capture process could lead to lower investment cost and better economic indicators of the CO2 capture plant.