Iniciativas de evaluación para la indización semántica de literatura médica en español: PLANTL, LILACS, IBECS Y BIOASQ

XVI Jornadas Nacionales de Información y Documentación en Ciencias de la Salud. Oviedo, 4-5 de abril de 2019El proyecto Faro de Sanidad del Plan de Impulso de las Tecnologías del Lenguaje (PlanTL) pretende fomentar el desarrollo de sistemas de procesamiento del lenguaje natural (PLN), minería de textos y traducción automática para español y lenguas cooficiales. Una actividad importante del PlanTL es la organización de campañas de evaluación de sistemas de PLN y minería de textos, un mecanismo que no sólo es clave para evaluar la calidad de los resultados obtenidos por sistemas y algoritmos predictivos, sino que representa un motor fundamental para fomentar el desarrollo de herramientas y recursos de tecnologías del lenguaje. Debido a la importancia de la literatura para la toma de decisiones en medicina y el volumen considerable de publicaciones en español, el Plan TL, en colaboración con el BSC, el CNIO, la BNCS y la iniciativa BioASQ ha lanzado una tarea competitiva relacionada con la indización automática de la literatura médica en español con términos DeCS. Su fin es generar recursos de etiquetado semántico que sirvan de ayuda a la indización manual. La tarea BioASQ (bioasq.org) de indización semántica biomédica en español se realizará usando resúmenes de artículos de revistas contenidas en las bases de datos LILACS (Literatura Lationamericana en Ciencias de la Salud) y IBECS1 (Índice Bibliográfico Español en Ciencias de la Salud) como conjunto básico etiquetado y, a partir de ellos, desarrollar los algoritmos de indización automática, facilitando así el desarrollo de modelos de inteligencia artificial. La evaluación de los sistemas se realiza con la plataforma de BioASQ, mediante un sistema de evaluación continua. En él, se solicita a los participantes que asignen automáticamente términos DeCS a los registros nuevos añadidos a las bases de datos a medida que se hacen públicos, y antes de que se haya completado la indización manual. El rendimiento de indización se calcula comparando indización automática y manual. Gracias a los resultados de ediciones previas de BioASQ para la indización de PubMed, se ha mejorado este proceso en dicho recurso. Esta tarea de indización biomédica en español servirá para generar recursos comparables para indizar LILACS e IBECS y otros conjuntos documentales.The health flagship project of the Plan for the Advancement of Language Technology (PlanTL) tries to promote the development of natural language processing systems (NLP), text mining and machine translation resources for Spanish and co-official languages. There is a growing demand for a better exploitation of datasets generated by clinicians, especially electronic health records, as well as the integration and management of this kind of data in personalized medicine platforms integrating also information extracted from the literature. In this context, the PlanTL collaborates in the organization of evaluation efforts of clinical NLP and text mining systems, a key mechanism to evaluate the quality of results obtained by such automated systems and a fundamental mechanism to promote the development of tools and resources related to language technologies. Given the importance of literature for medical decision-making and the growing volume of Spanish medical publications, the TL Plan, in collaboration with the BSC, CNIO, the Biblioteca Nacional de Ciencias de la Salud and the BioASQ team have launched a shared task on automatic indexing of abstracts in Spanish with DeCS terms. The aim of this tracks is to generate semantic annotation resources that can be used to assist manual indexing. The Spanish biomedical semantic indexing track of BioASQ (bioasq.org) will rely on abstracts of journals contained in the LILACS databases as a basic Gold Standard manually labeled benchmark set for the development of automatic indexing algorithms particularly those based on artificial intelligence language models. The evaluation of participating systems is done through the BioASQ platform, which requests results in a continuous evaluation process, i.e. automatically asking for DeCS term assignment for newly added documents to LILACS, as they are made public, and before the manual indexing results are publicly released. The indexing performance in BioASQ is calculated by comparing automatic indexing against manual annotations. Thanks to the results of previous editions of BioASQ for indexing PubMed, the MeSH indexing process of this resource was considerably improved. This novel effort on medical indexing in Spanish will serve to generate comparable resources to semantically index not only LILACS but also other health databases and repositories in Spanish.N

Overview of BioASQ 2021-MESINESP track. Evaluation of advance hierarchical classification techniques for scientific literature, patents and clinical trials

CLEF 2021 – Conference and Labs of the Evaluation Forum, September 21–24, 2021, Bucharest, Romania,There is a pressing need to exploit recent advances in natural language processing technologies, in particular language models and deep learning approaches, to enable improved retrieval, classification and ultimately access to information contained in multiple, heterogeneous types of documents. This is particularly true for the field of biomedicine and clinical research, where medical experts and scientists need to carry out complex search queries against a variety of document collections, including literature, patents, clinical trials or other kind of content like EHRs. Indexing documents with structured controlled vocabularies used for semantic search engines and query expansion purposes is a critical task for enabling sophisticated user queries and even cross-language retrieval. Due to the complexity of the medical domain and the use of very large hierarchical indexing terminologies, implementing efficient automatic systems to aid manual indexing is extremely difficult. This paper provides a summary of the MESINESP task results on medical semantic indexing in Spanish (BioASQ/ CLEF 2021 Challenge). MESINESP was carried out in direct collaboration with literature content databases and medical indexing experts using the DeCS vocabulary, a similar resource as MeSH terms. Seven participating teams used advanced technologies including extreme multilabel classification and deep language models to solve this challenge which can be viewed as a multi-label classification problem. MESINESP resources, we have released a Gold Standard collection of 243,000 documents with a total of 2179 manual annotations divided in train, development and test subsets covering literature, patents as well as clinical trial summaries, under a cross-genre training and data labeling scenario. Manual indexing of the evaluation subsets was carried out by three independent experts using a specially developed indexing interface called ASIT. Additionally, we have published a collection of large-scale automatic semantic annotations based on NER systems of these documents with mentions of drugs/medications (170,000), symptoms (137,000), diseases (840,000) and clinical procedures (415,000). In addition to a summary of the used technologies by the teams, this paperS

Analysis and Report 1991-1992 : Dublin Institute of Technology, Kevin Street

Analysis and report for the year 1991-1992. Academic activities and involvement with society

Physiotherapy and neuro rehabilitation on stroke evidence and needs

Scientific knowledge in the area of rehabilitation and physiotherapy for stroke is booming and leading to more sustainable models of practice. Several interventions show positive effects with strong scientific support. However, some issues remain to be clarified like what are the effects of PT on brain activity and what are the effects of hands on interventions. Also a general coherence of interventions and outcomes and outcomes measures need to improve. With the intent to clarify these questions and to give an overview of Physiotherapy evidence and needs on stroke rehabilitation, this thesis will present the state of the art on a literature review and the four studies developed on the context of this PhD: Physiotherapy Hands-on Interventions and Stroke - Systematic Review; Physiotherapy and Brain Activity on Stroke - Systematic Review; Brain activity during lower limb movement with physiotherapy manual facilitation – an fMRI study; ICF Linking Process for Categorization of Interventions and Outcomes Measures on Stroke Physiotherapy - Delphi panel. As innovative aspects of this thesis, we highlight: the organization within the ICF framework for the outcomes related with movement; the study of brain activity during a complex multijoint movement of lower limb; the study of immediate effects of manual facilitation of movement, as no similar studies was found on our literature search for this thesis. Regardless the limitations encountered, the non-conclusive findings and some non-identified evidence, it seems still valid to conclude that Physiotherapy is no longer a “black box”, instead is a evidence-based profession. Exists clear and evidence based information for clinical settings and scientific community, that hands off physiotherapy is relevant and has efficacy proved on the rehabilitation of stroke patients on the domains of Structure & Functions and Activities & Participation. This efficacy is extended to the brain activity, which validates the idea that PT can influence neuroplasticity process and consequently contribute for a better recovery in a neurobiological perspective with impact on human performance and autonomy.O conhecimento científico na area da intervenção em utentes com sequelas após Acidente Vascular Cerebral (AVC) e especificamente na área da Fisioterapia, tem crescido nos últimos ano, conduzindo a modelos de prática mais sustentados. São várias as intervneções da Fisioterapia com eficácia comprovada. Contudo, alguns aspectos ainda necessitam de clarificação, como seja quais os efeitos da Fisioterapia na actividade cerebral e quais são os efeitos das intervenções baseadas na manualidade do Fisioterapeuta. É ainda necessária, uma maior coerência entre as intervenções, as variáveis em estudo e os instrumentos de avaliação utilizados. Com o objectivo de contribuir para o esclarecimento destas questões e de oferecer uma visao global da evidência da intervenção da Fisioterapia e as necessidades de desenvolvimento na intervenção e utentes com AVC, esta tese apresenta um estado da arte na revisão de literature e os quarto estudos desenvolvidos no contexto deste doutoramento: Efeitos da Fisioterapia manual em utentes com AVC - revisão sistemática; Efeitos da Fisioterapia na actividade cerebral em utentes com AVC - revisão sistemática; Efeitos imediatos da facilitação manual na actividade cerebral - estudo com RMf; Processo de categorização de intervenções e intrumentos específicos da intervenção em utentes com AVC - Painel de Delphi. Como aspectos inovadores, salientamos a organização de acordo com a estrutura da CIF, para as variaveis relacionadas com o movimento; o estudo a actividade cerebral durante um movimento complexo e multi-articular do membro inferior; o estudo dos efeitos imediatos da facilitação manual na actividade cerebral. Independentemente das limitações encontradas, dos achados não conclusivos e alguns achados de não benefício de intervenções, parece-nos ser válido concluir que a Fisioterapia deixou de ser uma “caixa negra” sendo uma profissão científicamente suportada. Existe informação clara e suportada cientificamente, disponível para os locais de prática e para a comunidade científica, de que a Fisioterapia “hands off” é relevante e tem eficácia comprovada no contexto da intervenção em utentes com AVC, nos domínios da Estrutura e Função e da Actividade e Participação. Esta eficácia estende-se à actividade cerebral, validando a ideia de que a Fisioterapia pode influenciar a neuroplasticidade e consequentemente contribuir para uma recuperação neurobiológica mais adequada, com impacto no desempenho humano e autonomia

Exploring patient-neurosurgical team inter-relationships throughout the perioperative period of awake craniotomy

The portfolio thesis is divided into three parts: a systematic literature review, an empirical study, and appendices.Part one is a systematic literature review exploring definitions, measures and influencers of health-related quality of life (HRQofL) in brain tumour (BT) populations. The review was undertaken as no BT-specific HRQofL definition currently exists, literature remains unclear regarding the existence of reliable and valid BT-specific measures, and little is known about factors associated with HRQofL that may be amenable to change. A systematic search of four databases identified 13 relevant studies. No accepted HRQofL definition emerged. Only two validated BT-specific HRQofL measures were reported and numerous variables influencing HRQofL were identified within themes of ‘patient’, ‘tumour’, and ‘social support’ factors. Findings provided recommendations for future research and useful insights for refining clinical practice.Part two is an empirical study exploring how both patients and neurosurgical team members experience awake craniotomy (AC) and make sense of their perioperative interactions. The qualitative study aimed to enhance knowledge surrounding efficacious approaches to build positive patient-practitioner relationships with the potential to improve overall AC experience. A patient and neurosurgical team group, each comprising eight participants, were interviewed and the data was analysed using Interpretative Phenomenological Analysis (IPA). Four superordinate and six subordinate themes, and three superordinate and seven subordinate themes emerged within patient and neurosurgical team groups respectively. Themes are discussed within the context of wider healthcare literature, identifying relevant clinical implications.Part three consists of appendices supporting the systematic literature review and the empirical study. It also includes a reflective statement of the ‘research experience’

Decoding Legalese Without Borders: Multilingual Evaluation of Language Models on Long Legal Texts

Pretrained transformers have sparked an explosion of research in the field of Natural Language Processing (NLP). Scaling up language models based on the transformer architecture in terms of size, compute, and data led to impressive emergent capabilities that were considered unattainable in such a brief span, a mere three years ago, prior to the launch of GPT-3. These advances catapulted the previously niche field of legal NLP into the mainstream, at the latest, with GPT-4 passing the bar. Many products based on GPT-4 and other large language models are entering the market at an increasing pace, many of those targeting the legal field. This dissertation makes contributions in two key areas within Natural Language Processing (NLP) focused on legal text: resource curation and detailed model analysis. First, we curate an extensive set of multilingual legal datasets, train a variety of language models on these, and establish comprehensive benchmarks for evaluating Large Language Models (LLMs) in the legal domain. Second, we conduct a multidimensional analysis of model performance, focusing on metrics like explainability and calibration in the context of Legal Judgment Prediction. We introduce novel evaluation frameworks and find that while our trained models exhibit high performance and better calibration than human experts, they do not necessarily offer improved explainability. Furthermore, we investigate the feasibility of re-identification in anonymized legal texts, concluding that large-scale re-identification using LLMs is currently unfeasible. For future work, we propose exploring domain adaptation and instruction tuning to enhance language model performance on legal benchmarks, while also advocating for a detailed examination of dataset overlaps and model interpretability. Additionally, we emphasize the need for dataset extension to unexplored legal tasks and underrepresented jurisdictions, aiming for a more comprehensive coverage of the global legal landscape in NLP resources

Exploring Tai Chi as an Early Intervention to Improve Balance and Reduce Falls Among Stroke Survivors – A Randomized Feasibility Study

Stroke is a major cause of disability worldwide, with many stroke survivors being at high risk of falling. Falling leads to an increasing amount of hospital admissions, placing substantial economic burden on health services. It has previously been shown that exercise programmes improve balance and reduce falls in older people. Tai Chi has been shown to reduce falls in older people. Therefore, it may show similar benefits early in stroke rehabilitation. The aim of this randomised controlled feasibility study is to explore the acceptability and adherence of a bespoke Tai Chi programme for stroke survivors. Additionally, the suitability of the outcome measures has also been examined, along with the implementation, demand and practicalities of the programme. Twenty-three potential participants completed the study and were identified and recruited at the point of discharge at a local hospital on a stroke unit. Participants were randomised into two groups: Tai Chi with usual care (experimental) (n=14) or usual care (control) (n=9). The experimental group attended one-hour Tai Chi classes twice a week and participated in home practice for 12 weeks. Primary outcome measures were fall rates and the Berg Balance Scale [BBS] to measure falls risk and balance ability. Secondary outcome measures included the Geriatric Depression Scale [GDS] to measure depression levels, the Tinetti Falls Efficacy Scale [FES] to measure fear of falling, and the SF 12 to measure Quality of Life [QoL]. Semi-structured interviews were conducted with the experimental group to gain participants’ perspectives of the programme. This study found Tai Chi is feasible for stroke survivors as an adjunct to their rehabilitation. Further, Tai Chi may empower them to take control over their own recovery at home. Recommended outcome measures include the number of fallers with the BBS, GDS and FES as secondary outcome measures. Future larger RCTs may consider a 24-week intervention and more advanced professional home practice materials. Adopting a wait-list design and including hospital-based introductory classes are recommended to improve recruitment. Mid-intervention assessment and long-term follow-ups of six and twelve months or longer are also recommended in a future trial

From despair to hope studies in HIV and tuberculosis 1992-2011

Includes abstract. Includes bibliographical references