Результаты поиска

Proposal of Brain Plasticity Index Based on Navigated Transcranial Magnetic Stimulation: Metric of Functional Displacement for Language Function.

OBJECTIVE: To identify a brain plasticity index (BPI) that accounts for the cortical variation in language function on the basis of preoperative/postoperative navigated transcranial magnetic stimulation (nTMS) mapping. METHODS: This was a prospective, monocentric study of preoperative/postoperative nTMS mapping. A Python-based open-source pipeline was created to objectively quantify BPI maps, calculated with 2-dimensional nearest-neighbor interpolation of nTMS points for the 2 hemispheres (right/left). BPI maps registered on the Montreal Neurological Institute neuro-anatomy-atlas. Tumoral seg…

Relationship between language features extracted through NLP and clinically diagnosed Alzheimer's disease and mild cognitive impairment in Slovak.

BACKGROUND: Dementia, particularly Alzheimer's disease (AD), affects language, especially lexical-semantic processing. Discourse analysis using NLP methods can aid early detection, but research in inflectional languages like Slovak is limited. METHODS: Speech samples from 216 Slovak-speaking participants (64 AD, 44 MCI, 108 HC) were collected using a picture description task and analyzed for lexical complexity using 15 NLP-based measures. RESULTS: Several lexical complexity measures, including GTTR, UBER, SICHEL, MTLD, HDD and others, significantly differentiated AD or MCI from healthy contr…

Using natural language processing to extract carotid stenosis severity from clinical notes to create a nationwide veteran cohort.

OBJECTIVE: The prevalence of moderate to severe asymptomatic carotid stenosis (ie, atherosclerotic narrowing of the extracranial carotid arteries) is generally approximately 6% and 2%, respectively. Most prior studies of carotid stenosis risk factors have been small. This study describes the development and validation of a natural language processing (NLP) tool to identify carotid stenosis and uses it to identify significant risk factors, presence, and severity of carotid stenosis. METHODS: We created an NLP tool to extract the ratio of peak systolic velocity of the internal carotid artery to…

Transforming cataract care through artificial intelligence: an evaluation of large language models' performance in addressing cataract-related queries.

PURPOSE: To evaluate the performance of five popular large language models (LLMs) in addressing cataract-related queries. METHODS: This comparative evaluation study was conducted at the Eye and ENT Hospital of Fudan University. We performed both qualitative and quantitative assessments of responses from five LLMs: ChatGPT-4, ChatGPT-4o, Gemini, Copilot, and the open-source Llama 3.5. Model outputs were benchmarked against human-generated responses using seven key metrics: accuracy, completeness, conciseness, harmlessness, readability, stability, and self-correction capability. Additional inte…

Topological data mapping of online hate speech, misinformation, and general mental health: A large language model based study.

The advent of social media has led to an increased concern over its potential to propagate hate speech and misinformation, which, in additio … ive amount of social media posts to uncover the underlying hidden links. Machine learning and large language models such as ChatGPT make such an analysis possible. In this study, we collected thousands of posts from carefully selected communities on the social media site Reddit. We then utilized OpenAI's GPT3 to derive embeddings of these posts, which are …

Large language model responses to patient-oriented neurointerventional queries: A multirater assessment of accuracy, completeness, safety, and actionability.

BackgroundAs large language models (LLMs) become increasingly accessible to the public, patients are turning to these tools for medical guidance - including in highly specialized fields like interventional neuroradiology. Despite their growing use, the safety, completeness, and reliability of LLM-generated information in subspecialty medicine remain unclear.MethodsFive publicly available LLMs - ChatGPT, Gemini, Claude, Perplexity, and DeepSeek - were prompted with four neurointerventional patient-facing clinical questions spanning ischemic stroke, hemorrhagic stroke, venous disorders, and proc…

Evaluating the clinical utility of multimodal large language models for detecting age-related macular degeneration from retinal imaging.

This single-center retrospective study evaluated the performance of four multimodal large language models (MLLMs) (ChatGPT-4o, Claude 3.5 Sonnet, Google Gemini 1.5 Pro, Perplexity Sonar Large) in detecting and grading the severity of age-related macular degeneration (AMD) from ultrawide field fundus images. Images from 76 patients (136 eyes; mean age 81.1 years; 69.7% female) seen at the University of California San Diego were graded independently for AMD severity by two junior retinal specialists (and an adjudicating senior retina specialist for disagreements) using the Age-Related Eye Diseas…

Health Information Scanning and Seeking in Diverse Language, Cultural and Technological Media Among Latinx Adolescents: Cross-Sectional Study.

BACKGROUND: Continuous scientific and policy debate regarding the potential harm and/or benefit of media and social media on adolescent health has resulted, in part, from a deficiency in robust scientific evidence. Even with a lack of scientific consensus, public attitudes, and sweeping social media prohibitions have swiftly ensued. A focus on the diversity of adolescents around the world and their diverse use of language, culture, and social media is absent from these discussions. OBJECTIVE: This study aims to guide communication policy and practice, including those addressing access to soci…

Speech-Language Therapists' Training, Confidence, and Barriers When Serving Bilingual Children: Development and Application of a National Survey.

PURPOSE: Most pediatric speech-language therapists (SLTs) will serve bilingual children. This article reports findings from the National Survey of SLTs' Training, Confidence, and Barriers When Serving Bilingual Children. This survey was created for SLTs to self-report training, confidence, and barriers when assessing and delivering interventions to bilingual children. METHOD: The 58-question survey was developed using commonly accepted procedures for questionnaire development to establish content validity: (a) identification of the purpose of the survey, (b) creation of a blueprint of items, …

Plain language summaries supporting patient involvement: lessons and guidance from HTAi Patient and Citizen Involvement Interest Group (PCIG).

Patient involvement is an increasingly recognized cornerstone of effective Health Technology Assessment (HTA). Clear, accessible information empowers patient organizations to contribute meaningfully to HTA. Therefore, an international Summary Information for Patient Groups template was developed to provide plain language summaries of new medicines being assessed. Pilots using the template were conducted in Australia in 2021 and England in 2022, providing a trial within the HTA process. In Australia, the Consumer Evidence and Engagement Unit (CEEU) used a workshop and survey, together with key …

Plain language summary of quality of life in CheckMate 9ER: Cabozantinib plus nivolumab in advanced renal cell carcinoma.

Аннотация не предоставлена источником. Откройте карточку для перехода к публикации.

Совпадение в полном тексте источника
… This is an abstract of the Plain Language Summary of Publication article . To read the full Plain Language Summary of this article, click here to view the PDF . … Writing disclosure Editorial and medical writing support of this plain language summary were provided by Holly Clarke, PhD, and Charlotte Majerczyk, PhD, of Lumanity Communications Inc., and were funded by Janssen Global Services, LLC. …

An Experimental Evaluation of Smart Sensors for Pedestrian Attribute Recognition Using Multi-Task Learning and Vision Language Models.

This paper presents the experimental evaluation and analyzes the results of the first edition of the pedestrian attribute recognition (PAR) contest, the international competition which focused on smart visual sensors based on multi-task computer vision methods for the recognition of binary and multi-class pedestrian attributes from images. The participant teams designed intelligent sensors based on vision-language models, transformers and convolutional neural networks that address the multi-label recognition problem leveraging task interdependencies to enhance model efficiency and effectivenes…

Exploring speech-language pathologists' training and use of topical nasal anaesthesia during laryngeal endoscopy in the United States.

BACKGROUND: Speech-language pathologists (SLPs) perform nasal laryngoscopy (LE) to assess voice and dysphagia-related disorders. The procedural aspects may include the use of topical nasal anaesthesia. AIMS: To explore the practice patterns of American Speech-Language-Hearing Association (ASHA)-certified SLPs use of anaesthesia during laryngeal endoscopy procedures in the United States METHODS & PROCEDURES: Data were collected via a brief computerized survey. A mixed methodology was employed. National representation across the United States was achieved. OUTCOMES & RESULTS: Limited pre-licen…

Large language models versus classical machine learning performance in COVID-19 mortality prediction using high-dimensional tabular data.

This study compared the performance of classical feature-based machine learning models (CMLs) and large language models (LLMs) in predicting COVID-19 mortality using high-dimensional tabular data from 9,134 patients across four hospitals. Seven CML models, including XGBoost and random forest (RF), were evaluated alongside eight LLMs, such as GPT-4 and Mistral-7b, which performed zero-shot classification on text-converted structured data. Additionally, Mistral-7b was fine-tuned using the QLoRA approach. XGBoost and RF demonstrated superior performance among CMLs, achieving F1 scores of 0.87 and…

A Large Language Model-based Framework to Retrieve Life Cycle Inventory and Environmental Impact Data from Scientific Literature.

Life cycle assessment (LCA) quantifies environmental impacts from raw material extraction to end-of-life (EoL) treatment, yet its accuracy depends on reliable life cycle inventory (LCI) data. However, obtaining such data is time-consuming and requires an extensive literature review or access to databases that are often behind paywalls that hinder transparent research. This study introduces a systematic framework leveraging a retrained large language model (LLM) to assist LCA practitioners in retrieving LCI data and insightful information about their environmental impact. The framework follows …

Elizabeth Usher memorial lecture 2024: Speech-language pathology practice in Aboriginal spaces: A journey of learning and unlearning.

In this paper I describe learnings gained from 15 years collaboration with Aboriginal colleagues in Australia, in endeavours to improve reha … . My journey has involved challenging and un-learning some widely accepted Western tenets of speech-language pathology practice in order to explore culturally acceptable practices. The notion of learning, while at the same time unlearning and relearning is discussed in this paper along with several crucial ingredients of working cross-culturally in an Abor …

The relationship between mindfulness and second language resilience among Chinese English majors: the mediating role of academic hope.

BACKGROUND: In light of the heightened expectations surrounding the development of foreign language professionals in the age of artificial intelligence and the pursuit of academic excellence in Asian culture, Chinese English majors are faced with tremendous academic pressure. Accordingly, as a positive individual trait, second language (L2) resilience has recently received considerable attention in foreign and second language learning research. PURPOSE: Based on the hope theory, the broaden-and-build theory, and resilience theory framework, the present study explores the influence of mindfuln…

Generative Language Intervention for Young Children With Down Syndrome Using Augmentative and Alternative Communication: A Randomized Controlled Trial.

PURPOSE: Children with Down syndrome often have poor speech intelligibility, which can mask expressive language competence; this, in turn, can lead to serious misconceptions about overall competence and intellectual abilities. Although aided augmentative and alternative communication (AAC) can be used to bridge these gaps, children with Down syndrome are not always provided with consistent access to focused AAC language intervention supports. The primary goal of this study was to evaluate the effect of implementing the AAC Generative Language Intervention (AAC-GLI) approach on the aided expres…

Speech-language pathologists' views on visual discourse elicitation materials for cognitive communication disorder after TBI: An exploratory study.

BACKGROUND: Spoken discourse is elicited as part of speech-language pathology (SLP) practice after traumatic brain injury (TBI). Research literature reports on a range of monologic tasks for eliciting discourse samples, including different visual stimuli. The preferences of SLPs for these materials has not previously been investigated. AIMS: To explore the practice and views of SLPs on available visual discourse elicitation stimuli, specifically the clinical utility and acceptability of these tasks, and alignment with materials reported in research studies. We also sought SLPs' perspectives o…

Phonemic Fluency and Rhyme Production in People with Aphasic Word Retrieval Disorders: Sub-Lexical Written Language Skills Matter.

BACKGROUND: In everyday communication, word retrieval is semantically driven. A similar processing mechanism can be assumed for category fluency tasks. In contrast, in phonemic fluency tasks or rhyme production, the retrieval process must be based on the word form. In phonemic fluency, executive and language functions have been discussed as influencing this specific retrieval mechanism. In addition, studies of adults with developmental dyslexia and non-literate individuals have shown that deficits in written language processing are associated with poorer performance in phonemic fluency; a rela…