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Performance of Natural Language Processing versus International Classification of Diseases Codes in Building Registries for Patients With Fall Injury: Retrospective Analysis.

BACKGROUND: Standardized registries, such as the International Classification of Diseases (ICD) codes, are commonly built using administrative codes assigned to patient encounters. However, patients with fall injury are often coded using subsequent injury codes, such as hip fractures. This necessitates manual screening to ensure the accuracy of data registries. OBJECTIVE: This study aimed to automate the extraction of fall incidents and mechanisms using natural language processing (NLP) and compare this approach with the ICD method. METHODS: Clinical notes for patients with fall-induced hip …

Экзамен на получение языковых навыков высокого уровня 2 Фаза множественного склероза (восстановление-излучение и вторичный прогресс) в сравнении с здоровыми контрчастями.

Языковые навыки скомпрометированы после неврологических повреждений, таких, как множественный склероз (MS), что существенно влияет на качество жизни пациентов. СС препятствует функционированию языка высокого уровня. Несмотря на существующие исследования, ни в одном из исследований не рассматривались высокоуровневые языковые функции на различных этапах заболевания. Это имеет решающее значение для лучшего понимания лингвистических характеристик затронутых пациентов. МЕТОДЫ: Это описательно-аналитическое исследование включало 25 пациенты с RRMS, 27 пациентов с СМПС, и 30 здоровые люди (возрастные

Совпадение в аннотации оригинала
BACKGROUND: Language skills compromised after neurological damage, such as multiple sclerosis (MS), significantly impacting patients' quality of life. MS impairs high-level language functioning. Despite existing research, no studies have examined high-level language functions during different phases of the disease. This is crucial for a better understanding …

Recommendations for initial diabetic retinopathy screening of diabetic patients using large language model-based artificial intelligence in real-life case scenarios.

PURPOSE: To study the role of artificial intelligence (AI) to identify key risk factors for diabetic retinopathy (DR) screening and develop recommendations based on clinician and large language model (LLM) based AI platform opinions for newly detected diabetes mellitus (DM) cases. METHODS: Five clinicians and three AI applications were given 20 AI-generated hypothetical case scenarios to assess DR screening timing. We calculated inter-rater agreements between clinicians, AI-platforms, and the "majority clinician response" (defined as the maximum number of identical responses provided by the c…

Speech and lexico-semantic errors during direct cortical stimulation mapping of the language-dominant hemisphere: effects of object and action naming.

OBJECTIVE: In this retrospective study, the authors aimed to establish the stereotactically defined probability distribution for speech (i.e., anarthria, speech arrest) and lexico-semantic errors (i.e., anomia) through direct cortical stimulation (DCS) by using two tasks: action naming and object naming. They also analyzed the patterns of interindividual variability in the localization of the language sites involved, and investigated whether any patient or lesion location factors were associated with greater variability. METHODS: Eighty-one Italian-speaking patients who underwent awake surger…

Changes in symptom burden and quality of life among women with uterine fibroids receiving relugolix combination therapy: a plain language summary.

WHAT IS THIS SUMMARY ABOUT?: This is a summary of findings from two research studies (known as clinical trials). The studies looked at how well a medicine called relugolix combination therapy worked in women with heavy menstrual bleeding (heavy bleeding during a period) with uterine fibroids (noncancerous or benign growths in the uterus). In this analysis of the studies, researchers looked at how patients self-reported their uterine fibroid symptoms before and after taking relugolix combination therapy. Researchers also looked at how patients self-reported the impact of uterine fibroids on the

Bridging the conversational gap in epilepsy: Using large language models to reveal insights into patient behavior and concerns from online discussions.

OBJECTIVE: This study was undertaken to explore the experiences and concerns of people living with epilepsy by analyzing discussions in an online epilepsy community, using large language models (LLMs) to identify themes, demographic patterns, and associations with emotional distress, substance use, and suicidal ideation. METHODS: We analyzed 56 970 posts and responses to them from 21 906 users on the epilepsy forum (subreddit) of Reddit and 768 504 posts from the same users in other subreddits, between 2010 and 2023. LLMs, validated against human labeling, were used to identify 23 recurring t…

Investigating morphosyntactic and semantic measures in bilingual Azeri-Persian speaking children aged 5.5 to 6.5 years with and without language impairment.

The present study aims to investigate morphosyntactic and semantic measures in bilingual Azeri-Persian-speaking children aged 5.5-6.5 years with and without language impairment. In this cross-sectional study, the bilingual participants were thirty children with language impairment (LI) and fifteen typically developing children (TD) who were selected from nurseries and Speech therapy clinics. The language samples were collected through story-telling in Azeri and Persian languages, separately. The linguistic analysis was done based on morphosyntactic and semantic parameters. The Alberta Language…

Predicting which patients with cancer will see a psychiatrist or counsellor from their initial oncology consultation document using natural language processing.

BackgroundPatients with cancer often have unmet psychosocial needs. Early detection of who requires referral to a counsellor or psychiatrist may improve their care. This work used natural language processing to predict which patients will see a counsellor or psychiatrist from a patient's initial oncology consultation document. We believe this is the first use of artificial intelligence to predict psychiatric outcomes from non-psychiatric medical documents.MethodsThis retrospective prognostic study used data from 47,625 patients at BC Cancer. We analyzed initial oncology consultation documents …

Novel approach for Arabic fake news classification using embedding from large language features with CNN-LSTM ensemble model and explainable AI.

The widespread fake news challenges the management of low-quality information, making effective detection strategies necessary. This study addresses this critical issue by advancing fake news detection in Arabic and overcoming limitations in existing approaches. Deep learning models, Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM), EfficientNetB4, Inception, Xception, ResNet, ConvLSTM and a novel voting ensemble framework combining CNN and LSTM are employed for text classification. The proposed framework integrates the ELMO word embedding technique having contextual repre

Grammatical correction and morphological productivity tasks as potential identifiers of developmental language disorder in Spanish-Catalan bilingual children: a pilot study.

A critical problem for Catalan-Spanish bilinguals is the lack of assessment tools to conduct valid and accurate oral language evaluations. The purpose of this preliminary study was to provide pilot data for a new potential assessment tool in Catalan. We examined the possibility that two novel tasks, a grammatical correction (GramCorr) and morphological productivity (MP; nonword and word subtasks), could differentiate between Catalan-speaking children with and without developmental language disorder (DLD) with good diagnostic accuracy. Twenty-seven school-aged children with DLD (Mage = 9;1 year…

DeepAIP: Deep learning for anti-inflammatory peptide prediction using pre-trained protein language model features based on contextual self-attention network.

Non-steroidal anti-inflammatory drugs (NSAIDs), glucocorticoids, and other immunosuppressants are commonly used medications for treating inflammation. However, these drugs often come with numerous side effects. Therefore, finding more effective methods for inflammation treatment has become more necessary. The study of anti-inflammatory peptides can effectively address these issues. In this work, we propose a contextual self-attention deep learning model, coupled with features extracted from a pre-trained protein language model, to predict Anti-inflammatory Peptides (AIP). The contextual self-a…

Insights Into the Patient Experience of Hormone Therapy for Early Breast Cancer Treatment Using Patient Forum Discussions and Natural Language Processing.

PURPOSE: Understanding the real-world experience of patients with early breast cancer (eBC) is imperative for optimizing outcomes and evolving patient care. However, there is a lack of patient-level data, hindering clinical development. This social listening study was performed to understand patient insights into symptoms and impacts of hormone therapy (HT) for eBC using posts from patient forums on breastcancer.org to inform future clinical research. METHODS: Natural language processing (NLP) and machine learning techniques were used to identify themes related to eBC from a sample of 500,000…

Knowledge Mapping of Aspergillus-Related Research in Respiratory Medicine: A Bibliometric Analysis Based on English-Language Articles Spanning 1975 to 2022.

Background: Aspergillus has become the second most common causative agent of invasive fungal infections and is the leading cause of death from fungal infections. Methods: English-language publications ranging from 1975 to 2022 collected from the Web of Science Core Collection database were analyzed visually using VOSviewer, R package Bibliometrix, Scimago graphic, Gephi, Pajek, and Microsoft Excel 365. Literature search using the advanced search function in WoSCC with the search formula "TS=(Aspergillus)." The inclusion criteria were as follows: (1) article type = article; (2) time span = 1975…

Plain language summary of the CheckMate 816 study results: nivolumab plus chemotherapy given before surgery for non-small-cell lung cancer.

WHAT IS THIS SUMMARY ABOUT?: In this article, we summarize results from the ongoing phase 3 CheckMate 816 clinical study that were published in The New England Journal of Medicine in 2022. The goal of CheckMate 816 was to find out if nivolumab, an immunotherapy that activates a person's immune system (the body's natural defense system) to fight cancer, plus chemotherapy works better than chemotherapy alone when given before surgery in people with non-small-cell lung cancer (NSCLC) that can be removed surgically (resectable NSCLC). WHAT HAPPENED IN THE STUDY?: Adults who had not previously tak

Could you give me a leg up …? Models, frameworks and support structures to help aspiring clinical academic speech and language therapists.

BACKGROUND: Increasing research capacity and capability for the speech and language therapy (SLT) profession is a key national strategic driver, with many speech and language therapists (SLTs) aspiring to a clinical academic (CA) career. There are known benefits but also acknowledged challenges with this career path, including limited funding opportunities and a poorly established career trajectory. AIMS: To present models, frameworks and support structures that can be used by aspiring SLT CAs to chart research knowledge and skills, and plan career development. Organisational models are also …

A plain language summary exploring a new treatment combination for untreated locally advanced or metastatic urothelial cancer: enfortumab vedotin plus pembrolizumab.

WHAT IS THIS SUMMARY ABOUT?: This summary provides the results of a study of two treatments for cancer, enfortumab vedotin and pembrolizumab, that were studied together against locally advanced or metastatic urothelial cancer (la/mUC), a cancer that occurs most commonly in the bladder. WHAT WERE THE RESULTS?: In the 45 patients studied, around 16% did have serious side effects, but most side effects were manageable. Twenty-four percent of patients, however, stopped the study treatment because of their side effects. Within about 2 months of starting treatment, most patients' (73%) tumors were

More focal, less heterogeneous? Multi-level meta-analysis of cathodal high-definition transcranial direct current stimulation effects on language and cognition.

High-definition transcranial direct current stimulation (HD-tDCS) is a relatively focal, novel non-invasive brain stimulation method with the potential to investigate the causal contributions of specific cortical brain regions to language and cognition. Studies with HD-tDCS typically employ a 4 × 1 electrode design with a single central target electrode surrounded by four return electrodes, among which return current intensity is evenly distributed. With cathodal HD-tDCS, neural excitability in the target region is assumed to be reduced, which offers interesting perspectives for neuropsycholog…

Construct Validity of the Dutch, English, French, and Spanish LPFS-BF 2.0: Measurement Invariance Across Language and Gender and Criterion Validity.

With the introduction of the Alternative Model of Personality Disorders in the DSM-5, the need for short measures of the level of personality functioning has emerged, both for screening purposes and for assessing change during treatment. The Level of Personality Functioning Scale-Brief Form 2.0 (LPFS-BF 2.0) was constructed for this and has received support for its two-factor structure and criterion validity. The authors aimed to provide additional construct validity evidence for the LPFS-BF 2.0 by examining its factor structure and measurement invariance across the Dutch, English, French, and

Correlation Between Plasma Oligomeric Amyloid-β and Performance on the Language Neutral Visual Cognitive Assessment Test in a Southeast Asian Population.

Oligomeric amyloid-β (OAβ), an upstream driver of Alzheimer's disease (AD) neuropathology, correlates with poor cognitive performance and brain volume reduction. Its effect on cognitive performance measured by the language neutral Visual Cognitive Assessment Test (VCAT) remains to be evaluated. We studied the correlation of plasma OAβ with VCAT scores and grey matter volume (GMV) in a Southeast Asian cohort with mild cognitive impairment. Higher plasma OAβ significantly correlated with lower; cognitive scores (VCAT, Mini-Mental State Examination) and GMV/intracranial volume ratio. Such finding…

Plain language summary: Does a person's age affect how common fungal infections are and how well drugs can kill the infections?

WHAT IS THIS SUMMARY ABOUT?: Fungi are types of microbes that include molds and yeasts. Fungal infections can make people ill and can even cause death, especially in older people. They can be treated using antifungal drugs, but some fungi are drug resistant. This means the drug cannot kill the fungi. This is a summary based on a study that looked at fungal samples to find out more about antifungal drug resistance in adults younger than 65 compared with adults aged 65 and older. WHAT WERE THE RESULTS?: The study found that one type of drug-resistant fungus, called Candida parapsilosis, was mor