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Ensuring Adolescent Patient Portal Confidentiality in the Age of the Cures Act Final Rule.

J Adolesc Health 2021 Oct 16. Epub 2021 Oct 16.

Information Services, Stanford Children's Health, Stanford, California.

Purpose: Managing confidential adolescent health information in patient portals presents unique challenges. Adolescent patients and guardians electronically access medical records and communicate with providers via portals. In confidential matters like sexual health, ensuring confidentiality is crucial. Read More

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October 2021

Distributional social semantics: Inferring word meanings from communication patterns.

Authors:
Brendan T Johns

Cogn Psychol 2021 Oct 16;131:101441. Epub 2021 Oct 16.

Department of Psychology, McGill University, 2001 McGill College Avenue, Montreal, Quebec H3A 1G1, Canada. Electronic address:

Distributional models of lexical semantics have proven to be powerful accounts of how word meanings are acquired from the natural language environment (Günther, Rinaldi, & Marelli, 2019; Kumar, 2020). Standard models of this type acquire the meaning of words through the learning of word co-occurrence statistics across large corpora. However, these models ignore social and communicative aspects of language processing, which is considered central to usage-based and adaptive theories of language (Tomasello, 2003; Beckner et al. Read More

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October 2021

Modeling Sequential Annotations for Sequence Labeling With Crowds.

IEEE Trans Cybern 2021 Oct 19;PP. Epub 2021 Oct 19.

Crowd sequential annotations can be an efficient and cost-effective way to build large datasets for sequence labeling. Different from tagging independent instances, for crowd sequential annotations, the quality of label sequence relies on the expertise level of annotators in capturing internal dependencies for each token in the sequence. In this article, we propose modeling sequential annotation for sequence labeling with crowds (SA-SLC). Read More

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October 2021

Multi-Scale 2D Temporal Adjacency Networks for Moment Localization with Natural Language.

IEEE Trans Pattern Anal Mach Intell 2021 Oct 19;PP. Epub 2021 Oct 19.

We address the problem of retrieving a specific moment from an untrimmed video by natural language. It is a challenging problem because a target moment may take place in the context of other temporal moments in the untrimmed video. Existing methods cannot tackle this challenge well since they do not fully consider the temporal contexts between temporal moments. Read More

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October 2021

Two-field non-mydriatic fundus photography for diabetic retinopathy screening: a protocol for a systematic review and meta-analysis.

BMJ Open 2021 Oct 18;11(10):e051761. Epub 2021 Oct 18.

Imaging Department, Shenzhen Institute of Translational Medicine, The First Affiliated Hospital of Shenzhen University, Shenzhen Second People's Hospital, Shenzhen, China

Introduction: Diabetic retinopathy (DR) is one of the most prevalent microvascular complications of diabetes mellitus. Guidelines for DR screening in different countries vary greatly, including fundus photography, slit-lamp biomicroscopy, indirect ophthalmoscopy, Optical Coherence Tomography (OCT), OCT-A and Fundus Fluorescein Angiography (FFA). Two-field non-mydriatic fundus photography (NMFP) is an effective screening method due to its low cost and less time-consuming process. Read More

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October 2021

Serum RANKL levels in Chinese patients with ankylosing spondylitis: a meta-analysis.

J Orthop Surg Res 2021 Oct 18;16(1):615. Epub 2021 Oct 18.

Department of Orthopaedics, Shengjing Hospital of China Medical University, Sanhao Street No. 36, Heping District, Shenyang, Liaoning, 110004, People's Republic of China.

Objective: We aimed to determine the association between serum receptor activator of nuclear factor-kappa B ligand (sRANKL) levels and ankylosing spondylitis (AS) in Chinese patients.

Methods: The PubMed, Cochrane Library, Embase, Chinese Biomedical Database, Web of Science, China National Knowledge Infrastructure, VIP, and Wan Fang databases were searched for studies conducted before October 1, 2020, without language restrictions. STATA version 12. Read More

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October 2021

A representation and deep learning model for annotating ubiquitylation sentences stating E3 ligase - substrate interaction.

BMC Bioinformatics 2021 Oct 18;22(1):507. Epub 2021 Oct 18.

Warshel Institute for Computational Biology, The Chinese University of Hong Kong, Shenzhen, China.

Background: Ubiquitylation is an important post-translational modification of proteins that not only plays a central role in cellular coding, but is also closely associated with the development of a variety of diseases. The specific selection of substrate by ligase E3 is the key in ubiquitylation. As various high-throughput analytical techniques continue to be applied to the study of ubiquitylation, a large amount of ubiquitylation site data, and records of E3-substrate interactions continue to be generated. Read More

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October 2021

Natural language processing for cognitive therapy: Extracting schemas from thought records.

PLoS One 2021 18;16(10):e0257832. Epub 2021 Oct 18.

Department of Intelligent Systems, Delft University of Technology, Delft, Netherlands.

The cognitive approach to psychotherapy aims to change patients' maladaptive schemas, that is, overly negative views on themselves, the world, or the future. To obtain awareness of these views, they record their thought processes in situations that caused pathogenic emotional responses. The schemas underlying such thought records have, thus far, been largely manually identified. Read More

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October 2021

Mild Adverse Events of Sputnik V Vaccine in Russia: Social Media Content Analysis of Telegram via Deep Learning.

J Med Internet Res 2021 Sep 28. Epub 2021 Sep 28.

System Modeling Group, Institute for Veterinary Epidemiology and Biostatistics, Freie Universität Berlin, Königsweg 67, Berlin, DE.

Background: There is a limited amount of data on the COVID-19 vector vaccine Gam-COVID-Vac (Sputnik V) safety profile. Previous infodemiology studies showed that social media discourse could be analyzed to assess the most concerning adverse events (AE) caused by drugs.

Objective: We aimed to investigate mild AEs of Sputnik V based on a participatory trial conducted on Telegram in the Russian language. Read More

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September 2021

Identifying and classifying goals for scientific knowledge.

Bioinform Adv 2021 28;1(1):vbab012. Epub 2021 Jul 28.

Computational Bioscience Program, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA.

Motivation: Science progresses by posing good questions, yet work in biomedical text mining has not focused on them much. We propose a novel idea for biomedical natural language processing: identifying and characterizing the stated in the biomedical literature. Formally, the task is to identify and characterize , statements where scientific knowledge is missing or incomplete. Read More

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CD161, a promising Immune Checkpoint, correlates with Patient Prognosis: A Pan-cancer Analysis.

J Cancer 2021 9;12(21):6588-6599. Epub 2021 Sep 9.

Department of Neurosurgery, Xiangya Hospital, Central South University, 87 Xiangya Road, Changsha, Hunan, 410008, China.

CD161 is a promising immune checkpoint mainly expressed on natural killer (NK) cells and is essential for immunoregulatory functions. However, it remains obscure how CD161 correlates with immune infiltration and patient prognosis in pan-cancer. We employed HPA, TCGA, GTEx, TIMER2. Read More

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September 2021

Capturing the Trajectory of Psychological Status and Analyzing Online Public Reactions During the Coronavirus Disease 2019 Pandemic Through Weibo Posts in China.

Front Psychol 2021 29;12:744691. Epub 2021 Sep 29.

State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, China.

When a major, sudden infectious disease occurs, people tend to react emotionally and display reactions such as tension, anxiety, fear, depression, and somatization symptoms. Social media played a substantial awareness role in developing countries during the outbreak of coronavirus disease 2019 (COVID-19). This study aimed to analyze public opinion regarding COVID-19 and to explore the trajectory of psychological status and online public reactions to the COVID-19 pandemic by examining online content from Weibo in China. Read More

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September 2021

T4SEfinder: a bioinformatics tool for genome-scale prediction of bacterial type IV secreted effectors using pre-trained protein language model.

Brief Bioinform 2021 Oct 15. Epub 2021 Oct 15.

State Key Laboratory of Microbial Metabolism, Joint International Laboratory on Metabolic & Developmental Sciences, School of Life Sciences & Biotechnology, Shanghai Jiao Tong University, Shanghai 200030, China.

Bacterial type IV secretion systems (T4SSs) are versatile and membrane-spanning apparatuses, which mediate both genetic exchange and delivery of effector proteins to target eukaryotic cells. The secreted effectors (T4SEs) can affect gene expression and signal transduction of the host cells. As such, they often function as virulence factors and play an important role in bacterial pathogenesis. Read More

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October 2021

Identification of efflux proteins based on contextual representations with deep bidirectional transformer encoders.

Anal Biochem 2021 Oct 14;633:114416. Epub 2021 Oct 14.

Department of Computer Science & Engineering, Yuan Ze University, Chungli, 32003, Taiwan. Electronic address:

Efflux proteins are the transport proteins expressed in the plasma membrane, which are involved in the movement of unwanted toxic substances through specific efflux pumps. Several studies based on computational approaches have been proposed to predict transport proteins and thereby to understand the mechanism of the movement of ions across cell membranes. However, few methods were developed to identify efflux proteins. Read More

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October 2021

Using Deep-Learning Algorithms to Simultaneously Identify Right and Left Ventricular Dysfunction From the Electrocardiogram.

JACC Cardiovasc Imaging 2021 Oct 7. Epub 2021 Oct 7.

Mount Sinai Clinical Intelligence Center, Icahn School of Medicine at Mount Sinai, New York, New York, USA; The Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, New York, USA; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA. Electronic address:

Objectives: This study sought to develop DL models capable of comprehensively quantifying left and right ventricular dysfunction from ECG data in a large, diverse population.

Background: Rapid evaluation of left and right ventricular function using deep learning (DL) on electrocardiograms (ECGs) can assist diagnostic workflow. However, DL tools to estimate right- ventricular (RV) function do not exist, whereas those to estimate left ventricular (LV) function are restricted to quantification of very low LV function only. Read More

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October 2021

Deep semi-supervised learning ensemble framework for classifying co-mentions of human proteins and phenotypes.

BMC Bioinformatics 2021 Oct 16;22(1):500. Epub 2021 Oct 16.

School of Computing, University of North Florida, Jacksonville, USA.

Background: Identifying human protein-phenotype relationships has attracted researchers in bioinformatics and biomedical natural language processing due to its importance in uncovering rare and complex diseases. Since experimental validation of protein-phenotype associations is prohibitive, automated tools capable of accurately extracting these associations from the biomedical text are in high demand. However, while the manual annotation of protein-phenotype co-mentions required for training such models is highly resource-consuming, extracting millions of unlabeled co-mentions is straightforward. Read More

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October 2021

When judging what you know changes what you really know: Soliciting metamemory judgments reactively enhances children's learning.

Child Dev 2021 Oct 16. Epub 2021 Oct 16.

Institute of Developmental Psychology, Faculty of Psychology, Beijing Normal University, Beijing, China.

Recent studies established that making concurrent judgments of learning (JOLs) can significantly alter (typically enhance) memory itself-a reactivity effect. The current study recruited 190 Chinese children (M  = 8.68 years; 101 female) in 2020 and 2021 to explore the reactivity effect on children's learning, its developmental trajectory and associated metacognitive awareness. Read More

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October 2021

DUKweb, diachronic word representations from the UK Web Archive corpus.

Sci Data 2021 Oct 15;8(1):269. Epub 2021 Oct 15.

The Alan Turing Institute, London, United Kingdom.

Lexical semantic change (detecting shifts in the meaning and usage of words) is an important task for social and cultural studies as well as for Natural Language Processing applications. Diachronic word embeddings (time-sensitive vector representations of words that preserve their meaning) have become the standard resource for this task. However, given the significant computational resources needed for their generation, very few resources exist that make diachronic word embeddings available to the scientific community. Read More

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October 2021

Association of Social Support With Overall Survival and Healthcare Utilization in Patients With Aggressive Hematologic Malignancies.

J Natl Compr Canc Netw 2021 Oct 15:1-7. Epub 2021 Oct 15.

1Division of Hematology and Oncology, Department of Medicine, Massachusetts General Hospital.

Background: Social support plays a crucial role for patients with aggressive hematologic malignancies as they navigate their illness course. The aim of this study was to examine associations of social support with overall survival (OS) and healthcare utilization in this population.

Methods: A cross-sectional secondary analysis was conducted using data from a prospective longitudinal cohort study of 251 hospitalized patients with aggressive hematologic malignancies at Massachusetts General Hospital from 2014 through 2017. Read More

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October 2021

Automation of penicillin adverse drug reaction categorisation and risk stratification with machine learning natural language processing.

Int J Med Inform 2021 Oct 5;156:104611. Epub 2021 Oct 5.

Department of Clinical Pharmacology, Royal Adelaide Hospital, Adelaide, South Australia, Australia; Discipline of Clinical Pharmacology, School of Medicine, University of Adelaide, Adelaide, South Australia, Australia.

Background: The penicillin adverse drug reaction (ADR) label is common in electronic health records (EHRs). However, there is significant misclassification between allergy and intolerance within the EHR and most patients can be delabelled after an immunologic assessment. Machine learning natural language processing may be able to assist with the categorisation and risk stratification of penicillin ADRs. Read More

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October 2021

A language modeling-like approach to sketching.

Neural Netw 2021 Oct 2;144:627-638. Epub 2021 Oct 2.

Department of Information Engineering and Mathematics, University of Siena, Italy. Electronic address:

Sketching is a universal communication tool that, despite its simplicity, is able to efficiently express a large variety of concepts and, in some limited contexts, it can be even more immediate and effective than natural language. In this paper we explore the feasibility of using neural networks to approach sketching in the same way they are commonly used in Language Modeling. We propose a novel approach to what we refer to as "Sketch Modeling", in which a neural network is exploited to learn a probabilistic model that estimates the probability of sketches. Read More

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October 2021

Mapping Individual Differences on the Internet: Case Study of the Type 1 Diabetes Community.

JMIR Diabetes 2021 Oct 15;6(4):e30756. Epub 2021 Oct 15.

Department of Psychology, University of Oregon, Eugene, OR, United States.

Background: Social media platforms, such as Twitter, are increasingly popular among communities of people with chronic conditions, including those with type 1 diabetes (T1D). There is some evidence that social media confers emotional and health-related benefits to people with T1D, including emotional support and practical information regarding health maintenance. Research on social media has primarily relied on self-reports of web-based behavior and qualitative assessment of web-based content, which can be expensive and time-consuming. Read More

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October 2021

Design Implications for Explanations: A Case Study on Supporting Reflective Assessment of Potentially Misleading Videos.

Front Artif Intell 2021 27;4:712072. Epub 2021 Sep 27.

Web Information Systems Group, Department of Software Technology, Delft University of Technology, Delft, Netherlands.

Online videos have become a prevalent means for people to acquire information. Videos, however, are often polarized, misleading, or contain topics on which people have different, contradictory views. In this work, we introduce to stimulate more deliberate reasoning about videos and raise users' awareness of potentially deceiving or biased information. Read More

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September 2021

Coffee With a Hint of Data: Towards Using Data-Driven Approaches in Personalised Long-Term Interactions.

Front Robot AI 2021 28;8:676814. Epub 2021 Sep 28.

Centre for Robotics and Neural Systems, University of Plymouth, Plymouth, United Kingdom.

While earlier research in human-robot interaction pre-dominantly uses rule-based architectures for natural language interaction, these approaches are not flexible enough for long-term interactions in the real world due to the large variation in user utterances. In contrast, data-driven approaches map the user input to the agent output directly, hence, provide more flexibility with these variations without requiring any set of rules. However, data-driven approaches are generally applied to single dialogue exchanges with a user and do not build up a memory over long-term conversation with different users, whereas long-term interactions require remembering users and their preferences incrementally and continuously and recalling previous interactions with users to adapt and personalise the interactions, known as the problem. Read More

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September 2021

Sentiment Classification of News Text Data Using Intelligent Model.

Authors:
Shitao Zhang

Front Psychol 2021 28;12:758967. Epub 2021 Sep 28.

School of Network Communication, Zhejiang Yuexiu University, Shaoxing, China.

Text sentiment classification is a fundamental sub-area in natural language processing. The sentiment classification algorithm is highly domain-dependent. For example, the phrase "traffic jam" expresses negative sentiment in the sentence "I was stuck in a traffic jam on the elevated for 2 h. Read More

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September 2021

Digital hermeneutics: scaled readings of online depression discourses.

Med Humanit 2021 Oct 14. Epub 2021 Oct 14.

Department of Informatics, King's College London, London, London, UK

When it comes to understanding experiences of illness, humanities and social sciences research have traditionally reserved a prominent role for narrative. Yet, depression has characteristics that withstand the form of traditional narratives, such as a lack of desire and an impotence to act. How can a 'datafied' approach to online forms of depression writing pose a valuable addition to existing narrative approaches in health humanities? In this article, we analyse lay people's depression discourses online. Read More

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October 2021

Detection of Pneumothorax with Deep Learning Models: Learning From Radiologist Labels vs Natural Language Processing Model Generated Labels.

Acad Radiol 2021 Oct 12. Epub 2021 Oct 12.

Department of Diagnostic Imaging, National University Hospital, Singapore.

Rationale And Objectives: To compare the performance of pneumothorax deep learning detection models trained with radiologist versus natural language processing (NLP) labels on the NIH ChestX-ray14 dataset.

Materials And Methods: The ChestX-ray14 dataset consisted of 112,120 frontal chest radiographs with 5302 positive and 106, 818 negative labels for pneumothorax using NLP (dataset A). All 112,120 radiographs were also inspected by 4 radiologists leaving a visually confirmed set of 5,138 positive and 104,751 negative for pneumothorax (dataset B). Read More

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October 2021

A Comparison Between the Korean Digits-in-Noise Test and the Korean Speech Perception-in-Noise Test in Normal-Hearing and Hearing-Impaired Listeners.

J Audiol Otol 2021 Oct 10;25(4):171-177. Epub 2021 Oct 10.

Department of Speech, Language, and Hearing Sciences, University of Florida, Gainesville, FL, USA.

Background And Objectives: The purpose of the present study was to validate the performance and diagnostic efficacy of the Korean digits-in-noise (K-DIN) test in comparison to the Korean speech perception-in-noise (K-SPIN) test, which is the representative speech-in-noise test in clinical practice.

Subjects And Purpose: Twenty-seven subjects (15 normal-hearing and 12 hearing-impaired listeners) participated. The recorded Korean 0-9 digits were used to form quasirandom digit triplets; 50 target digit triplets were presented at the most comfortable level of each subject while presenting speech-shaped background noise at various levels of signal-to-noise ratios (-12. Read More

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October 2021

Timing of venous thromboembolism diagnosis in hospitalized and non-hospitalized patients with COVID-19.

Thromb Res 2021 Oct 7;207:150-157. Epub 2021 Oct 7.

Department of Cardiovascular Diseases, Division of Vascular Medicine, Rochester, MN, United States of America; Department of Internal Medicine, Division of Hematology/Oncology, Mayo Clinic, MN, United States of America. Electronic address:

Background: The reported incidence of venous thromboembolism (VTE) in COVID-19 patients varies widely depending on patient populations sampled and has been predominately studied in hospitalized patients. The goal of this study was to assess the evolving burden of COVID-19 and the timing of associated VTE events in a systems-wide cohort.

Methods: COVID-19 PCR positive hospitalized and non-hospitalized patients ≥18 years of age tested between 1/1/2020 through 12/31/2020 were retrospectively analyzed using electronic medical records from multiple states across the Mayo Clinic enterprise. Read More

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October 2021

An ontology-based review of transgender literature: Revealing a history of medicalization and pathologization.

Int J Med Inform 2021 Sep 29;156:104601. Epub 2021 Sep 29.

Division of Emergency Medicine, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, United States; Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, United States.

Objectives: To evaluate the linguistic changes of transgender-related resources prior to 1999 to create a comprehensive dataset of resources using an ontology-derived search system, laying a framework for ontology-based reviews to be used in informatics.

Methods: We analyzed 77 bibliographies and 11 databases for transgender resources published prior to 31 December 1999. We used 858 variants of the term "transgender" to identify resources. Read More

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September 2021