1,335 results match your criteria machine translation


Machine Learning for Medical Coding in Healthcare Surveys.

Vital Health Stat 1 2021 Oct(189):1-29

Objectives Medical coding, or the translation of healthcare information into numeric codes, is expensive and time intensive. This exploratory study evaluates the use of machine learning classifiers to perform automated medical coding for large statistical healthcare surveys. Read More

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October 2021

Validation of the Reliability of Machine Translation for a Medical Article From Japanese to English Using DeepL Translator.

Cureus 2021 Sep 6;13(9):e17778. Epub 2021 Sep 6.

Department of Radiation Oncology, Kanagawa Cancer Center, Yokohama, JPN.

Background The reliability of DeepL Translator (DeepL GmbH, Cologne, Germany) for the translation for medical articles has not been verified yet. In this study, we investigated the accuracy of machine translation from Japanese to English for a medical article using the DeepL Translator. Methodology The subject of this study was an English-language medical article translated from Japanese, which had already been published. Read More

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September 2021

Evaluation framework to guide implementation of AI systems into healthcare settings.

BMJ Health Care Inform 2021 Oct;28(1)

Deakin University Faculty of Health, Geelong, Victoria, Australia.

Objectives: To date, many artificial intelligence (AI) systems have been developed in healthcare, but adoption has been limited. This may be due to inappropriate or incomplete evaluation and a lack of internationally recognised AI standards on evaluation. To have confidence in the generalisability of AI systems in healthcare and to enable their integration into workflows, there is a need for a practical yet comprehensive instrument to assess the translational aspects of the available AI systems. Read More

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October 2021

A Transformer-Based Neural Machine Translation Model for Arabic Dialects That Utilizes Subword Units.

Sensors (Basel) 2021 Sep 29;21(19). Epub 2021 Sep 29.

School of Computer Science and Engineering, Kyungpook National University, 80 Daehak-ro, Buk-gu, Daegu 41566, Korea.

Languages that allow free word order, such as Arabic dialects, are of significant difficulty for neural machine translation (NMT) because of many scarce words and the inefficiency of NMT systems to translate these words. Unknown Word (UNK) tokens represent the out-of-vocabulary words for the reason that NMT systems run with vocabulary that has fixed size. Scarce words are encoded completely as sequences of subword pieces employing the Word-Piece Model. Read More

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September 2021

Assessing Communicative Effectiveness of Public Health Information in Chinese: Developing Automatic Decision Aids for International Health Professionals.

Int J Environ Res Public Health 2021 Sep 30;18(19). Epub 2021 Sep 30.

School of Languages and Cultures, The University of Sydney, Sydney 2006, Australia.

Effective multilingual communication of authoritative health information plays an important role in helping to reduce health disparities and inequalities in developed and developing countries. Health information communication from the World Health Organization is governed by key principles including health information relevance, credibility, understandability, actionability, accessibility. Multilingual health information developed under these principles provide valuable benchmarks to assess the quality of health resources developed by local health authorities. Read More

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September 2021

Multi-Stage Harmonization for Robust AI across Breast MR Databases.

Cancers (Basel) 2021 Sep 26;13(19). Epub 2021 Sep 26.

Department of Radiology, The University of Chicago, Chicago, IL 60637, USA.

Radiomic features extracted from medical images may demonstrate a batch effect when cases come from different sources. We investigated classification performance using training and independent test sets drawn from two sources using both pre-harmonization and post-harmonization features. In this retrospective study, a database of thirty-two radiomic features, extracted from DCE-MR images of breast lesions after fuzzy c-means segmentation, was collected. Read More

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September 2021

Artificial Intelligence in Thyroid Field-A Comprehensive Review.

Cancers (Basel) 2021 Sep 22;13(19). Epub 2021 Sep 22.

Servizio di Endocrinologia e Diabetologia, Ospedale Regionale di Lugano e Mendrisio, Ente Ospedaliero Cantonale, 6900 Lugano, Switzerland.

Artificial intelligence (AI) uses mathematical algorithms to perform tasks that require human cognitive abilities. AI-based methodologies, e.g. Read More

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September 2021

O-JMeSH: creating a bilingual English-Japanese controlled vocabulary of MeSH UIDs through machine translation and mutual information.

Genomics Inform 2021 Sep 30;19(3):e26. Epub 2021 Sep 30.

Graduate School of Integrative Science and Engineering, Tokyo City University, Tokyo 158-8557, Japan.

Previous approaches to create a controlled vocabulary for Japanese have resorted to existing bilingual dictionary and transformation rules to allow such mappings. However, given the possible new terms introduced due to coronavirus disease 2019 (COVID-19) and the emphasis on respiratory and infection-related terms, coverage might not be guaranteed. We propose creating a Japanese bilingual controlled vocabulary based on MeSH terms assigned to COVID-19 related publications in this work. Read More

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September 2021

Optimization of Machine Online Translation System Based on Deep Convolution Neural Network Algorithm.

Authors:
Juan Zhao

Comput Intell Neurosci 2021 29;2021:7388825. Epub 2021 Sep 29.

School of Foreign Studies, North China University of Water Resources and Electric Power, Zhengzhou, Henan 450046, China.

In order to effectively optimize the machine online translation system and improve its translation efficiency and translation quality, this study uses the deep separable convolution neural network algorithm to construct a machine online translation model and evaluates the quality on the basis of pseudo data learning. In order to verify the performance of the model, the regression performance experiment of the model, the method performance experiment of generating pseudo data for specific tasks, the sorting task performance experiment of the model, and the machine translation quality comparison experiment are designed. RMSE and MAE were used to evaluate the regression task performance of the model. Read More

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October 2021

An Iterative and Collaborative End-to-End Methodology Applied to Digital Mental Health.

Front Psychiatry 2021 23;12:574440. Epub 2021 Sep 23.

Groupe onepoint, Paris, France.

Artificial intelligence (AI) algorithms together with advances in data storage have recently made it possible to better characterize, predict, prevent, and treat a range of psychiatric illnesses. Amid the rapidly growing number of biological devices and the exponential accumulation of data in the mental health sector, the upcoming years are facing a need to homogenize research and development processes in academia as well as in the private sector and to centralize data into federalizing platforms. This has become even more important in light of the current global pandemic. Read More

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September 2021

A Multifaceted Approach to Optimizing AAV Delivery to the Brain for the Treatment of Neurodegenerative Diseases.

Front Neurosci 2021 24;15:747726. Epub 2021 Sep 24.

Department of Neurology, University of Maryland School of Medicine, Baltimore, MD, United States.

Despite major advancements in gene therapy technologies, there are no approved gene therapies for diseases which predominantly effect the brain. Adeno-associated virus (AAV) vectors have emerged as the most effective delivery vector for gene therapy owing to their simplicity, wide spread transduction and low immunogenicity. Unfortunately, the blood-brain barrier (BBB) makes IV delivery of AAVs, to the brain highly inefficient. Read More

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September 2021

Translating the InChI: adapting neural machine translation to predict IUPAC names from a chemical identifier.

J Cheminform 2021 Oct 7;13(1):79. Epub 2021 Oct 7.

School of Chemistry, Faculty of Engineering and Physical Sciences, University of Southampton, Southampton, SO17 1BJ, UK.

We present a sequence-to-sequence machine learning model for predicting the IUPAC name of a chemical from its standard International Chemical Identifier (InChI). The model uses two stacks of transformers in an encoder-decoder architecture, a setup similar to the neural networks used in state-of-the-art machine translation. Unlike neural machine translation, which usually tokenizes input and output into words or sub-words, our model processes the InChI and predicts the IUPAC name character by character. Read More

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October 2021

Predicting the Linguistic Accessibility of Chinese Health Translations: Machine Learning Algorithm Development.

JMIR Med Inform 2021 Oct 7;9(10):e30588. Epub 2021 Oct 7.

University of Geneva, Geneva, Switzerland.

Background: Linguistic accessibility has an important impact on the reception and utilization of translated health resources among multicultural and multilingual populations. Linguistic understandability of health translation has been understudied.

Objective: Our study aimed to develop novel machine learning models for the study of the linguistic accessibility of health translations comparing Chinese translations of the World Health Organization health materials with original Chinese health resources developed by the Chinese health authorities. Read More

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October 2021

Artificial intelligence models in chronic lymphocytic leukemia - recommendations toward state-of-the-art.

Leuk Lymphoma 2021 Oct 6:1-14. Epub 2021 Oct 6.

Department of Hematology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark.

Artificial intelligence (AI), machine learning and predictive modeling are becoming enabling technologies in many day-to-day applications. Translation of these advances to the patient's bedside for AI assisted interventions is not yet the norm. With specific emphasis on CLL, here, we review the progress of prognostic models in hematology and highlight sources of stagnation that may be limiting significant improvements in prognostication in the near future. Read More

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October 2021

On the classification of simple and complex biological images using Krawtchouk moments and Generalized pseudo-Zernike moments: a case study with fly wing images and breast cancer mammograms.

PeerJ Comput Sci 2021 9;7:e698. Epub 2021 Sep 9.

Institute of Mathematical Sciences, Faculty of Science, Universiti Malaya, Kuala Lumpur, Malaysia.

In image analysis, orthogonal moments are useful mathematical transformations for creating new features from digital images. Moreover, orthogonal moment invariants produce image features that are resistant to translation, rotation, and scaling operations. Here, we show the result of a case study in biological image analysis to help researchers judge the potential efficacy of image features derived from orthogonal moments in a machine learning context. Read More

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September 2021

A scoping review of artificial intelligence applications in thoracic surgery.

Eur J Cardiothorac Surg 2021 Oct 3. Epub 2021 Oct 3.

Division of Pulmonary, Critical Care and Sleep Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA.

Objectives: Machine learning (ML) has great potential, but there are few examples of its implementation improving outcomes. The thoracic surgeon must be aware of pertinent ML literature and how to evaluate this field for the safe translation to patient care. This scoping review provides an introduction to ML applications specific to the thoracic surgeon. Read More

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October 2021

Perceptions and knowledge of telemedicine in Ecuadorian practicing physicians: an instrument adaptation, validation and translation from English to Spanish.

BMC Public Health 2021 10 2;21(1):1781. Epub 2021 Oct 2.

Universidad Espíritu Santo, Samborondón, Ecuador.

Background: During the COVID-19 pandemic, multiple countries have taken measures, such as isolation and quarantine, to prevent person-to-person spread of disease. These actions forced many physicians to adopt new techniques, such as telemedicine, to continue patient care, which has proven to be useful in continued care for those with non-COVID-19 pathologies. Various factors, such as security, confidentiality, cost-effectiveness, comfort, and the risk of malpractice, influence the perception of telemedicine among medical practitioners. Read More

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October 2021

Atrial Fibrillation Genomics: Discovery and Translation.

Curr Cardiol Rep 2021 10 1;23(11):164. Epub 2021 Oct 1.

Scripps Clinic, La Jolla, CA, 92037, USA.

Purpose Of Review: Our understanding of the fundamental cellular and molecular factors leading to atrial fibrillation (AF) remains stagnant despite significant advancement in ablation and device technologies. Diagnosis and prevention strategies fall behind that of treatment, but expanding knowledge in AF genetics holds the potential to drive progress. We aim to review how an understanding of the genetic contributions to AF can guide an approach to individualized risk stratification and novel avenues in drug discovery. Read More

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October 2021

Public Covid-19 X-ray datasets and their impact on model bias - A systematic review of a significant problem.

Med Image Anal 2021 Sep 27;74:102225. Epub 2021 Sep 27.

Luxembourg Centre for Systems Biomedicine, University of Luxembourg, 7, Avenue des Hauts Fourneaux, Esch-sur-Alzette L-4362, Luxembourg.

Computer-aided-diagnosis and stratification of COVID-19 based on chest X-ray suffers from weak bias assessment and limited quality-control. Undetected bias induced by inappropriate use of datasets, and improper consideration of confounders prevents the translation of prediction models into clinical practice. By adopting established tools for model evaluation to the task of evaluating datasets, this study provides a systematic appraisal of publicly available COVID-19 chest X-ray datasets, determining their potential use and evaluating potential sources of bias. Read More

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September 2021

Rationale and Pathways Forward in the Implementation of Coronary Artery Calcium-Based Enrichment of Randomized Trials.

Am Heart J 2021 Sep 26. Epub 2021 Sep 26.

Division of Cardiovascular Prevention and Wellness, Department of Cardiology, Houston Methodist DeBakey Heart & Vascular Center, Houston (TX), USA; Center for Outcomes Research, Houston Methodist, Houston (TX), USA.

The Food and Drug Administration recommends prognostic enrichment of randomized controlled trials (RCTs), aimed at restricting the study population to participants most likely to have events and therefore derive benefit from a given intervention. The coronary artery calcium (CAC) score is powerful discriminator of cardiovascular risk, and in this review we discuss how CAC may be used to augment widely used prognostic enrichment paradigms of RCTs of add-on therapies in primary prevention. We describe recent studies in this space, with special attention to the ability of CAC to further stratify risk among guideline-recommended candidates for add-on risk-reduction therapies. Read More

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September 2021

The application of radiomics in laryngeal cancer.

Br J Radiol 2021 Sep 29:20210499. Epub 2021 Sep 29.

Otolaryngology Department, Newcastle-Upon-Tyne Hospitals NHS Foundation Trust, Newcastle Upon Tyne, UK.

Objectives: Radiomics is the conversion of medical images into quantitative high-dimensional data. Laryngeal cancer, one of the most common head and neck cancers, has risen globally by 58.7%. Read More

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September 2021

Enrichment of SARS-CoV-2 Entry Factors and Interacting Intracellular Genes in Tissue and Circulating Immune Cells.

Viruses 2021 09 2;13(9). Epub 2021 Sep 2.

Center for Translational Immunology, University Medical Center Utrecht, 3584 EA Utrecht, The Netherlands.

SARS-CoV-2 uses ACE2 and TMPRSS2 to gain entry into the cell. However, recent studies have shown that SARS-CoV-2 may use additional host factors that are required for the viral lifecycle. Here we used publicly available datasets, CoV-associated genes, and machine learning algorithms to explore the SARS-CoV-2 interaction landscape in different tissues. Read More

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September 2021

Forecasting Erroneous Neural Machine Translation of Disease Symptoms: Development of Bayesian Probabilistic Classifiers for Cross-Lingual Health Translation.

Int J Environ Res Public Health 2021 Sep 19;18(18). Epub 2021 Sep 19.

School of Computer Science, South China Normal University, Guangzhou 510631, China.

Background: Machine translation (MT) technologies have increasing applications in healthcare. Despite their convenience, cost-effectiveness, and constantly improved accuracy, research shows that the use of MT tools in medical or healthcare settings poses risks to vulnerable populations.

Objectives: We aimed to develop machine learning classifiers (MNB and RVM) to forecast nuanced yet significant MT errors of clinical symptoms in Chinese neural MT outputs. Read More

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September 2021

Longitudinal Prediction of Infant MR Images With Multi-Contrast Perceptual Adversarial Learning.

Front Neurosci 2021 9;15:653213. Epub 2021 Sep 9.

Department of Psychiatry, UNC School of Medicine, University of North Carolina, Chapel Hill, NC, United States.

The infant brain undergoes a remarkable period of neural development that is crucial for the development of cognitive and behavioral capacities (Hasegawa et al., 2018). Longitudinal magnetic resonance imaging (MRI) is able to characterize the developmental trajectories and is critical in neuroimaging studies of early brain development. Read More

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September 2021

Protein Abundance Prediction Through Machine Learning Methods.

J Mol Biol 2021 Sep 23;433(22):167267. Epub 2021 Sep 23.

Department of Microbiology, Universidade Federal de Viçosa, Viçosa, MG 36570-900, Brazil. Electronic address:

Proteins are responsible for most physiological processes, and their abundance provides crucial information for systems biology research. However, absolute protein quantification, as determined by mass spectrometry, still has limitations in capturing the protein pool. Protein abundance is impacted by translation kinetics, which rely on features of codons. Read More

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September 2021

iR5hmcSC: Identifying RNA 5-hydroxymethylcytosine with multiple features based on stacking learning.

Comput Biol Chem 2021 Sep 20;95:107583. Epub 2021 Sep 20.

School of Mathematics and Statistics, Xidian University, Xi'an 710071, PR China.

RNA 5-hydroxymethylcytosine (5hmC) modification is the basis of the translation of genetic information and the biological evolution. The study of its distribution in transcriptome is fundamentally crucial to reveal the biological significance of 5hmC. Biochemical experiments can use a variety of sequencing-based technologies to achieve high-throughput identification of 5hmC; however, they are labor-intensive, time-consuming, as well as expensive. Read More

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September 2021

Predicting fracture outcomes from clinical registry data using artificial intelligence supplemented models for evidence-informed treatment (PRAISE) study protocol.

PLoS One 2021 23;16(9):e0257361. Epub 2021 Sep 23.

Clinical Registries, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.

Background: Distal radius (wrist) fractures are the second most common fracture admitted to hospital. The anatomical pattern of these types of injuries is diverse, with variation in clinical management, guidelines for management remain inconclusive, and the uptake of findings from clinical trials into routine practice limited. Robust predictive modelling, which considers both the characteristics of the fracture and patient, provides the best opportunity to reduce variation in care and improve patient outcomes. Read More

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September 2021

Analysis of potential genetic biomarkers and molecular mechanism of smoking-related postmenopausal osteoporosis using weighted gene co-expression network analysis and machine learning.

PLoS One 2021 23;16(9):e0257343. Epub 2021 Sep 23.

Department of Traumatology & Orthopedics, Wuxi Affiliated Hospital of Nanjing University of Chinese Medicine, Wuxi, P.R. China.

Objectives: Smoking is a significant independent risk factor for postmenopausal osteoporosis, leading to genome variations in postmenopausal smokers. This study investigates potential biomarkers and molecular mechanisms of smoking-related postmenopausal osteoporosis (SRPO).

Materials And Methods: The GSE13850 microarray dataset was downloaded from Gene Expression Omnibus (GEO). Read More

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September 2021

Assessment of Quality of Life 8-Dimension (AQoL-8D): translation, validation, and application in two Dutch trials in patients with epilepsy and schizophrenia.

Expert Rev Pharmacoecon Outcomes Res 2021 Sep 26:1-9. Epub 2021 Sep 26.

Department of Health Services Research, CAPHRI Care and Public Health Research Institute, Maastricht University, Maastricht, The Netherlands.

Background: To translate and linguistically validate the Assessment of Quality of Life 8-dimensions (AQoL-8D) for use in the Netherlands and to compare the psychometric properties of AQoL-8D with the EuroQol 5-dimensions 5-levels (EQ-5D-5L) in two patient samples.

Methods: AQoL-8D was translated from English into Dutch. The translated AQoL-8D was then administered alongside the EQ-5D-5L at baseline and follow-up of two Dutch randomized controlled trials among patients with epilepsy and schizophrenia. Read More

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September 2021

API2CAN: a dataset & service for canonical utterance generation for REST APIs.

BMC Res Notes 2021 Sep 22;14(1):368. Epub 2021 Sep 22.

UNSW Sydney, Kensington, Australia.

Objectives: Recently natural language interfaces (e.g., chatbots) have gained enormous attention. Read More

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September 2021