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Total 117 results found since Jan 2013.
Development and validation of predictive model based on deep learning method for classification of dyslipidemia in Chinese medicine
ConclusionsThis study successfully developed a well-performing classification prediction model for dyslipidemia with MOPS, transforming the syndrome diagnosis problem in TCM into a prediction and classification problem in artificial intelligence. Patients with dyslipidemia of MOPS can be accurately recognized through limited information from patients. We also screened out significant diagnostic factors for composing diagnostic rules of dyslipidemia with MOPS. The study is an avant-garde attempt at introducing the deep-learning method into the research of TCM, which provides a useful reference for the extension of deep lear...
Source: Health Information Science and Systems - April 6, 2023 Category: Information Technology Source Type: research
Roundup: Thai researchers develop AI for assessing stroke risk and more briefs
Also, Remidio receives a CE mark for its AI tool for detecting referable diabetic retinopathy.
Source: mobihealthnews - March 3, 2023 Category: Information Technology Source Type: news
Discovering Key Topics in Emergency Medical Dispatch from Free Text Dispatcher Observations
The objective of this work was to discover key topics latent in free text dispatcher observations registered during emergency medical calls. We used a total of 1374931 independent retrospective cases from the Valencian emergency medical dispatch service in Spain, from 2014 to 2019. Text fields were preprocessed to reduce vocabulary size and filter noise, removing accent and punctuation marks, along with uninformative and infrequent words. Key topics were inferred from the multinomial probabilities over words conditioned on each topic from a Latent Dirichlet Allocation model, trained following an online mini-batch variation...
Source: Studies in Health Technology and Informatics - May 25, 2022 Category: Information Technology Authors: Pablo Ferri Carlos S áez Antonio F élix-De Castro Purificaci ón Sánchez-Cuesta Juan M Garc ía-Gómez Source Type: research
Predicting Hospital Readmissions from Health Insurance Claims Data: A Modeling Study Targeting Potentially Inappropriate Prescribing
CONCLUSION: PIP successfully predicted readmissions for most diseases, opening the possibility for interventions to improve these modifiable risk factors. Machine-learning methods appear promising for future modeling of PIP predictors in complex older patients with many underlying diseases.PMID:35144291 | DOI:10.1055/s-0042-1742671
Source: Methods of Information in Medicine - February 10, 2022 Category: Information Technology Authors: Alexander Gerharz Carmen Ruff Lucas Wirbka Felicitas Stoll Walter E Haefeli Andreas Groll Andreas D Meid Source Type: research
Stroke Units Necessity for Patients, Web-Based "SUN4P" Registry: Descriptive Characteristics of the Population
CONCLUSIONS: These data are in accordance with current evidence and should be thoroughly assessed in order to ensure optimal therapeutic management of stroke patients.PMID:35062158 | DOI:10.3233/SHTI210925
Source: Studies in Health Technology and Informatics - January 22, 2022 Category: Information Technology Authors: Georgios Mavraganis Eleni Korompoki Evangelos Tsampalas Dafni Garefou Helen Alexopoulou Maria Lypiridou Ioannis Kalliontzakis Anastasia Fragkoulaki Aspasia Kouridaki Argyro Tountopoulou Ioanna Kouzi Sofia Vassilopoulou Efstathia Karagkiozi Anna-Maria Louk Source Type: research
