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Total 65 results found since Jan 2013.
Introducing Cochrane Heart, Stroke and Circulation
Stroke, heart disease, hypertension and peripheral vascular diseases are leading global causes of mortality and morbidity. As the population ages and these conditions become more common in low-income countries, the need for an integrated response has become increasingly clear.The newHeart, Stroke and Circulation Thematic Groupaims to bring together experts from across all four topics to foster collaboration between researchers in different fields while providing comprehensive reviews on cutting-edge topics related to stroke, heart disease, hypertension, and peripheral vascular diseases. A collaborative effortThrough th...
Source: Cochrane News and Events - May 10, 2023 Category: Information Technology Authors: Muriah Umoquit Source Type: news
Hypotension Prediction Index guided Goal Directed therapy and the amount of Hypotension during Major Gynaecologic Oncologic Surgery: a Randomized Controlled clinical Trial
AbstractIntraoperative hypotension (IOH) is associated with increased morbidity and mortality. Hypotension Prediction Index (HPI) is a machine learning derived algorithm that predicts IOH shortly before it occurs. We tested the hypothesis that the application of the HPI in combination with a pre-defined Goal Directed Therapy (GDT) hemodynamic protocol reduces IOH during major gynaecologic oncologic surgery. We enrolled women scheduled for major gynaecologic oncologic surgery under general anesthesia with invasive arterial pressure monitoring. Patients were randomized to a GDT protocol aimed at optimizing stroke volume inde...
Source: Journal of Clinical Monitoring and Computing - April 29, 2023 Category: Information Technology Source Type: research
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
A survey of deep learning for MRI brain tumor segmentation methods: Trends, challenges, and future directions
ConclusionThis review's objective is to increase scholars' interest in this difficult field and familiarize them with current advancements in it. To create CAD systems aimed at brain tumor identification using MR images, digital image processing approaches, such as preprocessing, segmentation, and classification, are applied. The classic machine learning and deep learning approaches for brain tumor identification are deliberated in this work. This paper provides a summary of commonly used MR image datasets. For classification, various machine learning and deep learning algorithms have been used. This survey examines curren...
Source: Health and Technology - February 27, 2023 Category: Information Technology Source Type: research
The 3rd Beijing Forum of Evidence-Based Medicine and 2023 Cochrane China Network Symposium successfully held
Cochrane China recently hosted a virtual event for the evidence-based medicine community that brought together many of its partners, local expertise, and international speakers. Here the team provides an overview of who was involved and what was covered at the event. The3rd Beijing forum of evidence-based medicine and Cochrane China Network Symposium was successfully held virtually on January 15th, 2023. The host of this conference wereCochrane China Network and Beijing GRADE Center. The organizers are Centre for Evidence-based Chinese Medicine, Beijing University of Chinese Medicine, affiliate of the Cochrane China Ne...
Source: Cochrane News and Events - February 17, 2023 Category: Information Technology Authors: Muriah Umoquit Source Type: news
Machine learning in a real-world PFO study: analysis of data from multi-centers in China
The association of patent foreman ovale (PFO) and cryptogenic stroke has been studied for years. Although device closure overall decreases the risk for recurrent stroke, treatment effects varied across differe...
Source: BMC Medical Informatics and Decision Making - November 24, 2022 Category: Information Technology Authors: Dongling Luo, Ziyang Yang, Gangcheng Zhang, Qunshan Shen, Hongwei Zhang, Junxing Lai, Hui Hu, Jianxin He, Shulin Wu and Caojin Zhang Tags: Research Source Type: research
Pilot Report for Intracranial Hemorrhage Detection with Deep Learning Implanted Head Computed Tomography Images at Emergency Department
AbstractHemorrhagic stroke is a serious clinical condition that requires timely diagnosis. An artificial intelligence algorithm system called DeepCT can identify hemorrhagic lesions rapidly from non-contrast head computed tomography (NCCT) images and has received regulatory clearance. A non-controlled retrospective pilot clinical trial was conducted. Patients who received NCCT at the emergency department (ED) of Kaohsiung Veteran General Hospital were collected. From 2020 January-1st to April-30th, the physicians read NCCT images without DeepCT. From 2020May-1st to August-31st, the physicians were assisted by DeepCT. The...
Source: Journal of Medical Systems - June 8, 2022 Category: Information Technology 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
Real-time reviews of research findings will help policymakers address global crises such as COVID-19
Real-time reviews of research findings could help policymakers address global crises such as COVID-19, saysthis articlepublished inNature. Living evidence was first developed by Cochrane and an important recommendation for future health emergencies that came out of the recent Cochrane Convenes meetings. According to scientists writing in the peer-reviewed journal Nature, policy missteps will continue to overshadow the global response to COVID-19 because policymakers are overwhelmed with rapidly shifting research evidence. Faced with new challenges such as the Omicron variant, decision-makers can ’t keep up wi...
Source: Cochrane News and Events - December 15, 2021 Category: Information Technology Authors: Lydia Parsonson Source Type: news
Machine Learning Based Risk Prediction for Major Adverse Cardiovascular Events
CONCLUSION: The developed risk prediction models achieved an excellent performance in the test data. Future research is needed to determine the performance of these models and their clinical benefit in prospective settings.PMID:33965930 | DOI:10.3233/SHTI210100
Source: Studies in Health Technology and Informatics - May 9, 2021 Category: Information Technology Authors: Michael Schrempf Diether Kramer Stefanie Jauk Sai P K Veeranki Werner Leodolter Peter P Rainer Source Type: research
