AI Medical Compendium Topic

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Cloud Computing

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Towards implementation of AI in New Zealand national diabetic screening program: Cloud-based, robust, and bespoke.

PloS one
Convolutional Neural Networks (CNNs) have become a prominent method of AI implementation in medical classification tasks. Grading Diabetic Retinopathy (DR) has been at the forefront of the development of AI for ophthalmology. However, major obstacles...

PRIMAGE project: predictive in silico multiscale analytics to support childhood cancer personalised evaluation empowered by imaging biomarkers.

European radiology experimental
PRIMAGE is one of the largest and more ambitious research projects dealing with medical imaging, artificial intelligence and cancer treatment in children. It is a 4-year European Commission-financed project that has 16 European partners in the consor...

Cloud-based ECG monitoring using event-driven ECG acquisition and machine learning techniques.

Physical and engineering sciences in medicine
An approach is proposed for the detection of chronic heart disorders from the electrocardiogram (ECG) signals. It utilizes an intelligent event-driven ECG signal acquisition system to achieve a real-time compression and effective signal processing an...

A Scalable Smartwatch-Based Medication Intake Detection System Using Distributed Machine Learning.

Journal of medical systems
Poor Medication adherence causes significant economic impact resulting in hospital readmission, hospital visits and other healthcare costs. The authors developed a smartwatch application and a cloud based data pipeline for developing a user-friendly ...

A health informatics transformation model based on intelligent cloud computing - exemplified by type 2 diabetes mellitus with related cardiovascular diseases.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Many studies regarding health analysis request structured datasets but the legacy resources provide scattered data. This study aims to establish a health informatics transformation model (HITM) based upon intelligent cloud c...

Continuous Wearable Monitoring Analytics Predict Heart Failure Hospitalization: The LINK-HF Multicenter Study.

Circulation. Heart failure
BACKGROUND: Implantable cardiac sensors have shown promise in reducing rehospitalization for heart failure (HF), but the efficacy of noninvasive approaches has not been determined. The objective of this study was to determine the accuracy of noninvas...

Tracking Knowledge Evolution in Cloud Health Care Research: Knowledge Map and Common Word Analysis.

Journal of medical Internet research
BACKGROUND: With the continuous development of the internet and the explosive growth in data, big data technology has emerged. With its ongoing development and application, cloud computing technology provides better data storage and analysis. The dev...

Deep feature transfer learning for trusted and automated malware signature generation in private cloud environments.

Neural networks : the official journal of the International Neural Network Society
This paper presents TrustSign, a novel, trusted automatic malware signature generation method based on high-level deep features transferred from a VGG-19 neural network model pretrained on the ImageNet dataset. While traditional automatic malware sig...

Recognition of big data mixed Raman spectra based on deep learning with smartphone as Raman analyzer.

Electrophoresis
Raman spectral detection has emerged as a powerful analytical technique due to the advantages of fast acquisition, non-invasion, and low cost. The on-site application is highly dependent on Raman automatic analysis algorithm. However, current Raman a...

Cloud-computing and machine learning in support of country-level land cover and ecosystem extent mapping in Liberia and Gabon.

PloS one
Liberia and Gabon joined the Gaborone Declaration for Sustainability in Africa (GDSA), established in 2012, with the goal of incorporating the value of nature into national decision making by estimating the multiple services obtained from ecosystems ...