AIMC Topic: Artificial Intelligence

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Inter-Domain Fusion for Enhanced Intrusion Detection in Power Systems: An Evidence Theoretic and Meta-Heuristic Approach.

Sensors (Basel, Switzerland)
False alerts due to misconfigured or compromised intrusion detection systems (IDS) in industrial control system (ICS) networks can lead to severe economic and operational damage. However, research using deep learning to reduce false alerts often requ...

Contextualized Design of IoT (Internet of Things) Finance for Edge Artificial Intelligence Computing.

Computational intelligence and neuroscience
With the widespread application of IoT technology in the world, the new industry of IoT finance has emerged. Under this new business model, commercial banks and other financial institutions can realize safer and more convenient financial services suc...

Nursing Care Systematization with Case-Based Reasoning and Artificial Intelligence.

Journal of healthcare engineering
Of the most popular applications of artificial intelligence (AI), those used in the health sector are the ones that represent the largest proportion, in terms of use and expectation. An investigative systematization model is proposed in the scientifi...

Cross-Camera External Validation for Artificial Intelligence Software in Diagnosis of Diabetic Retinopathy.

Journal of diabetes research
AIMS: To investigate the applicability of deep learning image assessment software VeriSee DR to different color fundus cameras for the screening of diabetic retinopathy (DR).

Advanced medical monitoring for the battlefield: A review on clinical applicability of compensatory reserve measurements for early and accurate hemorrhage detection.

The journal of trauma and acute care surgery
Hemorrhagic shock remains the leading cause of mortality in civilian trauma and battlefield settings. The ability of combat medics and other military medical personnel to obtain early identification and assessment of a bleeding casualty is hampered b...

An artificial intelligence system using maximum intensity projection MR images facilitates classification of non-mass enhancement breast lesions.

European radiology
OBJECTIVES: To build an artificial intelligence (AI) system to classify benign and malignant non-mass enhancement (NME) lesions using maximum intensity projection (MIP) of early post-contrast subtracted breast MR images.

Compression of Deep Neural Networks based on quantized tensor decomposition to implement on reconfigurable hardware platforms.

Neural networks : the official journal of the International Neural Network Society
Deep Neural Networks (DNNs) have been vastly and successfully employed in various artificial intelligence and machine learning applications (e.g., image processing and natural language processing). As DNNs become deeper and enclose more filters per l...

[Low-field magnetic resonance imaging : Just less expensive or completely different?].

Der Radiologe
Over the years the development of field strength in magnetic resonance imaging (MRI) has continued to increase from the low-field systems in the early years (0.2-0.5 T) to 1.5 T to 3 T to 7 T and more. In the last 2 years, there has been a renewed in...

Using Artificial Intelligence to Better Predict and Develop Biomarkers.

Heart failure clinics
Advancements in technology have improved biomarker discovery in the field of heart failure (HF). What was once a slow and laborious process has gained efficiency through use of high-throughput omics platforms to phenotype HF at the level of genes, tr...

Technical note: A PET/MR coil with an integrated, orbiting 511 keV transmission source for PET/MR imaging validated in an animal study.

Medical physics
BACKGROUND: MR-based methods for attenuation correction (AC) in PET/MRI either neglect attenuation of bone, or use MR-signal derived information about bone, which leads to a bias in quantification of tracer uptake in PET. In a previous study, we pres...