AIMC Topic: Software Design
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AI-driven cybersecurity framework for software development based on the ANN-ISM paradigm.
Scientific reports
Apr 18, 2025
With the increasing reliance on software applications, cybersecurity threats have become a critical concern for developers and organizations. The answer to this vulnerability is AI systems, which help us adapt a little better, as traditional measures...
[Supporting medical and nursing activities with AI: recommendations for responsible design and use].
Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz
Jul 17, 2024
Clinical decision support systems (CDSS) based on artificial intelligence (AI) are complex socio-technical innovations and are increasingly being used in medicine and nursing to improve the overall quality and efficiency of care, while also addressin...
Robotic tomographic ultrasound and artificial intelligence for management of haemodialysis arteriovenous fistulae.
The journal of vascular access
Nov 23, 2023
BACKGROUND: Arteriovenous fistulae (AVF) and Arteriovenous Grafts (AVG) may present a problematic vascular access for renal replacement therapy (RRT), reliant on recurrent specialist nurse and medical evaluation. Dysfunctional accesses are frequently...
Software Design
Robotics
Software
Renal Dialysis
Equipment Design
Humans
Blood Vessel Prosthesis Implantation
Treatment Outcome
Image Interpretation, Computer-Assisted
Artificial Intelligence
Arteriovenous Shunt, Surgical
Predictive Value of Tests
Ultrasonography, Doppler
Graft Occlusion, Vascular
Vascular Patency
Cross-Camera External Validation for Artificial Intelligence Software in Diagnosis of Diabetic Retinopathy.
Journal of diabetes research
Mar 9, 2022
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).
A machine learning pipeline for classification of cetacean echolocation clicks in large underwater acoustic datasets.
PLoS computational biology
Dec 3, 2021
Machine learning algorithms, including recent advances in deep learning, are promising for tools for detection and classification of broadband high frequency signals in passive acoustic recordings. However, these methods are generally data-hungry and...
Evaluation of Deep Neural Network ProSPr for Accurate Protein Distance Predictions on CASP14 Targets.
International journal of molecular sciences
Nov 27, 2021
The field of protein structure prediction has recently been revolutionized through the introduction of deep learning. The current state-of-the-art tool AlphaFold2 can predict highly accurate structures; however, it has a prohibitively long inference ...
Automated recognition of objects and types of forceps in surgical images using deep learning.
Scientific reports
Nov 19, 2021
Analysis of operative data with convolutional neural networks (CNNs) is expected to improve the knowledge and professional skills of surgeons. Identification of objects in videos recorded during surgery can be used for surgical skill assessment and s...
Deep Learning Algorithm for COVID-19 Classification Using Chest X-Ray Images.
Computational and mathematical methods in medicine
Nov 9, 2021
Early diagnosis of the harmful severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), along with clinical expertise, allows governments to break the transition chain and flatten the epidemic curve. Although reverse transcription-polymerase cha...
Development of a Method for Clinical Evaluation of Artificial Intelligence-Based Digital Wound Assessment Tools.
JAMA network open
May 3, 2021
IMPORTANCE: Accurate assessment of wound area and percentage of granulation tissue (PGT) are important for optimizing wound care and healing outcomes. Artificial intelligence (AI)-based wound assessment tools have the potential to improve the accurac...
MIScnn: a framework for medical image segmentation with convolutional neural networks and deep learning.
BMC medical imaging
Jan 18, 2021
BACKGROUND: The increased availability and usage of modern medical imaging induced a strong need for automatic medical image segmentation. Still, current image segmentation platforms do not provide the required functionalities for plain setup of medi...
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