AIMC Topic: Artificial Intelligence

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Weighted Bayesian Belief Network: A Computational Intelligence Approach for Predictive Modeling in Clinical Datasets.

Computational intelligence and neuroscience
There are growing concerns about the mortality due to Breast cancer many of which often result from delayed detection and treatment. So an effective computational approach is needed to develop a predictive model which will help patients and physician...

Cultural and Creative Product Design and Image Recognition Based on the Convolutional Neural Network Model.

Computational intelligence and neuroscience
The development in technology has resulted in the utilization of artificial intelligence systems in various fields. In this research, we are going to study cultural and creative product design and image recognition based on a convolutional neural net...

AIOps Architecture in Data Center Site Infrastructure Monitoring.

Computational intelligence and neuroscience
AIOps (artificial intelligence for IT operations) has been growing rapidly in recent years. However, it can be seen that the vast majority of AIOps applications are implemented in the IT domain. In contrast, there are few applications in the data cen...

Editor's Review and Introduction: Cognition-Inspired Artificial Intelligence.

Topics in cognitive science
Cognitive science has much to contribute to the general scientific body of knowledge, but it is also a field rife with possibilities for providing background research that can be leveraged by artificial intelligence (AI) developers. In this introduct...

Artificial intelligence in acute respiratory distress syndrome: A systematic review.

Artificial intelligence in medicine
BACKGROUND AND OBJECTIVE: Acute respiratory distress syndrome (ARDS) is a life-threatening pulmonary disease with a high clinical and cost burden across the globe. Artificial intelligence (AI), an emerging area, has been used for various purposes in ...

Assessing the robustness of clinical trials by estimating Jadad's score using artificial intelligence approaches.

Computers in biology and medicine
BACKGROUND: Clinical trials are essential in medical science and are currently the most robust strategy for evaluating the effectiveness of a treatment. However, some of these studies are less reliable than others due to flaws in their design. Assess...

Histologic Screening of Malignant Melanoma, Spitz, Dermal and Junctional Melanocytic Nevi Using a Deep Learning Model.

The American Journal of dermatopathology
OBJECTIVE: The integration of an artificial intelligence tool into pathologists' workflow may lead to a more accurate and timely diagnosis of melanocytic lesions, directly patient care. The objective of this study was to create and evaluate the perfo...

Artificial intelligence in retinal imaging for cardiovascular disease prediction: current trends and future directions.

Current opinion in ophthalmology
PURPOSE OF REVIEW: Retinal microvasculature assessment has shown promise to enhance cardiovascular disease (CVD) risk stratification. Integrating artificial intelligence into retinal microvasculature analysis may increase the screening capacity of CV...

Proceedings from the Society of Interventional Radiology Foundation Research Consensus Panel on Artificial Intelligence in Interventional Radiology: From Code to Bedside.

Journal of vascular and interventional radiology : JVIR
Artificial intelligence (AI)-based technologies are the most rapidly growing field of innovation in healthcare with the promise to achieve substantial improvements in delivery of patient care across all disciplines of medicine. Recent advances in ima...

Co-design of digital learning resources for care workers: reflections on the neurocare knowhow project.

Journal of medical engineering & technology
Neurocare Knowhow is an online learning platform for care workers who support people with neurological conditions. Care workers often do not receive specialist training around neurological conditions and can experience anxiety and apprehension about ...