AIMC Topic: Artificial Intelligence

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Developing and Implementing Predictive Models in a Learning Healthcare System: Traditional and Artificial Intelligence Approaches in the Veterans Health Administration.

Annual review of biomedical data science
Predicting clinical risk is an important part of healthcare and can inform decisions about treatments, preventive interventions, and provision of extra services. The field of predictive models has been revolutionized over the past two decades by elec...

Virtual reality in cardiac interventions-New tools or new toys?

Journal of cardiac surgery
Improvementsin medical imaging and a steady increase in computing power are leading to new possibilities in the field of cardiovascular interventions. Interventions can be planned in advance in greater detail, even to the point of simulating procedur...

Addressing neuroethics issues in practice: Lessons learnt by tech companies in AI ethics.

Neuron
Neurotechnologies raise ethical concerns overlapping with those of other technologies, like artificial intelligence (AI). We discuss how to leverage the experience and lessons learnt by tech companies addressing AI ethics issues to accelerate going f...

Automatic vein measurement by ultrasonography to prevent peripheral intravenous catheter failure for clinical practice using artificial intelligence: development and evaluation study of an automatic detection method based on deep learning.

BMJ open
OBJECTIVES: Complications due to peripheral intravenous catheters (PIVC) can be assessed using ultrasound imaging; however, it is not routinely conducted due to the need for training in image reading techniques. This study aimed to develop and valida...

Computed Tomography Texture Features and Risk Factor Analysis of Postoperative Recurrence of Patients with Advanced Gastric Cancer after Radical Treatment under Artificial Intelligence Algorithm.

Computational intelligence and neuroscience
Computer tomography texture analysis (CTTA) based on the V-Net convolutional neural network (CNN) algorithm was used to analyze the recurrence of advanced gastric cancer after radical treatment. Meanwhile, the clinical characteristics of patients wer...

Mandibular premolar identification system based on a deep learning model.

Journal of oral biosciences
OBJECTIVES: For constructing an isolated tooth identification system using deep learning, Igarashi et al. (2021) began constructing a learning model as basic research to identify the left and right mandibular first and second premolars. These teeth w...

Fully automatic volume segmentation using deep learning approaches to assess aneurysmal sac evolution after infrarenal endovascular aortic repair.

Journal of vascular surgery
OBJECTIVE: Endovascular aortic repair (EVAR) surveillance relies on serial measurements of the maximal diameter despite significant inter- and intraobserver variability. Volumetric measurements are more sensitive; however, their general use has been ...

Developing image analysis methods for digital pathology.

The Journal of pathology
The potential to use quantitative image analysis and artificial intelligence is one of the driving forces behind digital pathology. However, despite novel image analysis methods for pathology being described across many publications, few become widel...

Digital Health Profile of South Korea: A Cross Sectional Study.

International journal of environmental research and public health
(1) Backgroud: For future national digital healthcare policy development, it is vital to collect baseline data on the infrastructure and services of medical institutions' information and communication technology (ICT). To assess the state of medical ...