AIMC Topic: Adult

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Accuracy and time efficiency of a novel deep learning algorithm for Intracranial Hemorrhage detection in CT Scans.

La Radiologia medica
PURPOSE: To evaluate a deep learning-based pipeline using a Dense-UNet architecture for the assessment of acute intracranial hemorrhage (ICH) on non-contrast computed tomography (NCCT) head scans after traumatic brain injury (TBI).

A multicenter study on deep learning for glioblastoma auto-segmentation with prior knowledge in multimodal imaging.

Cancer science
A precise radiotherapy plan is crucial to ensure accurate segmentation of glioblastomas (GBMs) for radiation therapy. However, the traditional manual segmentation process is labor-intensive and heavily reliant on the experience of radiation oncologis...

Family history of cancer and lung cancer: Utility of big data and artificial intelligence for exploring the role of genetic risk.

Lung cancer (Amsterdam, Netherlands)
OBJECTIVES: Lung Cancer (LC) is a multifactorial disease for which the role of genetic susceptibility has become increasingly relevant. Our aim was to use artificial intelligence (AI) to analyze differences between patients with LC based on family hi...

Clinical application of convolutional neural network lung nodule detection software: An Australian quaternary hospital experience.

Journal of medical imaging and radiation oncology
INTRODUCTION: Early-stage lung cancer diagnosis through detection of nodules on computed tomography (CT) remains integral to patient survivorship, promoting national screening programmes and diagnostic tools using artificial intelligence (AI) convolu...

The impact of differential pricing subject on consumer behavior.

BMC psychology
The escalating use of artificial intelligence in marketing significantly impacts all aspects of consumer life. This research, grounded in attribution theory and S-O-R theory, employs scenario-based experimental methods to simulate two distinct purcha...

Admission blood tests predicting survival of SARS-CoV-2 infected patients: a practical implementation of graph convolution network in imbalance dataset.

BMC infectious diseases
BACKGROUND: Predicting an individual's risk of death from COVID-19 is essential for planning and optimising resources. However, since the real-world mortality rate is relatively low, particularly in places like Hong Kong, this makes building an accur...

Establishing the importance of co-creation and self-efficacy in creative collaboration with artificial intelligence.

Scientific reports
The emergence of generative AI technologies has led to an increasing number of people collaborating with AI to produce creative works. Across two experimental studies, in which we carefully designed and programmed state-of-the-art human-AI interfaces...

Impact of training data composition on the generalizability of convolutional neural network aortic cross-section segmentation in four-dimensional magnetic resonance flow imaging.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
BACKGROUND: Four-dimensional cardiovascular magnetic resonance flow imaging (4D flow CMR) plays an important role in assessing cardiovascular diseases. However, the manual or semi-automatic segmentation of aortic vessel boundaries in 4D flow data int...

Human-Robot Collaboration With a Corrective Shared Controlled Robot in a Sanding Task.

Human factors
OBJECTIVE: Physical and cognitive workloads and performance were studied for a corrective shared control (CSC) human-robot collaborative (HRC) sanding task.

Deep learning MR reconstruction in knees and ankles in children and young adults. Is it ready for clinical use?

Skeletal radiology
OBJECTIVE: To evaluate the diagnostic performance and image quality of accelerated Turbo Spin Echo sequences using deep-learning (DL) reconstructions compared to conventional sequences in knee and ankle MRIs of children and young adults.