AIMC Topic: Humans

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Pancreatic Cancer Imaging: A New Look at an Old Problem.

Current problems in diagnostic radiology
Computed tomography is the most commonly used imaging modality to detect and stage pancreatic cancer. Previous advances in pancreatic cancer imaging have focused on optimizing image acquisition parameters and reporting standards. However, current sta...

Attitudes and perceptions of dental students towards artificial intelligence.

Journal of dental education
INTRODUCTION: Artificial Intelligence (AI) is a burning topic and use of AI in our day-to-day life has increased exponentially. The purpose of this study was to evaluate the attitudes and perceptions of Turkish dental students towards AI and to provi...

Neuroimaging and deep learning for brain stroke detection - A review of recent advancements and future prospects.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: In recent years, deep learning algorithms have created a massive impact on addressing research challenges in different domains. The medical field also greatly benefits from the use of improving deep learning models which sav...

White learning methodology: A case study of cancer-related disease factors analysis in real-time PACS environment.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Bayesian network is a probabilistic model of which the prediction accuracy may not be one of the highest in the machine learning family. Deep learning (DL) on the other hand possess of higher predictive power than many other...

Artificial Intelligence (AI) based machine learning models predict glucose variability and hypoglycaemia risk in patients with type 2 diabetes on a multiple drug regimen who fast during ramadan (The PROFAST - IT Ramadan study).

Diabetes research and clinical practice
OBJECTIVE: To develop a machine-based algorithm from clinical and demographic data, physical activity and glucose variability to predict hyperglycaemic and hypoglycaemic excursions in patients with type 2 diabetes on multiple glucose lowering therapi...

DZC DIAG: mobile application based on expert system to aid in the diagnosis of dengue, Zika, and chikungunya.

Medical & biological engineering & computing
Dengue, Zika, and chikungunya are epidemic diseases transmitted by the Aedes mosquito. These virus infections can be so severe to the point of bringing on mobility and neurological problems, or even death. Expert systems (ES) can be used as tools for...

Prediction of visual field from swept-source optical coherence tomography using deep learning algorithms.

Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie
PURPOSE: To develop a deep learning method to predict visual field (VF) from wide-angle swept-source optical coherence tomography (SS-OCT) and compare the performance of three Google Inception architectures.

Early experience utilizing artificial intelligence shows significant reduction in transfer times and length of stay in a hub and spoke model.

Interventional neuroradiology : journal of peritherapeutic neuroradiology, surgical procedures and related neurosciences
BACKGROUND: Recently approved artificial intelligence (AI) software utilizes AI powered large vessel occlusion (LVO) detection technology which automatically identifies suspected LVO through CT angiogram (CTA) imaging and alerts on-call stroke teams....

Deep Learning Based Software to Identify Large Vessel Occlusion on Noncontrast Computed Tomography.

Stroke
BACKGROUND AND PURPOSE: Reliable recognition of large vessel occlusion (LVO) on noncontrast computed tomography (NCCT) may accelerate identification of endovascular treatment candidates. We aim to validate a machine learning algorithm (MethinksLVO) t...

Spatial-channel relation learning for brain tumor segmentation.

Medical physics
PURPOSE: Recently, research on brain tumor segmentation has made great progress. However, ambiguous patterns in magnetic resonance imaging data and linear fusion omitting semantic gaps between features in different branches remain challenging. We nee...