AIMC Topic: Humans

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Feasibility of robot-assisted neuroendovascular procedures.

Journal of neurosurgery
OBJECTIVE: Geographic factors prevent equitable access to urgent advanced neuroendovascular treatments. Robotic technologies may enable remote endovascular procedures in the future. The authors performed a translational, benchtop-to-clinical study to...

Machine learning methods for prediction of food effects on bioavailability: A comparison of support vector machines and artificial neural networks.

European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences
Despite countless advances in recent decades across various in vitro, in vivo and in silico tools, anticipation of whether a drug will show a human food effect (FE) remains challenging. One means to predict potential FE involves probing any dependenc...

Towards real time guide wire shape extraction in fluoroscopic sequences: A two phase deep learning scheme to extract sparse curvilinear structures.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
BACKGROUND AND OBJECTIVE: Real time localization and shape extraction of guide wire in fluoroscopic images plays a significant role in the image guided navigation during cerebral and cardiovascular interventions. Given the complexity of the non-rigid...

A comparative analysis of eleven neural networks architectures for small datasets of lung images of COVID-19 patients toward improved clinical decisions.

Computers in biology and medicine
The 2019 novel severe acute respiratory syndrome coronavirus 2-SARS-CoV2, commonly known as COVID-19, is a highly infectious disease that has endangered the health of many people around the world. COVID-19, which infects the lungs, is often diagnosed...

Complications of robot-assisted thymectomy: A single-arm meta-analysis and systematic review.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: Recently, thymectomy using minimally invasive approaches has been increasing with the development of robotic video-assisted thoracoscopic surgery (R-VATS). Although multimodal approach is effective for robot assisted thymectomy, it is nec...

Deep learning-enabled EPID-based 3D dosimetry for dose verification of step-and-shoot radiotherapy.

Medical physics
PURPOSE: The study aims at a novel dosimetry methodology to reconstruct a 3D dose distribution as imparted to a virtual cylindrical phantom using an electronic portal imaging device (EPID).

Clinically Distinct Subtypes of Acute Kidney Injury on Hospital Admission Identified by Machine Learning Consensus Clustering.

Medical sciences (Basel, Switzerland)
BACKGROUND: We aimed to cluster patients with acute kidney injury at hospital admission into clinically distinct subtypes using an unsupervised machine learning approach and assess the mortality risk among the distinct clusters.

Recognition of Fine-Grained Walking Patterns Using a Smartwatch with Deep Attentive Neural Networks.

Sensors (Basel, Switzerland)
Generally, people do various things while walking. For example, people frequently walk while looking at their smartphones. Sometimes we walk differently than usual; for example, when walking on ice or snow, we tend to waddle. Understanding walking pa...

Visual explanations from spiking neural networks using inter-spike intervals.

Scientific reports
By emulating biological features in brain, Spiking Neural Networks (SNNs) offer an energy-efficient alternative to conventional deep learning. To make SNNs ubiquitous, a 'visual explanation' technique for analysing and explaining the internal spike b...