AIMC Topic: Humans

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Automatic post-stroke lesion segmentation on MR images using 3D residual convolutional neural network.

NeuroImage. Clinical
In this paper, we demonstrate the feasibility and performance of deep residual neural networks for volumetric segmentation of irreversibly damaged brain tissue lesions on T1-weighted MRI scans for chronic stroke patients. A total of 239 T1-weighted M...

The compatibility of theoretical frameworks with machine learning analyses in psychological research.

Current opinion in psychology
Supervised machine learning has been increasingly used in psychology and psychiatry research. Machine learning offers an important advantage over traditional statistical analyses: statistical model training in example data to enhance predictions in e...

Using machine learning to improve ensemble docking for drug discovery.

Proteins
Ensemble docking has provided an inexpensive method to account for receptor flexibility in molecular docking for virtual screening. Unfortunately, as there is no rigorous theory to connect the docking scores from multiple structures to measured activ...

Automatic Medical Code Assignment via Deep Learning Approach for Intelligent Healthcare.

IEEE journal of biomedical and health informatics
With the development of healthcare 4.0, there has been an explosion in the amount of data such as image, medical text, physiological signals, lab tests, etc. Among them, medical records provide a complete picture of the associated clinical events. Ho...

Correction of out-of-FOV motion artifacts using convolutional neural network.

Magnetic resonance imaging
PURPOSE: Subject motion during MRI scan can result in severe degradation of image quality. Existing motion correction algorithms rely on the assumption that no information is missing during motions. However, this assumption does not hold when out-of-...

Developing knowledge-based planning for gynaecological and rectal cancers: a clinical validation of RapidPlan.

Journal of medical radiation sciences
INTRODUCTION: To create and clinically validate knowledge-based planning (KBP) models for gynaecologic (GYN) and rectal cancer patients. Assessment of ecologic generalisability and predictive validity of conventional planning versus single calculatio...

rSILS: initial clinical experience with single-port robotic (SPr) right colectomy.

Techniques in coloproctology
BACKGROUND: The da Vinci Single-Port (SP) robot is a novel platform designed to facilitate single-incision robotic surgery (rSILS). The objective of this study was to describe our initial experience using this platform for SP robotic (SPr) right cole...

Intelligent image-based deformation-assisted cell sorting with molecular specificity.

Nature methods
Although label-free cell sorting is desirable for providing pristine cells for further analysis or use, current approaches lack molecular specificity and speed. Here, we combine real-time fluorescence and deformability cytometry with sorting based on...

Experimental Data Based Machine Learning Classification Models with Predictive Ability to Select in Vitro Active Antiviral and Non-Toxic Essential Oils.

Molecules (Basel, Switzerland)
In the last decade essential oils have attracted scientists with a constant increase rate of more than 7% as witnessed by almost 5000 articles. Among the prominent studies essential oils are investigated as antibacterial agents alone or in combinatio...

IoT-Blockchain Enabled Optimized Provenance System for Food Industry 4.0 Using Advanced Deep Learning.

Sensors (Basel, Switzerland)
Agriculture and livestock play a vital role in social and economic stability. Food safety and transparency in the food supply chain are a significant concern for many people. Internet of Things (IoT) and blockchain are gaining attention due to their ...