AIMC Topic: Humans

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Automating Complex, Multistep Processes on a Single Robotic Platform to Generate Reproducible Phosphoproteomic Data.

SLAS discovery : advancing life sciences R & D
Mass spectrometry-based phosphoproteomics holds promise for advancing drug treatment and disease diagnosis; however, its clinical translation has thus far been limited. This is in part due to an unstandardized and segmented sample preparation process...

Design Space Exploration of Hardware Spiking Neurons for Embedded Artificial Intelligence.

Neural networks : the official journal of the International Neural Network Society
Machine learning is yielding unprecedented interest in research and industry, due to recent success in many applied contexts such as image classification and object recognition. However, the deployment of these systems requires huge computing capabil...

Post-hoc modification of linear models: Combining machine learning with domain information to make solid inferences from noisy data.

NeuroImage
Linear machine learning models "learn" a data transformation by being exposed to examples of input with the desired output, forming the basis for a variety of powerful techniques for analyzing neuroimaging data. However, their ability to learn the de...

Development of a clinical support system for identifying social frailty.

International journal of medical informatics
OBJECTIVE: Recognizing frailty, also known as clinical geriatric syndrome in the elderly that is characterized by high vulnerability and low resilience, and its extensive influence in clinical practice is challenging. This study aims to develop a soc...

Deep learning-enabled system for rapid pneumothorax screening on chest CT.

European journal of radiology
PURPOSE: Prompt diagnosis and quantitation of pneumothorax impact decisions pertaining to patient management. The purpose of our study was to develop and evaluate the accuracy of a deep learning (DL)-based image classification program for detection o...

Deep learning for World Health Organization grades of pancreatic neuroendocrine tumors on contrast-enhanced magnetic resonance images: a preliminary study.

International journal of computer assisted radiology and surgery
PURPOSE: The World Health Organization (WHO) grading system of pancreatic neuroendocrine tumor (PNET) plays an important role in the clinical decision. The rarity of PNET often negatively affects the radiological application of deep learning algorith...

Automatic detection of contouring errors using convolutional neural networks.

Medical physics
PURPOSE: To develop a head and neck normal structures autocontouring tool that could be used to automatically detect the errors in autocontours from a clinically validated autocontouring tool.

Application of fast curvelet Tsallis entropy and kernel random vector functional link network for automated detection of multiclass brain abnormalities.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Binary classification of brain magnetic resonance (MR) images has made remarkable progress and many automated systems have been developed in the last decade. Multiclass classification of brain MR images is comparatively more challenging and has great...