AIMC Topic: Humans

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A primer on artificial intelligence and its application to endoscopy.

Gastrointestinal endoscopy
Artificial intelligence (AI) has emerged as a powerful and exciting new technology poised to impact many aspects of health care. In endoscopy, AI is now being used to detect and characterize benign and malignant GI lesions and assess malignant lesion...

Training memristor-based multilayer neuromorphic networks with SGD, momentum and adaptive learning rates.

Neural networks : the official journal of the International Neural Network Society
Neural networks implemented with traditional hardware face inherent limitation of memory latency. Specifically, the processing units like GPUs, FPGAs, and customized ASICs, must wait for inputs to read from memory and outputs to write back. This moti...

Automated classification of cells into multiple classes in epithelial tissue of oral squamous cell carcinoma using transfer learning and convolutional neural network.

Neural networks : the official journal of the International Neural Network Society
The analysis of tissue of a tumor in the oral cavity is essential for the pathologist to ascertain its grading. Recent studies using biopsy images reveal computer-aided diagnosis for oral sub-mucous fibrosis (OSF) carried out using machine learning a...

Design and control of an image-guided robot for spine surgery in a hybrid OR.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: Minimally invasive spine (MIS) fusion surgery requires image guidance and expert manual dexterity for a successful, efficient, and accurate pedicle screw placement. Operating room (OR)-integrated robotic solution can provide precise assis...

MRI radiomics-based machine-learning classification of bone chondrosarcoma.

European journal of radiology
PURPOSE: To evaluate the diagnostic performance of machine learning for discrimination between low-grade and high-grade cartilaginous bone tumors based on radiomic parameters extracted from unenhanced magnetic resonance imaging (MRI).

Time-resolved correspondences between deep neural network layers and EEG measurements in object processing.

Vision research
The ventral visual stream is known to be organized hierarchically, where early visual areas processing simplistic features feed into higher visual areas processing more complex features. Hierarchical convolutional neural networks (CNNs) were largely ...

Measurement and identification of mental workload during simulated computer tasks with multimodal methods and machine learning.

Ergonomics
This study attempted to multimodally measure mental workload and validate indicators for estimating mental workload. A simulated computer work composed of mental arithmetic tasks with different levels of difficulty was designed and used in the experi...

Machine learning techniques for computer-aided classification of active inflammatory sacroiliitis in magnetic resonance imaging.

Advances in rheumatology (London, England)
BACKGROUND: Currently, magnetic resonance imaging (MRI) is used to evaluate active inflammatory sacroiliitis related to axial spondyloarthritis (axSpA). The qualitative and semiquantitative diagnosis performed by expert radiologists and rheumatologis...

Generation and evaluation of synthetic patient data.

BMC medical research methodology
BACKGROUND: Machine learning (ML) has made a significant impact in medicine and cancer research; however, its impact in these areas has been undeniably slower and more limited than in other application domains. A major reason for this has been the la...