AIMC Topic: Humans

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A 3D Deep Learning System for Detecting Referable Glaucoma Using Full OCT Macular Cube Scans.

Translational vision science & technology
PURPOSE: The purpose of this study was to develop a 3D deep learning system from spectral domain optical coherence tomography (SD-OCT) macular cubes to differentiate between referable and nonreferable cases for glaucoma applied to real-world datasets...

Methodological Challenges of Deep Learning in Optical Coherence Tomography for Retinal Diseases: A Review.

Translational vision science & technology
Artificial intelligence (AI)-based automated classification and segmentation of optical coherence tomography (OCT) features have become increasingly popular. However, its 3-dimensional volumetric nature has made developing an algorithm that generaliz...

Monitoring stance towards vaccination in twitter messages.

BMC medical informatics and decision making
BACKGROUND: We developed a system to automatically classify stance towards vaccination in Twitter messages, with a focus on messages with a negative stance. Such a system makes it possible to monitor the ongoing stream of messages on social media, of...

Identification of the best strategy to command variable stiffness using electromyographic signals.

Journal of neural engineering
OBJECTIVE: In the last decades, many EMG-controlled robotic devices were developed. Since stiffness control may be required to perform skillful interactions, different groups developed devices whose stiffness is real-time controlled based on EMG sign...

Mental state space visualization for interactive modeling of personalized BCI control strategies.

Journal of neural engineering
OBJECTIVE: Numerous studies in the area of BCI are focused on the search for a better experimental paradigm-a set of mental actions that a user can evoke consistently and a machine can discriminate reliably. Examples of such mental activities are mot...

Dynamic time warping-based transfer learning for improving common spatial patterns in brain-computer interface.

Journal of neural engineering
OBJECTIVE: Common spatial patterns (CSP) is a prominent feature extraction algorithm in motor imagery (MI)-based brain-computer interfaces (BCIs). However, CSP is computed using sample-based covariance-matrix estimation. Hence, its performance deteri...

Can exascale computing and explainable artificial intelligence applied to plant biology deliver on the United Nations sustainable development goals?

Current opinion in biotechnology
Human population growth and accelerated climate change necessitate agricultural improvements using designer crop ideotypes (idealized plants that can grow in niche environments). Diverse and highly skilled research groups must integrate efforts to br...

Deep Learning-driven research for drug discovery: Tackling Malaria.

PLoS computational biology
Malaria is an infectious disease that affects over 216 million people worldwide, killing over 445,000 patients annually. Due to the constant emergence of parasitic resistance to the current antimalarial drugs, the discovery of new drug candidates is ...

Detecting Congestive Heart Failure by Extracting Multimodal Features and Employing Machine Learning Techniques.

BioMed research international
The adaptability of heart to external and internal stimuli is reflected by the heart rate variability (HRV). Reduced HRV can be a predictor of negative cardiovascular outcomes. Based on the nonlinear, nonstationary, and highly complex dynamics of the...