AIMC Topic: Humans

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Artificial intelligence (AI) impacting diagnosis of glaucoma and understanding the regulatory aspects of AI-based software as medical device.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Glaucoma, the group of eye diseases is characterized by increased intraocular pressure, optic neuropathy and visual field defect patterns. Early and correct diagnosis of glaucoma can prevent irreversible vision loss and glaucomatous structural damage...

Digital Gaming Interventions in Psychiatry: Evidence, Applications and Challenges.

Psychiatry research
Human evolution has regularly intersected with technology. Digitalization of various services has brought a paradigm shift in consumerism. Treading this path, mental health practice has gradually moved to Digital Mental Health Interventions (DMHI), t...

Accelerating the identification of subtype selective inhibitors via Three-Dimensional Biologically Relevant Spectrum (BRS-3D): The monoamine oxidase subtypes as a case study.

Bioorganic chemistry
Subtype-selective drugs are of great therapeutic importance as they are expected to be more effective and with less side-effects. However, discovery of subtype selective inhibitors was hampered by the high similarity of the binding sites within subfa...

An easy-to-use deep-learning model for highly accurate diagnosis of Parkinson's disease using SPECT images.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Accurate diagnosis of Parkinson's Disease (PD) at its early stages remains a challenge for modern clinicians. In this study, we utilize a convolutional neural network (CNN) approach to address this problem. In particular, we develop a CNN-based netwo...

Facial Expression Recognition Using Frequency Neural Network.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Facial expression recognition has become a newly-emerging topic in recent decades, which has important value in the field of human-computer interaction. In this paper, we present a deep learning based approach, named frequency neural network (FreNet)...

Combining Recurrent Neural Networks and Adversarial Training for Human Motion Synthesis and Control.

IEEE transactions on visualization and computer graphics
This paper introduces a new generative deep learning network for human motion synthesis and control. Our key idea is to combine recurrent neural networks (RNNs) and adversarial training for human motion modeling. We first describe an efficient method...

Spatio-Temporal Manifold Learning for Human Motions via Long-Horizon Modeling.

IEEE transactions on visualization and computer graphics
Data-driven modeling of human motions is ubiquitous in computer graphics and computer vision applications, such as synthesizing realistic motions or recognizing actions. Recent research has shown that such problems can be approached by learning a nat...

Development challenges of high concentration monoclonal antibody formulations.

Drug discovery today. Technologies
High concentration monoclonal antibody drug products represent a special segment of biopharmaceuticals. In contrast to other monoclonal antibody products, high concentration monoclonal antibodies are injected subcutaneously helping increase patient c...

Noise robust automatic heartbeat classification system using support vector machine and conditional spectral moment.

Physical and engineering sciences in medicine
Heartbeat classification is central to the detection of the arrhythmia. For the effective heartbeat classification, the noise-robust features are very significant. In this work, we have proposed a noise-robust support vector machine (SVM) based heart...