AIMC Topic: Humans

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A decision support system based on support vector machine for diagnosis of periodontal disease.

BMC research notes
OBJECTIVE: Early diagnosis of many diseases is essential for their treatment. Furthermore, the existence of abundant and unknown variables makes more complicated decision making. For this reason, the diagnosis and classification of diseases using mac...

Deep learning-based BCI for gait decoding from EEG with LSTM recurrent neural network.

Journal of neural engineering
OBJECTIVE: Mobile Brain/Body Imaging (MoBI) frameworks allowed the research community to find evidence of cortical involvement at walking initiation and during locomotion. However, the decoding of gait patterns from brain signals remains an open chal...

A Monte Carlo based scatter removal method for non-isocentric cone-beam CT acquisitions using a deep convolutional autoencoder.

Physics in medicine and biology
The primary cone-beam computed tomography (CBCT) imaging beam scatters inside the patient and produces a contaminating photon fluence that is registered by the detector. Scattered photons cause artifacts in the image reconstruction, and are partially...

Home-Based Cognitively Assistive Robots: Maximizing Cognitive Functioning and Maintaining Independence in Older Adults Without Dementia.

Clinical interventions in aging
Promoting health and prolonging independence in the home is a priority for older adults, caregivers, clinicians, and society at large. Rapidly developing robotics technology provides a platform for interventions, with the fields of physically and soc...

Value of laboratory results in addition to vital signs in a machine learning algorithm to predict in-hospital cardiac arrest: A single-center retrospective cohort study.

PloS one
BACKGROUND: Although machine learning-based prediction models for in-hospital cardiac arrest (IHCA) have been widely investigated, it is unknown whether a model based on vital signs alone (Vitals-Only model) can perform similarly to a model that cons...

Evaluating body composition by combining quantitative spectral detector computed tomography and deep learning-based image segmentation.

European journal of radiology
PURPOSE: Aim of this study was to develop and evaluate a software toolkit, which allows for a fully automated body composition analysis in contrast enhanced abdominal computed tomography leveraging the strengths of both, quantitative information from...

[Artificial intelligence and its applications in medicine I: introductory background to AI and robotics].

Atencion primaria
Technology and medicine follow a parallel path during the last decades. Technological advances are changing the concept of health and health needs are influencing the development of technology. Artificial intelligence (AI) is made up of a series of s...

Identification of competing neural mechanisms underlying positive and negative perceptual hysteresis in the human visual system.

NeuroImage
Hysteresis is a well-known phenomenon in physics that relates changes in a system with its prior history. It is also part of human visual experience (perceptual hysteresis), and two different neural mechanisms might explain it: persistence (a cause o...

Towards explainable deep neural networks (xDNN).

Neural networks : the official journal of the International Neural Network Society
In this paper, we propose an elegant solution that is directly addressing the bottlenecks of the traditional deep learning approaches and offers an explainable internal architecture that can outperform the existing methods, requires very little compu...

Artificial intelligence in the IVF laboratory: overview through the application of different types of algorithms for the classification of reproductive data.

Journal of assisted reproduction and genetics
Over the past years, the assisted reproductive technologies (ARTs) have been accompanied by constant innovations. For instance, intracytoplasmic sperm injection (ICSI), time-lapse monitoring of the embryonic morphokinetics, and PGS are innovative tec...