AIMC Topic: Humans

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Clinical data classification using an enhanced SMOTE and chaotic evolutionary feature selection.

Computers in biology and medicine
Class imbalance and the presence of irrelevant or redundant features in training data can pose serious challenges to the development of a classification framework. This paper proposes a framework for developing a Clinical Decision Support System (CDS...

Reverse-Engineering Neural Networks to Characterize Their Cost Functions.

Neural computation
This letter considers a class of biologically plausible cost functions for neural networks, where the same cost function is minimized by both neural activity and plasticity. We show that such cost functions can be cast as a variational bound on model...

Artificial intelligence in cardiac radiology.

La Radiologia medica
Artificial intelligence (AI) is entering the clinical arena, and in the early stage, its implementation will be focused on the automatization tasks, improving diagnostic accuracy and reducing reading time. Many studies investigate the potential role ...

[Acceptance of assistive robots in the field of nursing and healthcare : Representative data show a clear picture for Germany].

Zeitschrift fur Gerontologie und Geriatrie
In view of the ageing society and the high costs of support and care in private households, the question arises as to what role assistive robots can play. This article focuses on the extent to which robots in nursing are accepted by the adult populat...

Electroencephalography Might Improve Diagnosis of Acute Stroke and Large Vessel Occlusion.

Stroke
BACKGROUND AND PURPOSE: Clinical methods have incomplete diagnostic value for early diagnosis of acute stroke and large vessel occlusion (LVO). Electroencephalography is rapidly sensitive to brain ischemia. This study examined the diagnostic utility ...

Learning probabilistic neural representations with randomly connected circuits.

Proceedings of the National Academy of Sciences of the United States of America
The brain represents and reasons probabilistically about complex stimuli and motor actions using a noisy, spike-based neural code. A key building block for such neural computations, as well as the basis for supervised and unsupervised learning, is th...

Heartbeat Detection by Laser Doppler Vibrometry and Machine Learning.

Sensors (Basel, Switzerland)
Heartbeat detection is a crucial step in several clinical fields. Laser Doppler Vibrometer (LDV) is a promising non-contact measurement for heartbeat detection. The aim of this work is to assess whether machine learning can be used for detecting hea...

Research on a Dynamic Algorithm for Cow Weighing Based on an SVM and Empirical Wavelet Transform.

Sensors (Basel, Switzerland)
Weight is an important indicator of the growth and development of dairy cows. The traditional static weighing methods require considerable human and financial resources, and the existing dynamic weighing algorithms do not consider the influence of th...

An Artificial Neural Network Model for Assessing Frailty-Associated Factors in the Thai Population.

International journal of environmental research and public health
Frailty, one of the major public health problems in the elderly, can result from multiple etiologic factors including biological and physical changes in the body which contribute to the reduction in the function of multiple bodily systems. A diagnosi...