AIMC Topic: Algorithms

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Convolutional neural networks and genetic algorithm for visual imagery classification.

Physical and engineering sciences in medicine
Brain-Computer Interface (BCI) systems establish a channel for direct communication between the brain and the outside world without having to use the peripheral nervous system. While most BCI systems use evoked potentials and motor imagery, in the pr...

Deep Reinforcement Learning and Its Neuroscientific Implications.

Neuron
The emergence of powerful artificial intelligence (AI) is defining new research directions in neuroscience. To date, this research has focused largely on deep neural networks trained using supervised learning in tasks such as image classification. Ho...

An Efficient Segmentation and Classification System in Medical Images Using Intuitionist Possibilistic Fuzzy C-Mean Clustering and Fuzzy SVM Algorithm.

Sensors (Basel, Switzerland)
The herpesvirus, polyomavirus, papillomavirus, and retrovirus families are associated with breast cancer. More effort is needed to assess the role of these viruses in the detection and diagnosis of breast cancer cases in women. The aim of this paper ...

Deep Physiological Model for Blood Glucose Prediction in T1DM Patients.

Sensors (Basel, Switzerland)
Accurate estimations for the near future levels of blood glucose are crucial for Type 1 Diabetes Mellitus (T1DM) patients in order to be able to react on time and avoid hypo and hyper-glycemic episodes. Accurate predictions for blood glucose are the ...

An Intelligent Opportunistic Routing Algorithm for Wireless Sensor Networks and Its Application Towards e-Healthcare.

Sensors (Basel, Switzerland)
The lifetime of a node in wireless sensor networks (WSN) is directly responsible for the longevity of the wireless network. The routing of packets is the most energy-consuming activity for a sensor node. Thus, finding an energy-efficient routing stra...

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...

Deep clustering with a Dynamic Autoencoder: From reconstruction towards centroids construction.

Neural networks : the official journal of the International Neural Network Society
In unsupervised learning, there is no apparent straightforward cost function that can capture the significant factors of variations and similarities. Since natural systems have smooth dynamics, an opportunity is lost if an unsupervised objective func...

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...

CAB U-Net: An end-to-end category attention boosting algorithm for segmentation.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
With the development of machine learning and artificial intelligence, many convolutional neural networks (CNNs) based segmentation methods have been proposed for 3D cardiac segmentation. In this paper, we propose the category attention boosting (CAB)...