Results 21 to 30 of about 99,068 (260)
Tomography, 2023 Breast cancer remains the leading cause of cancer-related deaths in women worldwide. Current screening regimens and clinical breast cancer risk assessment models use risk factors such as demographics and patient history to guide policy and assess risk ...
Maham Siddique +4 more
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Deep Learning with Artificial Neural Networks
, 2021 The field of artificial intelligence (AI) continues to evolve rapidly, with deep learning and neural networks playing a central role in many of its most impressive breakthroughs. From image recognition to natural language processing and beyond, these technologies have re-shaped how machines learn from data and interact with the world.
openaire +3 more sources
Synaptic Plasticity Dynamics for Deep Continuous Local Learning (DECOLLE)
Frontiers in Neuroscience, 2020 A growing body of work underlines striking similarities between biological neural networks and recurrent, binary neural networks. A relatively smaller body of work, however, addresses the similarities between learning dynamics employed in deep artificial
Jacques Kaiser +3 more
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A Novel Deep Learning Approach With Data Augmentation to Classify Motor Imagery Signals
IEEE Access, 2019 Brain-computer interface provides a new communication bridge between the human mind and devices, depending largely on the accurate classification and identification of non-invasive EEG signals. Recently, the deep learning approaches have been widely used
Zhiwen Zhang +6 more
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Scaling tabular data of training datasets with neural networks
Вісник Харківського національного університету імені В.Н. Каразіна. Серія: Математичне моделювання, інформаційні технології, автоматизовані системи управління, 2023 The paper proposes a method of scaling the tabular data of the training dataset using neural networks, describes the architecture of such networks. Relevance.
Дмитро Узлов +3 more
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Deep learning in bladder cancer imaging: A review
Frontiers in Oncology, 2022 Deep learning (DL) is a rapidly developing field in machine learning (ML). The concept of deep learning originates from research on artificial neural networks and is an upgrade of traditional neural networks.
Mingyang Li +3 more
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Artificial intelligence used in genome analysis studies
The EuroBiotech Journal, 2018 Next Generation Sequencing (NGS) or deep sequencing technology enables parallel reading of multiple individual DNA fragments, thereby enabling the identification of millions of base pairs in several hours.
D’Agaro Edo
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Artificial intelligence in surgical pathology
Journal of Pathology of Nepal, 2019 Artificial intelligence (AI) is machine intelligence that mimics human cognitive function. It denotes the intelligence presented by some artificial entities including computers and robots.
Gopi Aryal
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Which Artificial Intelligence Algorithm Better Predicts the Chinese Stock Market?
IEEE Access, 2018 Unpredictable stock market factors make it difficult to predict stock index futures. Although efforts to develop an effective prediction method have a long history, recent developments in artificial intelligence and the use of artificial neural networks ...
Lin Chen +5 more
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Deep learning in Emergency Medicine: Recent contributions and methodological challenges
Emergency Care Journal, 2020 In the last few years, artificial intelligence (AI) technology has grown dramatically impacting several fields of human knowledge and medicine in particular.
Francesco Faita
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