Results 61 to 70 of about 99,068 (260)

Providing a Foresight Model for Selecting the Appropriate Breast Cancer Diagnosis Model [PDF]

مجله انفورماتیک سلامت و زیست پزشکی
Introduction: Selecting an appropriate model for breast cancer diagnosis is critical. Unsuitable models can compromise diagnostic accuracy, lead to incorrect outcomes, and impact clinical decision-making.
Abdolhossein Shakibaeinia, Mohsen Chagin, Amin Golabpour, Ahmad Khosravi   +3 more
doaj  

Leveraging chaotic transients in the training of artificial neural networks

Physical Review Research
Traditional algorithms to optimize artificial neural networks when confronted with a supervised learning task are usually exploitation-type relaxational dynamics such as gradient descent (GD).
Pedro Jiménez-González, Miguel C. Soriano, Lucas Lacasa   +2 more
doaj   +1 more source

Noise‐Limited Bit Precision in Ferroelectric Synaptic Transistors for High‐Resolution Neuromorphic Computing

Advanced Functional Materials, EarlyView.
Low‐frequency noise spectroscopy defines the resolvable conductance states of synaptic FeFETs by coupling read‐current fluctuation with usable dynamic range. The resulting noise‐limited bit precision establishes a universal, device‐agnostic reliability metric beyond the memory window, enabling quantitative benchmarking and rational design of high ...
Jaehong Park, Yeonseop Shin, Changhyeon Han, Sangwoo Kim, Eunchan Park, Youngchan Cho, Jaehong Min, Hyunjun Ahn, Jaekyoung Park, Cheol‐Woong Yang, Jangsaeng Kim, Daewoong Kwon, Wonjun Shin   +12 more
wiley   +1 more source

Artificial intelligence in industrial heat exchanger fouling prediction: A 20-year systematic review of AI, ML, and DL approaches

ICT Express
Fouling in heat exchangers (HXs) affects various industries by lowering efficiency and increasing costs. Traditional fouling-prediction models often do not reflect important mechanistic information and thus become very complex and less reliable.
Abdul Wahid Soomro, Miss Laiha Mat Kiah, Rafidah Md Noor, Salim Newaz Kazi, Kaleemullah Shaikh, Wajahat Ahmed Khan, Ihsan Ali   +6 more
doaj   +1 more source

Superintelligent Deep Learning Artificial Neural Networks

, 2019
Activation Functions are crucial parts of the Deep Learning Artificial Neural Networks. From the Biological point of view, a neuron is just a node with many inputs and one output. A neural network consists of many interconnected neurons. It is a “simple” device that receives data at the input and provides a response. The function of
openaire   +2 more sources

Intelligent Orthopedics: Machine Learning in Diagnosis of Bone Disease, Implants, and Bone Health Monitoring

Advanced Healthcare Materials, EarlyView.
Efficient recovery from traumatic or degenerative diseases is a great challenge, even after all the advancements in bone and cartilage regeneration. Machine learning (ML) algorithms have presented opportunities to enhance these aspects by accurately analyzing imaging data.
Maryam Kamaei, Hesam Mohammadi, Shamim Golafshan, Mojtaba Alehosseini, Mahsa Mohammadzadeh, Atefeh Golshirazi, Nasim Golafshan, Tatiane Eufrásio‐da‐Silva, Alireza Dolatshahi‐Pirouz, Gorka Orive   +9 more
wiley   +1 more source

A CRITICAL REVIEW OF DEEP LEARNING APPLICATIONS, CHALLENGES, AND FUTURE DIRECTIONS IN STRUCTURAL ENGINEERING

International Journal for Computational Civil and Structural Engineering
Deep learning (DL), a major part of artificial intelligence (AI) is considered as a transformational technology in different areas of science, such as structural engineering.
Manaf Raid Salman, Marwan Al-Shaikhli, Hasan Ali Abbas, Hussain Hamed Ahmad, Sakhiah Abdul Kudus   +4 more
doaj   +1 more source

Nanomaterial Strategies for Pulmonary Delivery of Immunotherapeutics in Lung Cancer Treatment

Advanced Healthcare Materials, EarlyView.
Inhalable immunotherapeutic nanomedicines enable organ‐selective immune modulation by overcoming pulmonary delivery barriers and concentrating therapy within lung tumors. This Review defines how nanomaterial properties govern airway deposition, retention, cellular partitioning, and immune activation across vaccines, checkpoint blockade, STING agonists,
Han Zhang, Wei Tang
wiley   +1 more source

Research Based on Stock Predicting Model of Neural Networks Ensemble Learning

MATEC Web of Conferences, 2018
Financial time series is always one of the focus of financial market analysis and research. In recent years, with the rapid development of artificial intelligence, machine learning and financial market are more and more closely linked.
Xie Qi, Cheng Gengguo, Xu Xu, Zhao Zixuan   +3 more
doaj   +1 more source

Toward Scalable, Efficient, and Accurate Deep Spiking Neural Networks With Backward Residual Connections, Stochastic Softmax, and Hybridization

Frontiers in Neuroscience, 2020
Spiking Neural Networks (SNNs) may offer an energy-efficient alternative for implementing deep learning applications. In recent years, there have been several proposals focused on supervised (conversion, spike-based gradient descent) and unsupervised ...
Priyadarshini Panda, Sai Aparna Aketi, Kaushik Roy   +2 more
doaj   +1 more source