Search Results - "Deep Learning"

Sanger fra fortiden i en nåtidig krise: dybdelæring, resonans og motstand by Maria Jordet

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Performance of advanced machine learning algorithms overlogistic regression in predicting hospital readmissions: A meta-analysis by Ashna Talwar, Maria A. Lopez-Olivo, Yinan Huang, Lin Ying, Rajender R. Aparasu

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Radiogenomic association of deep MR imaging features with genomic profiles and clinical characteristics in breast cancer by Qian Liu, Pingzhao Hu

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IDENTIFIKASI PENYAKIT TANAMAN TOMAT MELALUI DAUN DENGAN METODE CONVOLUTIONAL NEURAL NETWORK ARSITEKTUR SQUEEZENET by Akbar Hidayatuloh, -

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Artificial Intelligence and Cognitive Science 30th Irish Conference, AICS 2022, Munster, Ireland, December 8-9, 2022, Revised Selected Papers /

Table of Contents: “…Machine Learning, Deep Learning and applications -- Responsible and Trustworthy Artificial Intelligence -- Natural Language Processing and Recommender Systems -- Knowledge Representation, reasoning, Optimisation and intelligent applications.…”
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Artificial Intelligence Technology by Huawei Technologies Co., Ltd

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Establishment of a novel tumor neoantigen prediction tool for personalized vaccine design by Kai Xin, Xiao Wei, Jie Shao, Fangjun Chen, Qin Liu, Baorui Liu

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CSM-Toxin: A Web-Server for Predicting Protein Toxicity by Vladimir Morozov, Carlos H. M. Rodrigues, David B. Ascher

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Monkeypox Global Research: A Comprehensive Analysis from Emergence to Present (1961-2023) for innovative prevention and control approaches by Nader Kameli, Abdullah Algaissi, Manal Mohamed Elhassan Taha, Edrous Alamer, Abdulaziz Alhazmi, Waleed Hakami, Badreldin S. Rahama, Anwar M. Hashem, Siddig Ibrahim Abdelwahab

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Exploring a Problem-Based Learning Approach in Pharmaceutics by Barbara McKenzie, Alyson Brown

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TIE-EEGNet: Temporal Information Enhanced EEGNet for Seizure Subtype Classification by Ruimin Peng, Changming Zhao, Jun Jiang, Guangtao Kuang, Yuqi Cui, Yifan Xu, Hao Du, Jianbo Shao, Dongrui Wu

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Identification of miRNA-Small Molecule Associations by Continuous Feature Representation Using Auto-Encoders by Ibrahim Abdelbaky, Hilal Tayara, Kil To Chong

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Artificial intelligence applications in pediatric oncology diagnosis by Yuhan Yang, Yimao Zhang, Yuan Li

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Uncovering the pharmacology of Ginkgo biloba folium in the cell-type-specific targets of Parkinson's disease by Yu-Chen Yan, Zhi-Heng Xu, Jian Wang, Wen-Bo Yu

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CCTCOVID: COVID-19 detection from chest X-ray images using Compact Convolutional Transformers by Abdolreza Marefat, Mahdieh Marefat, Javad Hassannataj Joloudari, Mohammad Ali Nematollahi, Reza Lashgari

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Proposing a Model for Detecting Intrusion Network Attacks Using Machine Learning Techniques by Teba Ali Jasem Ali, Muna Jawhar

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AI-Driven Stroke Rehabilitation Systems and Assessment: A Systematic Review by Sejuti Rahman, Sujan Sarker, A. K. M. Nadimul Haque, Monisha Mushtary Uttsha, Md Fokhrul Islam, Swakshar Deb

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Applications of artificial intelligence in dementia research by Kelvin K. F. Tsoi, Pingping Jia, N. Maritza Dowling, Jodi R. Titiner, Maude Wagner, Ana W. Capuano, Michael C. Donohue

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A Transformer-Based Prediction Method for Depth of Anesthesia During Target-Controlled Infusion of Propofol and Remifentanil by Yongkang He, Siyuan Peng, Mingjin Chen, Zhijing Yang, Yuanhui Chen

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Machine Learning for Brain Disorders

Table of Contents: “…A Non-Technical Introduction to Machine Learning -- Classic Machine Learning Methods -- Deep Learning: Basics and Convolutional Neural Networks (CNN) -- Recurrent Neural Networks (RNN) - Architectures, Training Tricks, and Introduction to Influential Research -- Generative Adversarial Networks and Other Generative Models -- Transformers and Visual Transformers -- Clinical Assessment of Brain Disorders -- Neuroimaging in Machine Learning for Brain Disorders -- Electroencephalography and Magnetoencephalography -- Working with Omics Data, An Interdisciplinary Challenge at the Crossroads of Biology and Computer Science -- Electronic Health Records as Source of Research Data -- Mobile Devices, Connected Objects, and Sensors -- Medical Image Segmentation using Deep Learning -- Image Registration: Fundamentals and Recent Advances Based on Deep Learning -- Computer-Aided Diagnosis and Prediction in Brain Disorders -- Subtyping Brain Diseases from Imaging Data -- Data-Driven Disease Progression Modelling -- Computational Pathology for Brain Disorders -- Integration of Multimodal Data -- Evaluating Machine Learning Models and their Diagnostic Value -- Reproducibility in Machine Learning for Medical Imaging -- Interpretability of Machine Learning Methods Applied to Neuroimaging -- A Regulatory Science Perspective on Performance Assessment of Machine Learning Algorithms in Imaging -- Main Existing Datasets for Open Brain Research on Humans -- Machine Learning for Alzheimer's Disease and Related Dementias -- Machine Learning for Parkinson's Disease and Related Disorders -- Machine Learning in Neuroimaging of Epilepsy -- Machine Learning in Multiple Sclerosis -- Machine Learning for Cerebrovascular Disorders -- The Role of Artificial Intelligence in Neuro-Oncology Imaging -- Machine Learning for Neurodevelopmental Disorders -- Machine Learning and BrainImaging for Psychiatric Disorders: New Perspectives.…”
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