Rezultati pretrage - "neural network"

Determining the Reliability of Software Electronic Engineering Tools in the Control of Vestibular Disorders in Inclusive Physical Education of Students od Oksana Blavt, Gennadii Iedynak, Lesia Galamanzhuk, Tetiana Helzhynska, Yuliya Nosko, Yurii Kachurak, Olena Voloshyn, Stepan Shabaga

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Crowdsourcing Knowledge Production of COVID-19 Information on Japanese Wikipedia in the Face of Uncertainty: Empirical Analysis od Kunhao Yang, Mikihito Tanaka

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Serological Biomarker-Based Machine Learning Models for Predicting the Relapse of Ulcerative Colitis od Pang W, Zhang B, Jin L, Yao Y, Han Q, Zheng X

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Bi-stream CNN Down Syndrome screening model based on genotyping array od Bing Feng, William Hoskins, Yan Zhang, Zibo Meng, David C. Samuels, Jiandong Wang, Ruofan Xia, Chao Liu, Jijun Tang, Yan Guo

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Estimating mandibular growth stage based on cervical vertebral maturation in lateral cephalometric radiographs using artificial intelligence od Sajjad Alipour Shoari, Seyed Vahid Sadrolashrafi, Aydin Sohrabi, Reza Afrouzian, Pooya Ebrahimi, Maryam Kouhsoltani, Minou Kouh Soltani

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AI-based diagnosis in mandibulofacial dysostosis with microcephaly using external ear shapes od Quentin Hennocq, Quentin Hennocq, Quentin Hennocq, Thomas Bongibault, Thomas Bongibault, Sandrine Marlin, Sandrine Marlin, Jeanne Amiel, Jeanne Amiel, Tania Attie-Bitach, Tania Attie-Bitach, Geneviève Baujat, Geneviève Baujat, Lucile Boutaud, Georges Carpentier, Pierre Corre, Pierre Corre, Françoise Denoyelle, François Djate Delbrah, Maxime Douillet, Eva Galliani, Wuttichart Kamolvisit, Wuttichart Kamolvisit, Stanislas Lyonnet, Stanislas Lyonnet, Dan Milea, Véronique Pingault, Véronique Pingault, Thantrira Porntaveetus, Thantrira Porntaveetus, Sandrine Touzet-Roumazeille, Marjolaine Willems, Arnaud Picard, Marlène Rio, Marlène Rio, Nicolas Garcelon, Roman H. Khonsari, Roman H. Khonsari, Roman H. Khonsari

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Adverse drug reaction signals mining comparison of amiodarone and dronedarone: a pharmacovigilance study based on FAERS od Ye Xu, Bin Zhao, Liqun He

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استخدام الشبكات العصبونية في بناء نظام كشف تسلل اعتماداً على مجموعة بيانات قياسية (KDD99) od حسن الأحمد, رنا ابراهيم

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Feasibility and basic acoustic characteristics of intelligent long-term bowel sound analysis in term neonates od Ping Zhou, Meiling Lu, Ping Chen, Danlei Wang, Zhenchao Jin, Lian Zhang

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EARN: an ensemble machine learning algorithm to predict driver genes in metastatic breast cancer od Leila Mirsadeghi, Reza Haji Hosseini, Ali Mohammad Banaei-Moghaddam, Kaveh Kavousi

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Potential adverse events associated with sphingosine-1-phosphate (S1P) receptor modulators in patients with multiple sclerosis: an analysis of the FDA adverse event reporting syste... od Xiping Yang, Yan Yan, Suyao Liu, Zhiqing Wang, Xia Feng

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Automated quantitative analysis of Ki-67 staining and HE images recognition and registration based on whole tissue sections in breast carcinoma od Min Feng, Yang Deng, Libo Yang, Qiuyang Jing, Zhang Zhang, Lian Xu, Xiaoxia Wei, Yanyan Zhou, Diwei Wu, Fei Xiang, Yizhe Wang, Ji Bao, Hong Bu

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PENGENALAN TULISAN AKSARA SUNDA OFFLINE DENGAN JARINGAN SYARAF TIRUAN BACKPROPAGATION od Dea rokhmatun Iradewa, -

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Machine Learning for Brain Disorders

Sadržaj: “…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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Update and Application of a Deep Learning Model for the Prediction of Interactions between Drugs Used by Patients with Multiple Sclerosis od Michael Hecker, Niklas Frahm, Uwe Klaus Zettl

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Association of thrombocytopenia with immune checkpoint inhibitors: a large-scale pharmacovigilance analysis based on the data from FDA adverse event reporting system database od Geliang Liu, Geliang Liu, Geliang Liu, Shuxian Zhang, Shuxian Zhang, Zhuang Mo, Zhuang Mo, Tai Huang, Tai Huang, Qi Yu, Qi Yu, Xuechun Lu, Xuechun Lu, Xuechun Lu, Peifeng He, Peifeng He

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A Smartphone-Based Decision Support Tool for Predicting Patients at Risk of Chemotherapy-Induced Nausea and Vomiting: Retrospective Study on App Development Using Decision Tree Ind... od Abu Saleh Mohammad Mosa, Md Kamruz Zaman Rana, Humayera Islam, A K M Mosharraf Hossain, Illhoi Yoo

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Development and Validation of Unplanned Extubation Prediction Models Using Intensive Care Unit Data: Retrospective, Comparative, Machine Learning Study od Sujeong Hur, Ji Young Min, Junsang Yoo, Kyunga Kim, Chi Ryang Chung, Patricia C Dykes, Won Chul Cha

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Acoustic Analysis of Speech for Screening for Suicide Risk: Machine Learning Classifiers for Between- and Within-Person Evaluation of Suicidality od Sooyeon Min, Daun Shin, Sang Jin Rhee, C Hyung Keun Park, Jeong Hun Yang, Yoojin Song, Min Ji Kim, Kyungdo Kim, Won Ik Cho, Oh Chul Kwon, Yong Min Ahn, Hyunju Lee

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Developing an Automatic System for Classifying Chatter About Health Services on Twitter: Case Study for Medicaid od Yang, Yuan-Chi, Al-Garadi, Mohammed Ali, Bremer, Whitney, Zhu, Jane M, Grande, David, Sarker, Abeed

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