A critique of pure learning and what artificial neural networks can learn from animal brains
Anthony M. Zador · Nature Communications · 2019 · Review
Full textCC BY
Artificial Intelligence
Filters3 filters applied
Year
Readable here
Study type
Licence
26 papersQuestions on this topic
Convolutional neural network for the diagnosis of early gastric cancer based on magnifying narrow band imaging
Lan Li, Yishu Chen, Zhe Shen et al. · Gastric Cancer · 2019
Full textCC BY
Artificial Intelligence in Lung Cancer Pathology Image Analysis
Shidan Wang, Donghan M. Yang, Ruichen Rong et al. · Cancers · 2019 · Review
Full textCC BY
Structured crowdsourcing enables convolutional segmentation of histology images
Mohamed Amgad, Habiba Elfandy, Hagar Hussein et al. · Bioinformatics · 2019
Full textCC BY
Estimating the success of re-identifications in incomplete datasets using generative models
Luc Rocher, Julien M. Hendrickx, Yves-Alexandre de Montjoye · Nature Communications · 2019
Full textCC BY
State-of-the-art in artificial neural network applications: A survey
Oludare Isaac Abiodun, Aman Jantan, Abiodun Esther Omolara et al. · Heliyon · 2018 · Review
Full textCC BY
Machine Learning Methods for Histopathological Image Analysis
Daisuke Komura, Shumpei Ishikawa · Computational and Structural Biotechnology Journal · 2018 · Review
Full textCC BY
Deep forest
Zhi-Hua Zhou, Ji Feng · National Science Review · 2018
Full textCC BY
Predictive representations can link model-based reinforcement learning to model-free mechanisms
Evan M. Russek, Ida Momennejad, Matthew M. Botvinick et al. · PLOS Computational Biology · 2017
Full textCC BY
An Approximation of the Error Backpropagation Algorithm in a Predictive Coding Network with Local Hebbian Synaptic Plasticity
James C. R. Whittington, Rafal Bogacz · Neural Computation · 2017
Abstract only
Thyroid Nodule Classification in Ultrasound Images by Fine-Tuning Deep Convolutional Neural Network
Jianning Chi, Ekta Walia, Paul Babyn et al. · Journal of Digital Imaging · 2017
Full textCC BY
Large scale tissue histopathology image classification, segmentation, and visualization via deep convolutional activation features
Yan Xu, Zhipeng Jia, Liang-Bo Wang et al. · BMC Bioinformatics · 2017
Full textCC BY
Neuromorphic photonic networks using silicon photonic weight banks
Alexander N. Tait, Thomas Ferreira de Lima, Ellen Zhou et al. · Scientific Reports · 2017
Abstract onlyCC BY
Systems pathology by multiplexed immunohistochemistry and whole-slide digital image analysis
Sami Blom, Lassi Paavolainen, Dmitrii Bychkov et al. · Scientific Reports · 2017
Full textCC BY
Classification of breast cancer histology images using Convolutional Neural Networks
Teresa Araújo, Guilherme Aresta, Eduardo Castro et al. · PLOS ONE · 2017
Full textCC BY
Ontobee: A linked ontology data server to support ontology term dereferencing, linkage, query and integration
Edison Ong, Zuoshuang Xiang, Bin Zhao et al. · Nucleic Acids Research · 2016
Full textCC BY
Deep biomarkers of human aging: Application of deep neural networks to biomarker development
Evgeny Putin, Polina Mamoshina, Alexander Aliper et al. · Aging · 2016
Full textCC BY
Interactive machine learning for health informatics: when do we need the human-in-the-loop?
Andreas Holzinger · Brain Informatics · 2016
Full textCC BY
Random synaptic feedback weights support error backpropagation for deep learning
Timothy P. Lillicrap, Daniel Cownden, Douglas B. Tweed et al. · Nature Communications · 2016
Full textCC BY
Discrimination of Breast Cancer with Microcalcifications on Mammography by Deep Learning
Jinhua Wang, Xi Yang, Hongmin Cai et al. · Scientific Reports · 2016
Full textCC BY