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Paper Citation Record · LEDGER

DeepHealth: Review and challenges of artificial intelligence in health informatics

As of 16 August 2026, this Paper Citation Record lists 100 of 300 outbound references and 0 inbound Pith citation observations for arXiv:1909.00384.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
1909.00384 v2

Coverage vector

measured 100 of 300 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T05:56:20.274827Z

measured 100 of 100 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

100 of 300 outbound references displayed

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  • verified fuzzy0
  • unresolved100
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  • malformed identifier0
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External citation measurements

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Outbound references

Observation 43ced669-7516-4d6f-a412-af1c5d22aef6 · outbound

This paper cites Deep learning for healthcare: review, opportunities and challenges.

DeepHealth: Review and challenges of artificial intelligence in health informatics Deep learning for healthcare: review, opportunities and challenges

Reference 1

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Observation 1ae7692b-0428-4b2a-b283-3cef572c2996 · outbound

This paper cites Deep learning for health informatics.

DeepHealth: Review and challenges of artificial intelligence in health informatics Deep learning for health informatics

Reference 2

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Observation 42a014b4-6559-466f-b861-62fff11f00ab · outbound

This paper cites A survey on deep learning in medical image analysis.

DeepHealth: Review and challenges of artificial intelligence in health informatics A survey on deep learning in medical image analysis

Reference 3

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Observation 1682c0ec-c6d2-4941-a570-510ff77dda85 · outbound

This paper cites Biomarker tests for molecularly targeted therapies–the key to unlocking precision medicine.

DeepHealth: Review and challenges of artificial intelligence in health informatics Biomarker tests for molecularly targeted therapies–the key to unlocking precision medicine

Reference 4

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Observation 2fefb1ed-4a43-457d-9377-e36542a4a82c · outbound

This paper cites A new initiative on precision medicine.

DeepHealth: Review and challenges of artificial intelligence in health informatics A new initiative on precision medicine

Reference 5

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Observation 685d89b7-035e-46d9-acbf-170f75c94867 · outbound

This paper cites Shickel, P.

DeepHealth: Review and challenges of artificial intelligence in health informatics Shickel, P

Reference 6

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Observation 9e550fe7-1047-489b-879c-0b28de4e2634 · outbound

This paper cites Deep learning for computational biology.

DeepHealth: Review and challenges of artificial intelligence in health informatics Deep learning for computational biology

Reference 7

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Observation 545f6729-0f25-470f-8334-fcbc38ce793e · outbound

This paper cites A guide to deep learning in healthcare.

DeepHealth: Review and challenges of artificial intelligence in health informatics A guide to deep learning in healthcare

Reference 8

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Observation b4c1d5d7-e2ec-497c-94e8-6f78e923fb08 · outbound

This paper cites A systematic literature review of machine learning in online personal health data.

DeepHealth: Review and challenges of artificial intelligence in health informatics A systematic literature review of machine learning in online personal health data

Reference 9

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Observation e70c5011-c0e3-464e-b864-2c8d07f11178 · outbound

This paper cites Deep Reinforcement Learning for Clinical Decision Support: A Brief Survey.

DeepHealth: Review and challenges of artificial intelligence in health informatics Deep Reinforcement Learning for Clinical Decision Support: A Brief Survey

Reference 10

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Observation fcb5a7ff-7a9d-43ec-8a26-5cebe5bbaa3e · outbound

This paper cites Deep learning for healthcare biometrics.

DeepHealth: Review and challenges of artificial intelligence in health informatics Deep learning for healthcare biometrics

Reference 11

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Observation 823b459d-a8cc-442e-b13b-45b990e22d38 · outbound

This paper cites Deep learning trends for focal brain pathology segmentation in mri.

DeepHealth: Review and challenges of artificial intelligence in health informatics Deep learning trends for focal brain pathology segmentation in mri

Reference 12

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Observation e6e639a2-c5c2-4d07-ad74-d78eba9bfef9 · outbound

This paper cites Big data application in biomedical research and health care: a literature review.

DeepHealth: Review and challenges of artificial intelligence in health informatics Big data application in biomedical research and health care: a literature review

Reference 13

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Observation fc0282b8-1f50-4b71-b0fe-0e88f8cbd1cf · outbound

This paper cites Biomedical informatics and machine learning for clinical genomics.

DeepHealth: Review and challenges of artificial intelligence in health informatics Biomedical informatics and machine learning for clinical genomics

Reference 14

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Observation 8fa87e55-a559-4c59-8c3e-58089339a067 · outbound

This paper cites Deep learning in drug discovery.

DeepHealth: Review and challenges of artificial intelligence in health informatics Deep learning in drug discovery

Reference 15

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Observation 0283730c-2e2e-410d-8c53-120ada786539 · outbound

This paper cites Deep learning: new computational modelling techniques for genomics.

DeepHealth: Review and challenges of artificial intelligence in health informatics Deep learning: new computational modelling techniques for genomics

Reference 16

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Observation bf698910-bf79-4a6d-9366-208c0217453a · outbound

This paper cites Deep artificial neural networks and neuromorphic chips for big data analysis: pharmaceutical and bioinformatics applications.

DeepHealth: Review and challenges of artificial intelligence in health informatics Deep artificial neural networks and neuromorphic chips for big data analysis: pharmaceutical and bioinformatics applications

Reference 17

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Observation 7e1084dc-a596-4c1f-8969-a176a2e30678 · outbound

This paper cites A review and assessment framework for mobile-based emergency intervention apps.

DeepHealth: Review and challenges of artificial intelligence in health informatics A review and assessment framework for mobile-based emergency intervention apps

Reference 18

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Observation d124575b-aac5-42c7-b630-d4f1b0e9b658 · outbound

This paper cites A review of wearable sensors and systems with application in rehabilitation.

DeepHealth: Review and challenges of artificial intelligence in health informatics A review of wearable sensors and systems with application in rehabilitation

Reference 19

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Observation 0016c407-7c16-4e6f-936b-3502ee13277c · outbound

This paper cites Critical care, critical data.Biomedical Engineering and Computational Biology, 10:1179597219856564, 2019.

DeepHealth: Review and challenges of artificial intelligence in health informatics Critical care, critical data.Biomedical Engineering and Computational Biology, 10:1179597219856564, 2019

Reference 20

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Observation cdbcd74b-b159-417e-87ad-6f5b149d1392 · outbound

This paper cites Deep learning in neural networks: An overview.

DeepHealth: Review and challenges of artificial intelligence in health informatics Deep learning in neural networks: An overview

Reference 21

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Observation 3a1fe5d7-30d6-4a37-86f2-accd9f1b4000 · outbound

This paper cites Dropout: a simple way to prevent neural networks from overfitting.

DeepHealth: Review and challenges of artificial intelligence in health informatics Dropout: a simple way to prevent neural networks from overfitting

Reference 22

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Observation 15b7447e-a1de-43f0-b8af-ae7aa91193fe · outbound

This paper cites Deep learning.

DeepHealth: Review and challenges of artificial intelligence in health informatics Deep learning

Reference 23

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Observation 52355d7b-0d90-40cc-858b-79f2e4b21966 · outbound

This paper cites 3d deep learning for multi-modal imaging-guided survival time prediction of brain tumor patients.

DeepHealth: Review and challenges of artificial intelligence in health informatics 3d deep learning for multi-modal imaging-guided survival time prediction of brain tumor patients

Reference 24

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Observation e067b6df-452b-49f8-ad0a-b5d35a790bd8 · outbound

This paper cites Multimodal deep learning for cervical dysplasia diagnosis.

DeepHealth: Review and challenges of artificial intelligence in health informatics Multimodal deep learning for cervical dysplasia diagnosis

Reference 25

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Observation ad25dd9d-e7f3-4de0-a4bb-20c2b0e8c560 · outbound

This paper cites Unsupervised transfer learning via multi-scale convolutional sparse coding for biomedical applications.

DeepHealth: Review and challenges of artificial intelligence in health informatics Unsupervised transfer learning via multi-scale convolutional sparse coding for biomedical applications

Reference 26

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Observation eb34a2b8-48d1-4d54-b2f0-4a69a0122406 · outbound

This paper cites Mass detection in digital breast tomosynthesis: Deep convolutional neural network with transfer learning from mammography.

DeepHealth: Review and challenges of artificial intelligence in health informatics Mass detection in digital breast tomosynthesis: Deep convolutional neural network with transfer learning from mammography

Reference 27

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Observation 3a7d497b-8887-4e8e-97e7-78474acaf53a · outbound

This paper cites Multi-instance deep learning: Discover discriminative local anatomies for bodypart recognition.

DeepHealth: Review and challenges of artificial intelligence in health informatics Multi-instance deep learning: Discover discriminative local anatomies for bodypart recognition

Reference 28

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Observation d36c18bf-df12-4b04-a66e-21d4b41bb921 · outbound

This paper cites Machine learning in genomic medicine: a review of computational problems and data sets.

DeepHealth: Review and challenges of artificial intelligence in health informatics Machine learning in genomic medicine: a review of computational problems and data sets

Reference 29

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Observation 9940725a-fcd9-46cd-b99a-ea87da46b9df · outbound

This paper cites The human splicing code reveals new insights into the genetic determinants of disease.

DeepHealth: Review and challenges of artificial intelligence in health informatics The human splicing code reveals new insights into the genetic determinants of disease

Reference 30

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Observation c56966e0-098c-41e6-8790-f938c332dd3b · outbound

This paper cites Predicting the sequence specificities of dna-and rna-binding proteins by deep learning.

DeepHealth: Review and challenges of artificial intelligence in health informatics Predicting the sequence specificities of dna-and rna-binding proteins by deep learning

Reference 31

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Observation d5d872d5-016a-4709-a5a5-454e07789b01 · outbound

This paper cites Accurate prediction of single-cell dna methylation states using deep learning.

DeepHealth: Review and challenges of artificial intelligence in health informatics Accurate prediction of single-cell dna methylation states using deep learning

Reference 32

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Observation 4b8942bb-e6b7-452c-ad6a-0b1747d98820 · outbound

This paper cites A clinically applicable approach to continuous prediction of future acute kidney injury.

DeepHealth: Review and challenges of artificial intelligence in health informatics A clinically applicable approach to continuous prediction of future acute kidney injury

Reference 33

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Observation 6e746111-afba-46b7-978c-668a4450c08c · outbound

This paper cites Davis, Thomas A.

DeepHealth: Review and challenges of artificial intelligence in health informatics Davis, Thomas A

Reference 34

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Observation 170cb205-7660-42da-ad88-05ce98a1cd48 · outbound

This paper cites Seymour, Jason N.

DeepHealth: Review and challenges of artificial intelligence in health informatics Seymour, Jason N

Reference 35

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Observation 348f9f11-9ca6-4f06-a3f5-4ed5830f4ff6 · outbound

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DeepHealth: Review and challenges of artificial intelligence in health informatics Knaus and Richard D

Reference 36

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Observation 1143dee5-b085-42ca-9b9d-9b28f10c6a93 · outbound

This paper cites Improving outcomes in patients with acute kidney injury: the impact of hospital based automated aki alerts.

DeepHealth: Review and challenges of artificial intelligence in health informatics Improving outcomes in patients with acute kidney injury: the impact of hospital based automated aki alerts

Reference 37

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DeepHealth: Review and challenges of artificial intelligence in health informatics Unresolved cited work

Reference 38

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Observation e3a9411f-b615-4d51-8f3f-7fb85510c25a · outbound

This paper cites Nephrotoxicities.

DeepHealth: Review and challenges of artificial intelligence in health informatics Nephrotoxicities

Reference 39

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Observation b0f052a3-32a4-4dbd-be38-8079ad7b8ad6 · outbound

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DeepHealth: Review and challenges of artificial intelligence in health informatics Review of vancomycin-induced renal toxicity: an update

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Observation 8bffd005-502c-4550-8190-3f035c1042c9 · outbound

This paper cites Supervised reinforcement learning with recurrent neural network for dynamic treatment recommendation.

DeepHealth: Review and challenges of artificial intelligence in health informatics Supervised reinforcement learning with recurrent neural network for dynamic treatment recommendation

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Observation 242a6296-c039-4018-b7b7-09e46c55af3e · outbound

This paper cites A clinically applicable approach to continuous prediction of future acute kidney injury.

DeepHealth: Review and challenges of artificial intelligence in health informatics A clinically applicable approach to continuous prediction of future acute kidney injury

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Observation 4ef4a6be-9243-46a9-8e3d-b5cbf59797d0 · outbound

This paper cites General practitioner-hospital commu- nications: A review of discharge summaries.

DeepHealth: Review and challenges of artificial intelligence in health informatics General practitioner-hospital commu- nications: A review of discharge summaries

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Observation 70d77db2-e43b-4d9f-a75e-db2586e68143 · outbound

This paper cites Biometric and mobile gait analysis for early diagnosis and therapy monitoring in parkinson’s disease.

DeepHealth: Review and challenges of artificial intelligence in health informatics Biometric and mobile gait analysis for early diagnosis and therapy monitoring in parkinson’s disease

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Observation 8b41e991-7195-4219-a40a-385d8af27e3e · outbound

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DeepHealth: Review and challenges of artificial intelligence in health informatics An adaptive deep learning approach for ppg-based identification

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Observation 8644e45c-1ff5-49e7-986f-aa8cfa687829 · outbound

This paper cites Decoding eeg and lfp signals using deep learning: heading truenorth.

DeepHealth: Review and challenges of artificial intelligence in health informatics Decoding eeg and lfp signals using deep learning: heading truenorth

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Observation ec5be85a-8414-48d6-af90-0870e83c56b4 · outbound

This paper cites Improving tuberculosis diagnostics using deep learning and mobile health technologies among resource-poor and marginalized communities.

DeepHealth: Review and challenges of artificial intelligence in health informatics Improving tuberculosis diagnostics using deep learning and mobile health technologies among resource-poor and marginalized communities

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Observation 3bba2afe-513b-42e9-91f1-b6e456a4d1f6 · outbound

This paper cites Social restricted boltzmann machine: Human behavior prediction in health social networks.

DeepHealth: Review and challenges of artificial intelligence in health informatics Social restricted boltzmann machine: Human behavior prediction in health social networks

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Observation 0b6e4abc-c9e7-45d2-8dce-a26597a89987 · outbound

This paper cites Social media image analysis for public health.

DeepHealth: Review and challenges of artificial intelligence in health informatics Social media image analysis for public health

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Observation 7a49a2ed-69da-4f66-adda-be2ff6a3950a · outbound

This paper cites On the ground validation of online diagnosis with twitter and medical records.

DeepHealth: Review and challenges of artificial intelligence in health informatics On the ground validation of online diagnosis with twitter and medical records

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Observation 0dcb298f-f088-4a46-9761-69a12a469ad8 · outbound

This paper cites An ensemble heterogeneous classification methodology for discovering health-related knowledge in social media messages.

DeepHealth: Review and challenges of artificial intelligence in health informatics An ensemble heterogeneous classification methodology for discovering health-related knowledge in social media messages

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Observation ce1d3afb-3de9-458b-a1f7-4b6b2a3dafc0 · outbound

This paper cites # hayfever; a longitudinal study into hay fever related tweets in the uk.

DeepHealth: Review and challenges of artificial intelligence in health informatics # hayfever; a longitudinal study into hay fever related tweets in the uk

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Observation ab08595c-4524-4c6a-a5b7-21c2b9def3f7 · outbound

This paper cites A machine learning approach to classification of drug reviews in russian.

DeepHealth: Review and challenges of artificial intelligence in health informatics A machine learning approach to classification of drug reviews in russian

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Observation de4c88b5-befc-482c-8ca4-6e1603ac6aac · outbound

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DeepHealth: Review and challenges of artificial intelligence in health informatics Predicting infectious disease using deep learning and big data

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This paper cites Uses of electronic health records for public health surveillance to advance public health.

DeepHealth: Review and challenges of artificial intelligence in health informatics Uses of electronic health records for public health surveillance to advance public health

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Observation 238f9683-4a67-4057-85a3-a802a681c144 · outbound

This paper cites Adoption of electronic health record systems among us non-federal acute care hospitals: 2008-2015.

DeepHealth: Review and challenges of artificial intelligence in health informatics Adoption of electronic health record systems among us non-federal acute care hospitals: 2008-2015

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Observation 6c31b360-771f-40d9-8a8f-c71c993c4181 · outbound

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DeepHealth: Review and challenges of artificial intelligence in health informatics Support vector machine

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DeepHealth: Review and challenges of artificial intelligence in health informatics Support vector machine soft margin classifiers: error analysis

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Observation c52edd38-1846-460c-9ece-01d5644e05e7 · outbound

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DeepHealth: Review and challenges of artificial intelligence in health informatics Support vector machines

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DeepHealth: Review and challenges of artificial intelligence in health informatics Multilinear operators for higher-order decompositions

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Observation e124aa75-1e9a-4f94-9ab9-605f2a068282 · outbound

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DeepHealth: Review and challenges of artificial intelligence in health informatics Word2vec — Wikipedia, the free encyclopedia

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DeepHealth: Review and challenges of artificial intelligence in health informatics Efficient Estimation of Word Representations in Vector Space

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DeepHealth: Review and challenges of artificial intelligence in health informatics Learning representations by back-propagating errors

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Observation 4e1e0474-5bfe-4f4e-b2c0-fb0961e32b41 · outbound

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DeepHealth: Review and challenges of artificial intelligence in health informatics Gradient-based learning applied to document recognition

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Observation 1eee6790-f33d-47a6-ae02-931245c33f66 · outbound

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DeepHealth: Review and challenges of artificial intelligence in health informatics Imagenet classification with deep convolutional neural networks

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Observation 97564f90-7c34-47b9-95fc-a0f82a6de05b · outbound

This paper cites Receptive fields, binocular interaction and functional architecture in the cat’s visual cortex.The Journal of physiology, 160(1):106–154, 1962.

DeepHealth: Review and challenges of artificial intelligence in health informatics Receptive fields, binocular interaction and functional architecture in the cat’s visual cortex.The Journal of physiology, 160(1):106–154, 1962

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DeepHealth: Review and challenges of artificial intelligence in health informatics 3d convolutional neural networks for human action recognition

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Observation 139f2b46-4a1b-492e-b7c6-db3baf26f7dd · outbound

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DeepHealth: Review and challenges of artificial intelligence in health informatics A learning algorithm for continually running fully recurrent neural networks

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Observation 86eb8e54-c186-460d-be1d-d3c19128ea59 · outbound

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DeepHealth: Review and challenges of artificial intelligence in health informatics Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation

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Observation dcab98f1-b12a-403a-8838-c5be2384b37a · outbound

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DeepHealth: Review and challenges of artificial intelligence in health informatics Lstm: A search space odyssey

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DeepHealth: Review and challenges of artificial intelligence in health informatics Natural Language Processing (almost) from Scratch

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Observation 649efd18-44c3-4ef5-96c6-887db3cca36d · outbound

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DeepHealth: Review and challenges of artificial intelligence in health informatics Learning long-term dependencies with gradient descent is difficult

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Observation 2a47d4f1-64eb-469c-b37c-4dfbce80d08b · outbound

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DeepHealth: Review and challenges of artificial intelligence in health informatics Long short-term memory

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DeepHealth: Review and challenges of artificial intelligence in health informatics Reducing the dimensionality of data with neural networks

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Observation 9f101167-5573-4e88-b04a-5ddaf5a317b5 · outbound

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DeepHealth: Review and challenges of artificial intelligence in health informatics Deep Learning

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Observation ff5ddc72-ca35-4978-bd09-84e7fc95272f · outbound

This paper cites Autoencoder — Wikipedia, the free encyclopedia.

DeepHealth: Review and challenges of artificial intelligence in health informatics Autoencoder — Wikipedia, the free encyclopedia

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Observation ac64b4b1-a7ed-42c6-b609-b97ba244433d · outbound

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DeepHealth: Review and challenges of artificial intelligence in health informatics Efficient learning of sparse representations with an energy-based model

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Observation 274c3c20-cfd8-457c-a377-d33ae5bdde87 · outbound

This paper cites Stacked denoising autoencoders: Learning useful representations in a deep network with a local denoising criterion.

DeepHealth: Review and challenges of artificial intelligence in health informatics Stacked denoising autoencoders: Learning useful representations in a deep network with a local denoising criterion

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Observation 389acbd5-26c0-4771-ae56-9dab54fc28c5 · outbound

This paper cites Extracting and composing robust features with denoising autoencoders.

DeepHealth: Review and challenges of artificial intelligence in health informatics Extracting and composing robust features with denoising autoencoders

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Observation a36862a5-cd79-45fa-8166-4ec426dd1190 · outbound

This paper cites Contractive auto-encoders: Explicit invariance during feature extraction.

DeepHealth: Review and challenges of artificial intelligence in health informatics Contractive auto-encoders: Explicit invariance during feature extraction

Reference 80

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Observation e0fa3b3a-a9be-42b5-bac6-6cd87651c67b · outbound

This paper cites Exploring strategies for training deep neural networks.

DeepHealth: Review and challenges of artificial intelligence in health informatics Exploring strategies for training deep neural networks

Reference 81

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Observation 1fdcebc1-37c9-4e28-b748-268664411aa6 · outbound

This paper cites A fast learning algorithm for deep belief nets.

DeepHealth: Review and challenges of artificial intelligence in health informatics A fast learning algorithm for deep belief nets

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Observation 6366338b-4903-4003-a0a2-41a4fbaff666 · outbound

This paper cites Learning and relearning in boltzmann machines.

DeepHealth: Review and challenges of artificial intelligence in health informatics Learning and relearning in boltzmann machines

Reference 83

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Observation 9355dae6-513f-4167-b25e-cb71a47d6d6f · outbound

This paper cites Probabilistic reasoning in intelligent systems: networks of plausible inference.

DeepHealth: Review and challenges of artificial intelligence in health informatics Probabilistic reasoning in intelligent systems: networks of plausible inference

Reference 84

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Observation 38b30860-91d2-4950-9c21-d1bf13eb0869 · outbound

This paper cites Deep boltzmann machines.

DeepHealth: Review and challenges of artificial intelligence in health informatics Deep boltzmann machines

Reference 85

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Observation f9e1b9e1-e9a5-4e18-8b7c-6ab5740295ee · outbound

This paper cites Attention is all you need.

DeepHealth: Review and challenges of artificial intelligence in health informatics Attention is all you need

Reference 86

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source=pdf_text observed=2026-08-14T05:56:20.220751Z digest=sha256:2e1a1cc531f47f5d85a01f2d126cfab46d600bab4a4e6264c76e42563960b833

Observation 6f421598-872b-4a8d-aac9-d78ca9fd37fd · outbound

This paper cites Neural Machine Translation by Jointly Learning to Align and Translate.

DeepHealth: Review and challenges of artificial intelligence in health informatics Neural Machine Translation by Jointly Learning to Align and Translate

Reference 87

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Observation 425bcb55-8cda-4e19-92c4-80728a29e486 · outbound

This paper cites How transferable are features in deep neural networks? In Advances in neural information processing systems, pages 3320–3328, 2014.

DeepHealth: Review and challenges of artificial intelligence in health informatics How transferable are features in deep neural networks? In Advances in neural information processing systems, pages 3320–3328, 2014

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Observation 15e72aa7-87f1-4dba-b724-fce6d015d0fd · outbound

This paper cites Learning many related tasks at the same time with backpropagation.

DeepHealth: Review and challenges of artificial intelligence in health informatics Learning many related tasks at the same time with backpropagation

Reference 89

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Observation 2ee07392-be30-4bfb-89f9-7c7c50d2c971 · outbound

This paper cites Deep learning of representations for unsupervised and transfer learning.

DeepHealth: Review and challenges of artificial intelligence in health informatics Deep learning of representations for unsupervised and transfer learning

Reference 90

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Observation 2d95655e-8c68-44ca-a86e-0742fd546a57 · outbound

This paper cites Deep learners benefit more from out-of-distribution examples.

DeepHealth: Review and challenges of artificial intelligence in health informatics Deep learners benefit more from out-of-distribution examples

Reference 91

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Observation ea1a8176-724a-4939-8178-55cf58deaaf6 · outbound

This paper cites Introduction to reinforcement learning, volume 135.

DeepHealth: Review and challenges of artificial intelligence in health informatics Introduction to reinforcement learning, volume 135

Reference 92

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Observation a6aa9a14-54a3-4e46-8629-f94a5a2ed8f3 · outbound

This paper cites Reinforcement learning: A survey.

DeepHealth: Review and challenges of artificial intelligence in health informatics Reinforcement learning: A survey

Reference 93

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Observation eae646f7-699e-45cf-9307-9294a974c1a1 · outbound

This paper cites Multiple model-based reinforcement learning.

DeepHealth: Review and challenges of artificial intelligence in health informatics Multiple model-based reinforcement learning

Reference 94

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Observation be28a1c5-864d-4f0f-8b21-9fa40f2f2ed1 · outbound

This paper cites A survey of actor-critic reinforcement learning: Standard and natural policy gradients.

DeepHealth: Review and challenges of artificial intelligence in health informatics A survey of actor-critic reinforcement learning: Standard and natural policy gradients

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Observation 8a97c1d5-44c6-4e0c-bc26-a928f16bae1f · outbound

This paper cites Representation learning: A review and new perspectives.

DeepHealth: Review and challenges of artificial intelligence in health informatics Representation learning: A review and new perspectives

Reference 96

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Observation 203d3687-cc59-45b3-ae91-25081361e38b · outbound

This paper cites Learning continuous control policies by stochastic value gradients.

DeepHealth: Review and challenges of artificial intelligence in health informatics Learning continuous control policies by stochastic value gradients

Reference 97

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Observation 00e70012-f59f-46d6-952c-a6e467ca0481 · outbound

This paper cites Gradient estimation using stochastic computation graphs.

DeepHealth: Review and challenges of artificial intelligence in health informatics Gradient estimation using stochastic computation graphs

Reference 98

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Observation fdf14dfd-4224-4e3a-aab8-f73f2b28c847 · outbound

This paper cites A Brief Survey of Deep Reinforcement Learning.

DeepHealth: Review and challenges of artificial intelligence in health informatics A Brief Survey of Deep Reinforcement Learning

Reference 99

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Observation 476f7b28-34cd-4c08-bb57-5bb0d47167af · outbound

This paper cites Predicting Alzheimer's disease: a neuroimaging study with 3D convolutional neural networks.

DeepHealth: Review and challenges of artificial intelligence in health informatics Predicting Alzheimer's disease: a neuroimaging study with 3D convolutional neural networks

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