Cited by 59Machine Learning in HealthcareArtificial Intelligence in HealthcareArtificial Intelligence in Healthcare and Education

Deep Learning to Predict Patient Future Diseases from the Electronic Health Records

Miotto, Riccardo, Li, Li, Dudley, Joel T.·2016·Lecture Notes in Computer Science

Integrity signals

Registry

Crossref · 10.1007/978-3-319-30671-1_66

Cites

12 of 12 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

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Cites

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Authors
Miotto, R., Li, L., & Dudley, J. T.
Affiliations
Icahn School of Medicine at Mount Sinai (US)
Corresponding author
Miotto, Riccardo
Venue
Lecture Notes in Computer Science
Published
2016
Pages
768-774
ISSN
  • 0302-9743 (ISSN-L)
  • 1611-3349
OpenAlex
W2474925868
Cited by
59
References
12
Citations by year
2026: 1 · 2025: 3 · 2024: 4 · 2023: 8 · 2022: 8 · 2021: 7 · 2020: 6 · 2019: 8 · 2018: 8 · 2017: 4 · 2016: 2
FWCI
3.95
Type
conference paper
Language
en
Open access
closed
Locations
Lecture notes in computer science (publishedVersion)
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › Machine Learning in Healthcare
  • Health Sciences › Health Professions › Health Information Management › Artificial Intelligence in Healthcare
  • Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
Keywords
electronic health records, deep learning, patient representation learning, preventive medicine, disease risk prediction, liver cancer, diabetes mellitus, heart failure

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

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