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10 merged results for "Neural Network Architectures"

Partial results: at least one source did not answer. Available results are shown rather than treating an upstream outage as zero matches.

Source status
  1. Precise anatomical delineation in ultrasound imaging using echo-spectral interactive networks.

    Xin Y, Wei S, He Q, Ling Q · 2026 · Journal of applied clinical medical physics

    limited evidence Transparent signal score 43/100 · policy 1.0.0

    Found in pubmed · DOI 10.1002/acm2.70891

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    • cautionDOI registered: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
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    • not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredOpen access status: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication license: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
  2. Sublinearly structured deep neural networks achieve feature learning consistency for compositional functions.

    Kim S, Sun Y, Liang F · 2026 · Statistical learning and data science

    limited evidence Transparent signal score 45/100 · policy 1.0.0

    Found in pubmed · DOI 10.1016/j.slads.2026.100007

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    • cautionDOI registered: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
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    • not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
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    • not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • supportingOpen access status: Normalized open-access status: open. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • not scoredPublication license: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
  3. FlexENN: A Graph Neural Network for Binding Energy Prediction of Globular and Intrinsically Disordered Proteins.

    Irshad M, Ori-McKenney K, Dima RI · 2026 · Journal of chemical information and modeling

    limited evidence Transparent signal score 43/100 · policy 1.0.0

    Found in pubmed · DOI 10.1021/acs.jcim.6c01545

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    • cautionDOI registered: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
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    • not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
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    • not scoredOpen access status: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
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    • not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
  4. spaDWGCN: a spatial distance weighted graph convolution network for accurate spatial tissue structure identification.

    Zou K, Wan R, Liu X, Pan Y · 2026 · Briefings in bioinformatics

    limited evidence Transparent signal score 45/100 · policy 1.0.0

    Found in pubmed · DOI 10.1093/bib/bbag623

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    • cautionDOI registered: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
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    • not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • supportingOpen access status: Normalized open-access status: open. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • not scoredPublication license: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
    • not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
  5. scYOU: a multi-scale yoked optimization and unsupervised framework for analysis of cellular heterogeneity and complex-associated protein module recovery.

    Gan Y, Huang Y, Gong X · 2026 · Briefings in bioinformatics

    limited evidence Transparent signal score 43/100 · policy 1.0.0

    Found in pubmed · DOI 10.1093/bib/bbag626

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    • not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredOpen access status: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
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    • not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
  6. Impact of training data on deep learning-based RNA 3D structure quality assessment.

    Adamczyk B, Szachniuk M, Antczak M · 2026 · Briefings in bioinformatics

    limited evidence Transparent signal score 43/100 · policy 1.0.0

    Found in pubmed · DOI 10.1093/bib/bbag630

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    • cautionDOI registered: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
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    • not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredOpen access status: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
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    • not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
  7. ESM-embedR: a protein language model framework for comparative mutation analysis and computational atypicality scoring of Lassa and Ebola virus sequences.

    Kolawole OM, Olayemi DM, Taiwo DI, Kolawole CF · 2026 · BMC bioinformatics

    limited evidence Transparent signal score 43/100 · policy 1.0.0

    Found in pubmed · DOI 10.1186/s12859-026-06579-w

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    • cautionDOI registered: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
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    • not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
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    • not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredOpen access status: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
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    • not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
  8. Evaluating JPEG2000 compression effects on prediction accuracy and storage efficiency in lung cancer whole-slide images: a deep learning-based analysis.

    Ji H, Yook M, Jung CK, Choi IY · 2026 · Diagnostic pathology

    limited evidence Transparent signal score 43/100 · policy 1.0.0

    Found in pubmed · DOI 10.1186/s13000-026-01830-7

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    • not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredOpen access status: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
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    • not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
  9. Impact of data quality on deep learning prediction of spatial transcriptomics from histology images.

    Hallinan C, Lucas CG, Fan J · 2026 · Genome biology

    limited evidence Transparent signal score 43/100 · policy 1.0.0

    Found in pubmed · DOI 10.1186/s13059-026-04236-2

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    • not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
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    • not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredOpen access status: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
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    • not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
  10. Beyond Model Choice: A Harness-Centered Framework for Designing Clinical Large Language Model Agents.

    Liu J, Liu S · 2026 · Journal of medical Internet research

    limited evidence Transparent signal score 43/100 · policy 1.0.0

    Found in pubmed · DOI 10.2196/101269

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    • not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
    • not scoredOpen access status: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
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    • not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
    • cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer