Evidence map›Paper›PMID 38433927›Full record

ArticleiScience2024

Distance-weighted Sinkhorn loss for Alzheimer's disease classification.

Zexuan Wang, Qipeng Zhan, Boning Tong, Shu Yang, Bojian Hou, Heng Huang, Andrew J Saykin, Paul M Thompson, Christos Davatzikos, Li Shen

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in iScience, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.2field-weighted citation impact, top 24% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 5 citations in OpenAlex.

  1. SLR: A Modified Logistic Regression Model with Sinkhorn Divergence for Alzheimer's Disease Classification.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2025
    Article
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 4 institutions in 1 country.

Zexuan WangUniversity of Pennsylvania, B301 Richards Building, 3700 Hamilton Walk, Philadelphia, PA 19104, USA.
Qipeng ZhanUniversity of Pennsylvania, B301 Richards Building, 3700 Hamilton Walk, Philadelphia, PA 19104, USA.
Boning TongUniversity of Pennsylvania, B301 Richards Building, 3700 Hamilton Walk, Philadelphia, PA 19104, USA.
Shu YangUniversity of Pennsylvania, B301 Richards Building, 3700 Hamilton Walk, Philadelphia, PA 19104, USA.
Bojian HouUniversity of Pennsylvania, B301 Richards Building, 3700 Hamilton Walk, Philadelphia, PA 19104, USA.
Heng HuangUniversity of Maryland, College Park, 8125 Paint Branch Drive, College Park, MD 20742, USA.
Andrew J SaykinIndiana University, 355 West 16th Street, Indianapolis, IN 46202, USA.
Paul M ThompsonUniversity of Southern California, 4676 Admiralty Way, Marina Del Rey, CA 90292, USA.
Christos DavatzikosUniversity of Pennsylvania, B301 Richards Building, 3700 Hamilton Walk, Philadelphia, PA 19104, USA.
Li ShenUniversity of Pennsylvania, B301 Richards Building, 3700 Hamilton Walk, Philadelphia, PA 19104, USA.
University of Pennsylvania · USIndiana University – Purdue University Indianapolis · USUniversity of Maryland, College Park · USUniversity of Southern California · US

Funding

Alzheimer's Disease Neuroimaging Initiative - SupplementU01AG024904 · NIA · NORTHERN CALIFORNIA INSTITUTE RES &EDUC · PI WEINER, MICHAEL W · 2004 to 2015
$121.0M
Technology Identification and Training CoreP30AG073105 · NIA · UNIVERSITY OF PENNSYLVANIA · PI DEMIRIS, GEORGE, KARLAWISH, JASON H · 2021 to 2025
$21.2M
Ultrascale Machine Learning to Empower Discovery in Alzheimers Disease BiobanksU01AG068057 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI Christos Davatzikos, Heng Huang · 2020 to 2026
$20.7M
Artificial Intelligence Strategies for Alzheimer's Disease ResearchU01AG066833 · NIA · CEDARS-SINAI MEDICAL CENTER · PI MOORE, JASON H., RITCHIE, MARYLYN D · 2022 to 2025
$6.7M
Translational big data analytic approaches to advance drug repurposing for Alzheimer's diseaseR01AG071470 · NIA · UNIVERSITY OF PENNSYLVANIA · PI KIM, DOKYOON, NING, XIA · 2021 to 2025
$3.8M
Advancing Analysis of Multi-omics Data in Alzheimer's Disease ResearchRF1AG063481 · NIA · UNIVERSITY OF PENNSYLVANIA · PI LONG, QI · 2019 to 2020
$3.8M
Bioinformatics Strategies for Multidimensional Brain Imaging GeneticsR01LM011360 · NLM · INDIANA UNIVERSITY INDIANAPOLIS · PI MOORE, JASON H., SAYKIN, ANDREW J · 2012 to 2015
$1.4M
Informatics Algorithms for Genomic Analysis of Brain Imaging DataR01LM013463 · NLM · UNIVERSITY OF PENNSYLVANIA · PI MOORE, JASON H., SAYKIN, ANDREW J · 2020 to 2023
$1.4M
NIA NIH HHS P30 AG073105NIA NIH HHS R01 AG071470NIA NIH HHS RF1 AG063481NIA NIH HHS U01 AG024904NIA NIH HHS U01 AG066833NIA NIH HHS U01 AG068057NLM NIH HHS R01 LM011360NLM NIH HHS R01 LM013463
6 · The paper itself

Abstract

Traditional loss functions such as cross-entropy loss often quantify the penalty for each mis-classified training sample without adequately considering its distance from the ground truth class distribution in the feature space. Intuitively, the larger this distance is, the higher the penalty should be. With this observation, we propose a penalty called distance-weighted Sinkhorn (DWS) loss. For each mis-classified training sample (with predicted label

Indexed as

Biocomputational methodClassification of bioinformatical subjectMachine learningMedical informaticsNeural networks

Identifiers

PMID38433927
PMCPMC10906516
OpenAlexW4391755833

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.