Evidence map›Paper›PMID 39070042›Full record

ArticleArXiv2026

Phuc Nguyen, Rohit Arora, Elliot D Hill, Jasper Braun, Alexandra Morgan, Liza M Quintana, Gabrielle Mazzoni, Ghee Rye Lee, Rima Arnaout, Ramy Arnaout

Abstract readPreprint
PubMed Full text at PMC
In one paragraph

Article in ArXiv, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Phuc NguyenDepartment of Pathology, Beth Israel Deaconess Medical Center, Boston, 02115, MA, USA.ORCID https://orcid.org/0000-0001-9993-8434
Rohit AroraNovo Nordisk, Plainsboro, 08536, NJ, USA.ORCID https://orcid.org/0000-0001-7128-6403
Elliot D HillDuke University, Durham, 27708, NC, USA.
Jasper BraunDepartment of Pathology, Beth Israel Deaconess Medical Center, Boston, 02115, MA, USA.ORCID https://orcid.org/0000-0003-1250-4399
Alexandra MorganDepartment of Pathology, Beth Israel Deaconess Medical Center, Boston, 02115, MA, USA.
Liza M QuintanaDepartment of Pathology, Beth Israel Deaconess Medical Center, Boston, 02115, MA, USA.ORCID https://orcid.org/0000-0002-5043-7425
Gabrielle MazzoniUniversity of Virginia, Charlottesville, 22903, VA, USA.ORCID https://orcid.org/0000-0001-7787-0547
Ghee Rye LeeOhio State College of Medicine, The Ohio State University, Columbus, 43210, OH, USA.ORCID https://orcid.org/0000-0001-6614-0223
Rima ArnaoutDepartment of Medicine, the Bakar Computational Health Sciences Institute, and the UCSF UC Berkeley Joint Program for Computational Precision Health, University of California San Francisco, San Francisco, 94143, CA, USA.ORCID https://orcid.org/0000-0002-7134-0040
Ramy ArnaoutDepartment of Pathology, Beth Israel Deaconess Medical Center, Boston, 02115, MA, USA.ORCID https://orcid.org/0000-0001-6955-9310

Funding

Toward efficient performance for deep learning on medical imagingR01HL150394 · NHLBI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Rima Arnaout · 2020 to 2026
$6.2M
An Integrated Multilevel Modeling Framework for Repertoire-Based DiagnosticsR01AI148747 · NIAID · BETH ISRAEL DEACONESS MEDICAL CENTER · PI ARNAOUT, RAMY · 2020 to 2024
$2.8M
NHLBI NIH HHS R01 HL150394NIAID NIH HHS R01 AI148747
6 · The paper itself

Abstract

Machine-learning datasets are typically characterized by measuring their size and class balance. However, there exists a richer and potentially more useful set of measures, termed S-entropy (similarity-sensitive entropy), that incorporate elements' frequencies and between-element similarities. Although these have been available in the R and Julia programming languages for other applications, they have not been as readily available in Python, which is widely used for machine learning, and are not easily applied to machine-learning-sized datasets without special coding considerations. To address these issues, we developed

Indexed as

computational pathologydata sciencediversityfrequencyimmunomicsmachine learningmedical imagingmetagenomicsPythonShannon entropysimilaritySimpson’s index

Identifiers

PMID39070042
PMCPMC11275705

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
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.