Evidence map›Paper›PMID 42775178›Full record

ArticleOxford open digital health2026

Leveraging digital pathology to enhance breast cancer diagnosis in low-resource settings: a cross-sectional study of major histopathology laboratories in Uganda.

Agnes R Semwanga, James Serubugo, Vincent M Kiberu, Hawa Nalwoga, Evelyn K Kahiigi, Nazarius M Tumwesigye, Sam Kalungi

Abstract read
In one paragraph

Article in Oxford open digital health, 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

7 authors.

Agnes R SemwangaDepartment of Information Systems, Makerere University College of Computing and Information Sciences, University Road P.O. Box 7062, Kampala, Uganda.
James SerubugoDepartment of Epidemiology and Biostatistics, Makerere University School of Public Health, New Mulago Hill Road, Mulago P.O. Box 7072, Kampala, Uganda.
Vincent M KiberuDepartment of Epidemiology and Biostatistics, Makerere University School of Public Health, New Mulago Hill Road, Mulago P.O. Box 7072, Kampala, Uganda.
Hawa NalwogaDepartment of Pathology, School of Biomedical Sciences, Makerere University College of Health Sciences, Pathology-Microbiology Building Upper Mulago Hill Road, Mulago P.O. Box 7072, Kampala, Uganda.
Evelyn K KahiigiDepartment of Information Systems, Makerere University College of Computing and Information Sciences, University Road P.O. Box 7062, Kampala, Uganda.
Nazarius M TumwesigyeDepartment of Epidemiology and Biostatistics, Makerere University School of Public Health, New Mulago Hill Road, Mulago P.O. Box 7072, Kampala, Uganda.
Sam KalungiUganda National Cancer Institute, Upper Mulago Hill Road P.O. Box 3935, Kampala, Uganda.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Breast cancer remains a leading cause of morbidity and mortality among Ugandan women, particularly in rural areas where pathology infrastructure and specialist access are limited. This study aimed to improve diagnostic efficiency and accuracy by digitizing breast cancer slides and implementing a web-based histopathology system to support remote diagnostics. A total of 100 glass slides from core breast biopsy samples were digitized using an Aperio AT2 slide scanner. A web-based breast histology information management system (BHIMS) was developed to store and provide remote access to these digital slides. Two experienced pathologists independently evaluated the slides using both conventional microscopy and the digital platform. Assessments focused on key morphological features, including cancer diagnosis, type, grade, mitosis, lymphatic invasion, nuclear pleomorphism, and tubule formation. Inter- and intra-observer agreement was analyzed using kappa statistics. Digital pathology showed high inter- and intra-observer reliability, particularly for cancer diagnosis and type. Slightly lower agreement was noted for nuanced features such as mitosis and lymphatic invasion. Conventional microscopy yielded stronger observer agreement and confidence, especially for mitotic count and invasion. Digital pathology offers a promising approach to improve breast cancer diagnosis in resource-limited settings. The BHIMS system enabled remote access and collaborative review of cases, supporting decentralized pathology services. However, broader adoption will require investment in high-resolution scanners, reliable internet, data storage, and training of pathologists. With these enhancements, digital pathology could significantly strengthen cancer care delivery in rural Uganda.

Indexed as

breast cancerdigital pathologyobserver agreementweb-based system

Identifiers

PMID42775178
PMCPMC13595349

What Socratic holds

Textmetadata
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 Socratic graph.