Determination of the Relative Frequencies of Expected Diagnoses in Duodenal Biopsies: An Essential Step in Developing an Artificial Intelligence Approach to Diagnostic Classification Article Swipe

PDF

V. Shenoy , Joby James , Amelia B. Williams-Walker , Navya Mohan , Kim Ngan Luu Hoang , J. Williams , Florian Jaeckle , Shelley Evans , Elizabeth J. Soilleux ·

YOU? · · 2025 · Open Access · · DOI: https://doi.org/10.20944/preprints202503.2274.v1

Understanding the diagnostic landscape prior to developing novel diagnostic strategies is key to managing expectations and authenticating results. In considering the possibility of developing alternate diagnostic approaches for coeliac disease based on duodenal biopsies, we audited 18 months’ worth of duodenal biopsies received in our centre to determine the exact proportions of different diagnoses. A total of 6245 duodenal biopsies were audited, of which 73.76% were normal and 8.84% fell within the spectrum of coeliac disease. Additionally, 6.47% were classified as showing non-specific inflammation, 1.86% were adenomas, 0.42% were carcinomas, and 0.06% were neuroendocrine tumours. Rarer diagnoses included ulceration, Helicobacter pylori infection, Giardiasis, lymphangiectasia, transplant rejection, and lymphoma. Furthermore, 227 biopsies (3.63%) showed isolated intraepithelial lymphocytosis, of which 24 cases eventually received a definitive diagnosis of coeliac disease. We present the first long-term audit of all endoscopic duodenal biopsies received by the histopathology department of a tertiary care facility. The results indicate that a fully automated system that could identify normal duodenal biopsies and biopsies within the spectrum of coeliac disease-associated enteropathy could decrease pathologists’ endoscopic duodenal biopsy workload by up to 80%.

Related Topics

Medical Diagnosis

Artificial Intelligence

Computer Science

Biomedical Engineering

Medicine

Radiology

Concepts

Medical diagnosis Artificial intelligence Computer science Pattern recognition (psychology) Biomedical engineering Medicine Radiology

Metadata

Type: preprint
Language: en
Landing Page: https://doi.org/10.20944/preprints202503.2274.v1
PDF: https://www.preprints.org/frontend/manuscript/ab985933d2bda88500db75dde3b9e5e0/download_pub
OA Status: green
Related Works: 10
OpenAlex ID: https://openalex.org/W4409016701

All OpenAlex metadata

Raw OpenAlex JSON

OpenAlex ID: https://openalex.org/W4409016701

Canonical identifier for this work in OpenAlex
DOI: https://doi.org/10.20944/preprints202503.2274.v1

Digital Object Identifier
Title: Determination of the Relative Frequencies of Expected Diagnoses in Duodenal Biopsies: An Essential Step in Developing an Artificial Intelligence Approach to Diagnostic Classification

Work title
Type: preprint

OpenAlex work type
Language: en

Primary language
Publication year: 2025

Year of publication
Publication date: 2025-03-31

Full publication date if available
Authors: V. Shenoy, Joby James, Amelia B. Williams-Walker, Navya Mohan, Kim Ngan Luu Hoang, J. Williams, Florian Jaeckle, Shelley Evans, Elizabeth J. Soilleux

List of authors in order
Landing page: https://doi.org/10.20944/preprints202503.2274.v1

Publisher landing page
PDF URL: https://www.preprints.org/frontend/manuscript/ab985933d2bda88500db75dde3b9e5e0/download_pub

Direct link to full text PDF
Open access: Yes

Whether a free full text is available
OA status: green

Open access status per OpenAlex
OA URL: https://www.preprints.org/frontend/manuscript/ab985933d2bda88500db75dde3b9e5e0/download_pub

Direct OA link when available
Concepts: Medical diagnosis, Artificial intelligence, Computer science, Pattern recognition (psychology), Biomedical engineering, Medicine, Radiology

Top concepts (fields/topics) attached by OpenAlex
Cited by: 0

Total citation count in OpenAlex
Related works (count): 10

Other works algorithmically related by OpenAlex

Full payload

id	https://openalex.org/W4409016701
doi	https://doi.org/10.20944/preprints202503.2274.v1
ids.doi	https://doi.org/10.20944/preprints202503.2274.v1
ids.openalex	https://openalex.org/W4409016701
fwci	0.0
type	preprint
title	Determination of the Relative Frequencies of Expected Diagnoses in Duodenal Biopsies: An Essential Step in Developing an Artificial Intelligence Approach to Diagnostic Classification
biblio.issue
biblio.volume
biblio.last_page
biblio.first_page
topics[0].id	https://openalex.org/T13702
topics[0].field.id	https://openalex.org/fields/17
topics[0].field.display_name	Computer Science
topics[0].score	0.8514000177383423
topics[0].domain.id	https://openalex.org/domains/3
topics[0].domain.display_name	Physical Sciences
topics[0].subfield.id	https://openalex.org/subfields/1702
topics[0].subfield.display_name	Artificial Intelligence
topics[0].display_name	Machine Learning in Healthcare
topics[1].id	https://openalex.org/T11396
topics[1].field.id	https://openalex.org/fields/36
topics[1].field.display_name	Health Professions
topics[1].score	0.7792999744415283
topics[1].domain.id	https://openalex.org/domains/4
topics[1].domain.display_name	Health Sciences
topics[1].subfield.id	https://openalex.org/subfields/3605
topics[1].subfield.display_name	Health Information Management
topics[1].display_name	Artificial Intelligence in Healthcare
topics[2].id	https://openalex.org/T14400
topics[2].field.id	https://openalex.org/fields/36
topics[2].field.display_name	Health Professions
topics[2].score	0.7390999794006348
topics[2].domain.id	https://openalex.org/domains/4
topics[2].domain.display_name	Health Sciences
topics[2].subfield.id	https://openalex.org/subfields/3605
topics[2].subfield.display_name	Health Information Management
topics[2].display_name	Medical Coding and Health Information
is_xpac	False
apc_list
apc_paid
concepts[0].id	https://openalex.org/C534262118
concepts[0].level	2
concepts[0].score	0.69981849193573
concepts[0].wikidata	https://www.wikidata.org/wiki/Q177719
concepts[0].display_name	Medical diagnosis
concepts[1].id	https://openalex.org/C154945302
concepts[1].level	1
concepts[1].score	0.5189592242240906
concepts[1].wikidata	https://www.wikidata.org/wiki/Q11660
concepts[1].display_name	Artificial intelligence
concepts[2].id	https://openalex.org/C41008148
concepts[2].level	0
concepts[2].score	0.41964611411094666
concepts[2].wikidata	https://www.wikidata.org/wiki/Q21198
concepts[2].display_name	Computer science
concepts[3].id	https://openalex.org/C153180895
concepts[3].level	2
concepts[3].score	0.3752243220806122
concepts[3].wikidata	https://www.wikidata.org/wiki/Q7148389
concepts[3].display_name	Pattern recognition (psychology)
concepts[4].id	https://openalex.org/C136229726
concepts[4].level	1
concepts[4].score	0.335688054561615
concepts[4].wikidata	https://www.wikidata.org/wiki/Q327092
concepts[4].display_name	Biomedical engineering
concepts[5].id	https://openalex.org/C71924100
concepts[5].level	0
concepts[5].score	0.28213247656822205
concepts[5].wikidata	https://www.wikidata.org/wiki/Q11190
concepts[5].display_name	Medicine
concepts[6].id	https://openalex.org/C126838900
concepts[6].level	1
concepts[6].score	0.2676204741001129
concepts[6].wikidata	https://www.wikidata.org/wiki/Q77604
concepts[6].display_name	Radiology
keywords[0].id	https://openalex.org/keywords/medical-diagnosis
keywords[0].score	0.69981849193573
keywords[0].display_name	Medical diagnosis
keywords[1].id	https://openalex.org/keywords/artificial-intelligence
keywords[1].score	0.5189592242240906
keywords[1].display_name	Artificial intelligence
keywords[2].id	https://openalex.org/keywords/computer-science
keywords[2].score	0.41964611411094666
keywords[2].display_name	Computer science
keywords[3].id	https://openalex.org/keywords/pattern-recognition
keywords[3].score	0.3752243220806122
keywords[3].display_name	Pattern recognition (psychology)
keywords[4].id	https://openalex.org/keywords/biomedical-engineering
keywords[4].score	0.335688054561615
keywords[4].display_name	Biomedical engineering
keywords[5].id	https://openalex.org/keywords/medicine
keywords[5].score	0.28213247656822205
keywords[5].display_name	Medicine
keywords[6].id	https://openalex.org/keywords/radiology
keywords[6].score	0.2676204741001129
keywords[6].display_name	Radiology
language	en
locations[0].id	doi:10.20944/preprints202503.2274.v1
locations[0].is_oa	True
locations[0].source.id	https://openalex.org/S6309402219
locations[0].source.issn
locations[0].source.type	repository
locations[0].source.is_oa	True
locations[0].source.issn_l
locations[0].source.is_core	False
locations[0].source.is_in_doaj	False
locations[0].source.display_name	Preprints.org
locations[0].source.host_organization
locations[0].source.host_organization_name
locations[0].source.host_organization_lineage	https://openalex.org/P4310310987
locations[0].source.host_organization_lineage_names	Multidisciplinary Digital Publishing Institute
locations[0].license	cc-by
locations[0].pdf_url	https://www.preprints.org/frontend/manuscript/ab985933d2bda88500db75dde3b9e5e0/download_pub
locations[0].version	acceptedVersion
locations[0].raw_type	posted-content
locations[0].license_id	https://openalex.org/licenses/cc-by
locations[0].is_accepted	True
locations[0].is_published	False
locations[0].raw_source_name
locations[0].landing_page_url	https://doi.org/10.20944/preprints202503.2274.v1
indexed_in	crossref
authorships[0].author.id	https://openalex.org/A5019739043
authorships[0].author.orcid	https://orcid.org/0000-0002-8306-4215
authorships[0].author.display_name	V. Shenoy
authorships[0].author_position	first
authorships[0].raw_author_name	V Shenoy
authorships[0].is_corresponding	False
authorships[1].author.id	https://openalex.org/A5022024488
authorships[1].author.orcid
authorships[1].author.display_name	Joby James
authorships[1].author_position	middle
authorships[1].raw_author_name	J. L. James
authorships[1].is_corresponding	False
authorships[2].author.id	https://openalex.org/A5093351322
authorships[2].author.orcid
authorships[2].author.display_name	Amelia B. Williams-Walker
authorships[2].author_position	middle
authorships[2].raw_author_name	A. B. Williams-Walker
authorships[2].is_corresponding	False
authorships[3].author.id	https://openalex.org/A5103999599
authorships[3].author.orcid
authorships[3].author.display_name	Navya Mohan
authorships[3].author_position	middle
authorships[3].raw_author_name	N. P.R. Madhan Mohan
authorships[3].is_corresponding	False
authorships[4].author.id	https://openalex.org/A5058866430
authorships[4].author.orcid	https://orcid.org/0000-0001-5670-1832
authorships[4].author.display_name	Kim Ngan Luu Hoang
authorships[4].author_position	middle
authorships[4].raw_author_name	K. N. Luu Hoang
authorships[4].is_corresponding	False
authorships[5].author.id	https://openalex.org/A5086596609
authorships[5].author.orcid
authorships[5].author.display_name	J. Williams
authorships[5].author_position	middle
authorships[5].raw_author_name	J. Williams
authorships[5].is_corresponding	False
authorships[6].author.id	https://openalex.org/A5033700527
authorships[6].author.orcid	https://orcid.org/0009-0002-4607-6476
authorships[6].author.display_name	Florian Jaeckle
authorships[6].author_position	middle
authorships[6].raw_author_name	F. Jaeckle
authorships[6].is_corresponding	False
authorships[7].author.id	https://openalex.org/A5016136114
authorships[7].author.orcid	https://orcid.org/0000-0003-3242-6017
authorships[7].author.display_name	Shelley Evans
authorships[7].author_position	middle
authorships[7].raw_author_name	S. C. Evans
authorships[7].is_corresponding	False
authorships[8].author.id	https://openalex.org/A5062739895
authorships[8].author.orcid	https://orcid.org/0000-0002-4032-7249
authorships[8].author.display_name	Elizabeth J. Soilleux
authorships[8].author_position	last
authorships[8].raw_author_name	E. J. Soilleux
authorships[8].is_corresponding	False
has_content.pdf	True
has_content.grobid_xml	False
is_paratext	False
open_access.is_oa	True
open_access.oa_url	https://www.preprints.org/frontend/manuscript/ab985933d2bda88500db75dde3b9e5e0/download_pub
open_access.oa_status	green
open_access.any_repository_has_fulltext	False
created_date	2025-10-10T00:00:00
display_name	Determination of the Relative Frequencies of Expected Diagnoses in Duodenal Biopsies: An Essential Step in Developing an Artificial Intelligence Approach to Diagnostic Classification
has_fulltext	False
is_retracted	False
updated_date	2025-11-06T03:46:38.306776
primary_topic.id	https://openalex.org/T13702
primary_topic.field.id	https://openalex.org/fields/17
primary_topic.field.display_name	Computer Science
primary_topic.score	0.8514000177383423
primary_topic.domain.id	https://openalex.org/domains/3
primary_topic.domain.display_name	Physical Sciences
primary_topic.subfield.id	https://openalex.org/subfields/1702
primary_topic.subfield.display_name	Artificial Intelligence
primary_topic.display_name	Machine Learning in Healthcare
related_works	https://openalex.org/W4391375266, https://openalex.org/W2899084033, https://openalex.org/W2748952813, https://openalex.org/W2390279801, https://openalex.org/W4391913857, https://openalex.org/W4249377076, https://openalex.org/W2358668433, https://openalex.org/W4396701345, https://openalex.org/W2033914206, https://openalex.org/W2042327336
cited_by_count	0
locations_count	1
best_oa_location.id	doi:10.20944/preprints202503.2274.v1
best_oa_location.is_oa	True
best_oa_location.source.id	https://openalex.org/S6309402219
best_oa_location.source.issn
best_oa_location.source.type	repository
best_oa_location.source.is_oa	True
best_oa_location.source.issn_l
best_oa_location.source.is_core	False
best_oa_location.source.is_in_doaj	False
best_oa_location.source.display_name	Preprints.org
best_oa_location.source.host_organization
best_oa_location.source.host_organization_name
best_oa_location.source.host_organization_lineage	https://openalex.org/P4310310987
best_oa_location.source.host_organization_lineage_names	Multidisciplinary Digital Publishing Institute
best_oa_location.license	cc-by
best_oa_location.pdf_url	https://www.preprints.org/frontend/manuscript/ab985933d2bda88500db75dde3b9e5e0/download_pub
best_oa_location.version	acceptedVersion
best_oa_location.raw_type	posted-content
best_oa_location.license_id	https://openalex.org/licenses/cc-by
best_oa_location.is_accepted	True
best_oa_location.is_published	False
best_oa_location.raw_source_name
best_oa_location.landing_page_url	https://doi.org/10.20944/preprints202503.2274.v1
primary_location.id	doi:10.20944/preprints202503.2274.v1
primary_location.is_oa	True
primary_location.source.id	https://openalex.org/S6309402219
primary_location.source.issn
primary_location.source.type	repository
primary_location.source.is_oa	True
primary_location.source.issn_l
primary_location.source.is_core	False
primary_location.source.is_in_doaj	False
primary_location.source.display_name	Preprints.org
primary_location.source.host_organization
primary_location.source.host_organization_name
primary_location.source.host_organization_lineage	https://openalex.org/P4310310987
primary_location.source.host_organization_lineage_names	Multidisciplinary Digital Publishing Institute
primary_location.license	cc-by
primary_location.pdf_url	https://www.preprints.org/frontend/manuscript/ab985933d2bda88500db75dde3b9e5e0/download_pub
primary_location.version	acceptedVersion
primary_location.raw_type	posted-content
primary_location.license_id	https://openalex.org/licenses/cc-by
primary_location.is_accepted	True
primary_location.is_published	False
primary_location.raw_source_name
primary_location.landing_page_url	https://doi.org/10.20944/preprints202503.2274.v1
publication_date	2025-03-31
publication_year	2025
referenced_works_count	0
abstract_inverted_index.A	54
abstract_inverted_index.a	122, 145, 153
abstract_inverted_index.18	36
abstract_inverted_index.24	118
abstract_inverted_index.In	18
abstract_inverted_index.We	128
abstract_inverted_index.as	80
abstract_inverted_index.by	140, 179
abstract_inverted_index.in	43
abstract_inverted_index.is	10
abstract_inverted_index.of	22, 39, 51, 56, 62, 73, 116, 125, 134, 144, 168
abstract_inverted_index.on	31
abstract_inverted_index.to	5, 12, 46, 181
abstract_inverted_index.up	180
abstract_inverted_index.we	34
abstract_inverted_index.227	109
abstract_inverted_index.The	149
abstract_inverted_index.all	135
abstract_inverted_index.and	15, 67, 90, 106, 163
abstract_inverted_index.for	27
abstract_inverted_index.key	11
abstract_inverted_index.our	44
abstract_inverted_index.the	1, 20, 48, 71, 130, 141, 166
abstract_inverted_index.6245	57
abstract_inverted_index.80%.	182
abstract_inverted_index.care	147
abstract_inverted_index.fell	69
abstract_inverted_index.that	152, 157
abstract_inverted_index.were	60, 65, 78, 85, 88, 92
abstract_inverted_index.0.06%	91
abstract_inverted_index.0.42%	87
abstract_inverted_index.1.86%	84
abstract_inverted_index.6.47%	77
abstract_inverted_index.8.84%	68
abstract_inverted_index.Rarer	95
abstract_inverted_index.audit	133
abstract_inverted_index.based	30
abstract_inverted_index.cases	119
abstract_inverted_index.could	158, 172
abstract_inverted_index.exact	49
abstract_inverted_index.first	131
abstract_inverted_index.fully	154
abstract_inverted_index.novel	7
abstract_inverted_index.prior	4
abstract_inverted_index.total	55
abstract_inverted_index.which	63, 117
abstract_inverted_index.worth	38
abstract_inverted_index.73.76%	64
abstract_inverted_index.biopsy	177
abstract_inverted_index.centre	45
abstract_inverted_index.normal	66, 160
abstract_inverted_index.pylori	100
abstract_inverted_index.showed	112
abstract_inverted_index.system	156
abstract_inverted_index.within	70, 165
abstract_inverted_index.(3.63%)	111
abstract_inverted_index.audited	35
abstract_inverted_index.coeliac	28, 74, 126, 169
abstract_inverted_index.disease	29
abstract_inverted_index.present	129
abstract_inverted_index.results	150
abstract_inverted_index.showing	81
abstract_inverted_index.audited,	61
abstract_inverted_index.biopsies	41, 59, 110, 138, 162, 164
abstract_inverted_index.decrease	173
abstract_inverted_index.disease.	75, 127
abstract_inverted_index.duodenal	32, 40, 58, 137, 161, 176
abstract_inverted_index.identify	159
abstract_inverted_index.included	97
abstract_inverted_index.indicate	151
abstract_inverted_index.isolated	113
abstract_inverted_index.managing	13
abstract_inverted_index.received	42, 121, 139
abstract_inverted_index.results.	17
abstract_inverted_index.spectrum	72, 167
abstract_inverted_index.tertiary	146
abstract_inverted_index.tumours.	94
abstract_inverted_index.workload	178
abstract_inverted_index.adenomas,	86
abstract_inverted_index.alternate	24
abstract_inverted_index.automated	155
abstract_inverted_index.biopsies,	33
abstract_inverted_index.determine	47
abstract_inverted_index.diagnoses	96
abstract_inverted_index.diagnosis	124
abstract_inverted_index.different	52
abstract_inverted_index.facility.	148
abstract_inverted_index.landscape	3
abstract_inverted_index.long-term	132
abstract_inverted_index.lymphoma.	107
abstract_inverted_index.months’	37
abstract_inverted_index.approaches	26
abstract_inverted_index.classified	79
abstract_inverted_index.definitive	123
abstract_inverted_index.department	143
abstract_inverted_index.developing	6, 23
abstract_inverted_index.diagnoses.	53
abstract_inverted_index.diagnostic	2, 8, 25
abstract_inverted_index.endoscopic	136, 175
abstract_inverted_index.eventually	120
abstract_inverted_index.infection,	101
abstract_inverted_index.rejection,	105
abstract_inverted_index.strategies	9
abstract_inverted_index.transplant	104
abstract_inverted_index.Giardiasis,	102
abstract_inverted_index.carcinomas,	89
abstract_inverted_index.considering	19
abstract_inverted_index.enteropathy	171
abstract_inverted_index.possibility	21
abstract_inverted_index.proportions	50
abstract_inverted_index.ulceration,	98
abstract_inverted_index.Furthermore,	108
abstract_inverted_index.Helicobacter	99
abstract_inverted_index.expectations	14
abstract_inverted_index.non-specific	82
abstract_inverted_index.Additionally,	76
abstract_inverted_index.Understanding	0
abstract_inverted_index.inflammation,	83
abstract_inverted_index.authenticating	16
abstract_inverted_index.histopathology	142
abstract_inverted_index.lymphocytosis,	115
abstract_inverted_index.neuroendocrine	93
abstract_inverted_index.intraepithelial	114
abstract_inverted_index.pathologists’	174
abstract_inverted_index.lymphangiectasia,	103
abstract_inverted_index.disease-associated	170
cited_by_percentile_year
countries_distinct_count	0
institutions_distinct_count	9
citation_normalized_percentile.value	0.04095146
citation_normalized_percentile.is_in_top_1_percent	False
citation_normalized_percentile.is_in_top_10_percent	True