Pitfalls in machine learning-based assessment of tumor-infiltrating lymphocytes in breast cancer: A report of the International Immuno-Oncology Biomarker Working Group on Breast Cancer.

Thagaard J, Broeckx G, Page DB, Jahangir CA, Verbandt S, Kos Z, Gupta R, Khiroya R, Abduljabbar K, Acosta Haab G, Acs B, Akturk G, Almeida JS, Alvarado-Cabrero I, Amgad M, Azmoudeh-Ardalan F, Badve S, Baharun NB, Balslev E, Bellolio ER, Bheemaraju V, Blenman KR, Botinelly Mendonça Fujimoto L, Bouchmaa N, Burgues O, Chardas A, Chon U Cheang M, Ciompi F, Cooper LA, Coosemans A, Corredor G, Dahl AB, Dantas Portela FL, Deman F, Demaria S, Doré Hansen J, Dudgeon SN, Ebstrup T, Elghazawy M, Fernandez-Martín C, Fox SB, Gallagher WM, Giltnane JM, Gnjatic S, Gonzalez-Ericsson PI, Grigoriadis A, Halama N, Hanna MG, Harbhajanka A, Hart SN, Hartman J, Hauberg S, Hewitt S, Hida AI, Horlings HM, Husain Z, Hytopoulos E, Irshad S, Janssen EA, Kahila M, Kataoka TR, Kawaguchi K, Kharidehal D, Khramtsov AI, Kiraz U, Kirtani P, Kodach LL, Korski K, Kovács A, Laenkholm AV, Lang-Schwarz C, Larsimont D, Lennerz JK, Lerousseau M, Li X, Ly A, Madabhushi A, Maley SK, Manur Narasimhamurthy V, Marks DK, McDonald ES, Mehrotra R, Michiels S, Minhas FUAA, Mittal S, Moore DA, Mushtaq S, Nighat H, Papathomas T, Penault-Llorca F, Perera RD, Pinard CJ, Pinto-Cardenas JC, Pruneri G, Pusztai L, Rahman A, Rajpoot NM, Rapoport BL, Rau TT, Reis-Filho JS, Ribeiro JM, Rimm D, Roslind A, Vincent-Salomon A, Salto-Tellez M, Saltz J, Sayed S, Scott E, Siziopikou KP, Sotiriou C, Stenzinger A, Sughayer MA, Sur D, Fineberg S, Symmans F, Tanaka S, Taxter T, Tejpar S, Teuwen J, Thompson EA, Tramm T, Tran WT, van der Laak J, van Diest PJ, Verghese GE, Viale G, Vieth M, Wahab N, Walter T, Waumans Y, Wen HY, Yang W, Yuan Y, Zin RM, Adams S, Bartlett J, Loibl S, Denkert C, Savas P, Loi S, Salgado R, Specht Stovgaard E

Open source

DOI: 10.1002/path.6155
Published: 2023 Aug
Container: The Journal of pathology
Publisher: Not recorded
Open access: yes

Credibility signals

limited evidence Score 45/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.

Show all credibility signals

cautionDOI registered: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
cautionDOI resolves: No matching Crossref record was present in this response. Source: Crossref; license: CC0 metadata
not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility. Source: DOAJ; license: CC0
not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredOpenAlex core source: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredROR affiliation: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
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

Cite this work

BibTeX

@article{allodium:10.1002/path.6155,
  title = {Pitfalls in machine learning-based assessment of tumor-infiltrating lymphocytes in breast cancer: A report of the International Immuno-Oncology Biomarker Working Group on Breast Cancer.},
  author = {Thagaard J and Broeckx G and Page DB and Jahangir CA and Verbandt S and Kos Z and Gupta R and Khiroya R and Abduljabbar K and Acosta Haab G and Acs B and Akturk G and Almeida JS and Alvarado-Cabrero I and Amgad M and Azmoudeh-Ardalan F and Badve S and Baharun NB and Balslev E and Bellolio ER and Bheemaraju V and Blenman KR and Botinelly Mendonça Fujimoto L and Bouchmaa N and Burgues O and Chardas A and Chon U Cheang M and Ciompi F and Cooper LA and Coosemans A and Corredor G and Dahl AB and Dantas Portela FL and Deman F and Demaria S and Doré Hansen J and Dudgeon SN and Ebstrup T and Elghazawy M and Fernandez-Martín C and Fox SB and Gallagher WM and Giltnane JM and Gnjatic S and Gonzalez-Ericsson PI and Grigoriadis A and Halama N and Hanna MG and Harbhajanka A and Hart SN and Hartman J and Hauberg S and Hewitt S and Hida AI and Horlings HM and Husain Z and Hytopoulos E and Irshad S and Janssen EA and Kahila M and Kataoka TR and Kawaguchi K and Kharidehal D and Khramtsov AI and Kiraz U and Kirtani P and Kodach LL and Korski K and Kovács A and Laenkholm AV and Lang-Schwarz C and Larsimont D and Lennerz JK and Lerousseau M and Li X and Ly A and Madabhushi A and Maley SK and Manur Narasimhamurthy V and Marks DK and McDonald ES and Mehrotra R and Michiels S and Minhas FUAA and Mittal S and Moore DA and Mushtaq S and Nighat H and Papathomas T and Penault-Llorca F and Perera RD and Pinard CJ and Pinto-Cardenas JC and Pruneri G and Pusztai L and Rahman A and Rajpoot NM and Rapoport BL and Rau TT and Reis-Filho JS and Ribeiro JM and Rimm D and Roslind A and Vincent-Salomon A and Salto-Tellez M and Saltz J and Sayed S and Scott E and Siziopikou KP and Sotiriou C and Stenzinger A and Sughayer MA and Sur D and Fineberg S and Symmans F and Tanaka S and Taxter T and Tejpar S and Teuwen J and Thompson EA and Tramm T and Tran WT and van der Laak J and van Diest PJ and Verghese GE and Viale G and Vieth M and Wahab N and Walter T and Waumans Y and Wen HY and Yang W and Yuan Y and Zin RM and Adams S and Bartlett J and Loibl S and Denkert C and Savas P and Loi S and Salgado R and Specht Stovgaard E},
  year = {2023},
  journal = {The Journal of pathology},
  doi = {10.1002/path.6155},
  url = {https://doi.org/10.1002/path.6155}
}

RIS

TY  - JOUR
TI  - Pitfalls in machine learning-based assessment of tumor-infiltrating lymphocytes in breast cancer: A report of the International Immuno-Oncology Biomarker Working Group on Breast Cancer.
AU  - Thagaard J
AU  - Broeckx G
AU  - Page DB
AU  - Jahangir CA
AU  - Verbandt S
AU  - Kos Z
AU  - Gupta R
AU  - Khiroya R
AU  - Abduljabbar K
AU  - Acosta Haab G
AU  - Acs B
AU  - Akturk G
AU  - Almeida JS
AU  - Alvarado-Cabrero I
AU  - Amgad M
AU  - Azmoudeh-Ardalan F
AU  - Badve S
AU  - Baharun NB
AU  - Balslev E
AU  - Bellolio ER
AU  - Bheemaraju V
AU  - Blenman KR
AU  - Botinelly Mendonça Fujimoto L
AU  - Bouchmaa N
AU  - Burgues O
AU  - Chardas A
AU  - Chon U Cheang M
AU  - Ciompi F
AU  - Cooper LA
AU  - Coosemans A
AU  - Corredor G
AU  - Dahl AB
AU  - Dantas Portela FL
AU  - Deman F
AU  - Demaria S
AU  - Doré Hansen J
AU  - Dudgeon SN
AU  - Ebstrup T
AU  - Elghazawy M
AU  - Fernandez-Martín C
AU  - Fox SB
AU  - Gallagher WM
AU  - Giltnane JM
AU  - Gnjatic S
AU  - Gonzalez-Ericsson PI
AU  - Grigoriadis A
AU  - Halama N
AU  - Hanna MG
AU  - Harbhajanka A
AU  - Hart SN
AU  - Hartman J
AU  - Hauberg S
AU  - Hewitt S
AU  - Hida AI
AU  - Horlings HM
AU  - Husain Z
AU  - Hytopoulos E
AU  - Irshad S
AU  - Janssen EA
AU  - Kahila M
AU  - Kataoka TR
AU  - Kawaguchi K
AU  - Kharidehal D
AU  - Khramtsov AI
AU  - Kiraz U
AU  - Kirtani P
AU  - Kodach LL
AU  - Korski K
AU  - Kovács A
AU  - Laenkholm AV
AU  - Lang-Schwarz C
AU  - Larsimont D
AU  - Lennerz JK
AU  - Lerousseau M
AU  - Li X
AU  - Ly A
AU  - Madabhushi A
AU  - Maley SK
AU  - Manur Narasimhamurthy V
AU  - Marks DK
AU  - McDonald ES
AU  - Mehrotra R
AU  - Michiels S
AU  - Minhas FUAA
AU  - Mittal S
AU  - Moore DA
AU  - Mushtaq S
AU  - Nighat H
AU  - Papathomas T
AU  - Penault-Llorca F
AU  - Perera RD
AU  - Pinard CJ
AU  - Pinto-Cardenas JC
AU  - Pruneri G
AU  - Pusztai L
AU  - Rahman A
AU  - Rajpoot NM
AU  - Rapoport BL
AU  - Rau TT
AU  - Reis-Filho JS
AU  - Ribeiro JM
AU  - Rimm D
AU  - Roslind A
AU  - Vincent-Salomon A
AU  - Salto-Tellez M
AU  - Saltz J
AU  - Sayed S
AU  - Scott E
AU  - Siziopikou KP
AU  - Sotiriou C
AU  - Stenzinger A
AU  - Sughayer MA
AU  - Sur D
AU  - Fineberg S
AU  - Symmans F
AU  - Tanaka S
AU  - Taxter T
AU  - Tejpar S
AU  - Teuwen J
AU  - Thompson EA
AU  - Tramm T
AU  - Tran WT
AU  - van der Laak J
AU  - van Diest PJ
AU  - Verghese GE
AU  - Viale G
AU  - Vieth M
AU  - Wahab N
AU  - Walter T
AU  - Waumans Y
AU  - Wen HY
AU  - Yang W
AU  - Yuan Y
AU  - Zin RM
AU  - Adams S
AU  - Bartlett J
AU  - Loibl S
AU  - Denkert C
AU  - Savas P
AU  - Loi S
AU  - Salgado R
AU  - Specht Stovgaard E
PY  - 2023
JO  - The Journal of pathology
DO  - 10.1002/path.6155
UR  - https://doi.org/10.1002/path.6155
ER  -

APA

J, T., G, B., DB, P., CA, J., S, V., Z, K., R, G., R, K., K, A., G, A. H., B, A., G, A., JS, A., I, A., M, A., F, A., S, B., NB, B., E, B., ER, B., V, B., KR, B., L, B. M. F., N, B., O, B., A, C., M, C. U. C., F, C., LA, C., A, C., G, C., AB, D., FL, D. P., F, D., S, D., J, D. H., SN, D., T, E., M, E., C, F., SB, F., WM, G., JM, G., S, G., PI, G., A, G., N, H., MG, H., A, H., SN, H., J, H., S, H., S, H., AI, H., HM, H., Z, H., E, H., S, I., EA, J., M, K., TR, K., K, K., D, K., AI, K., U, K., P, K., LL, K., K, K., A, K., AV, L., C, L., D, L., JK, L., M, L., X, L., A, L., A, M., SK, M., V, M. N., DK, M., ES, M., R, M., S, M., FUAA, M., S, M., DA, M., S, M., H, N., T, P., F, P., RD, P., CJ, P., JC, P., G, P., L, P., A, R., NM, R., BL, R., TT, R., JS, R., JM, R., D, R., A, R., A, V., M, S., J, S., S, S., E, S., KP, S., C, S., A, S., MA, S., D, S., S, F., F, S., S, T., T, T., S, T., J, T., EA, T., T, T., WT, T., J, V. D. L., PJ, V. D., GE, V., G, V., M, V., N, W., T, W., Y, W., HY, W., W, Y., Y, Y., RM, Z., S, A., J, B., S, L., C, D., P, S., S, L., R, S., & E, S. S. (2023). Pitfalls in machine learning-based assessment of tumor-infiltrating lymphocytes in breast cancer: A report of the International Immuno-Oncology Biomarker Working Group on Breast Cancer.. The Journal of pathology. https://doi.org/10.1002/path.6155

Source records

pubmed · retrieved 2026-09-25T03:35:32.856Z
hal · retrieved 2026-09-25T03:35:32.911Z