Thomas Walter
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Previous Organizations / Institutes
The organizations / institutes from the scholar's other articles in the past ten years
Research Subjects
Thomas Walter has a total of 430 co-authors. Here are the top co-authors by number of shared publications:
- Marvin Lerousseau
Centre for Computational Biology, Mines Paris, PSL University, Paris, 75272, France; INSERM UMR900, Institut Curie, PSL University, Paris, 75005, France
38 shared publications - Grégoire Gessain
INSERM U1015, Gustave Roussy, Paris-Saclay University, Villejuif, France
34 shared publications - Ahmed-Amine Anzali
INSERM U1015, Gustave Roussy Cancer Campus, Bâtiment de Médecine Moléculaire, Villejuif, France
33 shared publications - Alexandre Sayadi
Centre de Recherche Sur L’inflammation, Université Paris-Cité, Inserm, UMR 1149, Paris, France
33 shared publications - Alix Marhic
Department of Oto-Rhino-Laryngology, Head and Neck Surgery, Institut Gustave Roussy, Rue Edouard Vaillant, 94805 Villejuif, France
33 shared publications - Anne Auperin
Gustave Roussy 4 Biostatistics and Epidemiology Office Inserm U1018 Oncostat, Ligue Contre le Cancer, University Paris-Saclay, Villejuif, France
33 shared publications
Latest Publications
- 9 October 2026
- Published by Springer Nature
- p. C1
Correction to: Robust Pan-Cancer Mitotic Figure Detection with YOLOv12
- 9 October 2026
- Published by Springer Nature
- p. C1
Correction to: Robust Pan-Cancer Mitotic Figure Detection with YOLOv12
- 2 July 2026
- Published by Springer Nature
- p. 26-36
Robust Pan-Cancer Mitotic Figure Detection with YOLOv12
- 2 July 2026
- Published by Springer Nature
- p. 26-36
Robust Pan-Cancer Mitotic Figure Detection with YOLOv12
- 2 July 2026
- Published by Springer Nature
- p. 15-25
Efficient Fine-Tuning of DINOv3 Pretrained on Natural Images for Atypical Mitotic Figure Classification
- 2 July 2026
- Published by Springer Nature
- p. 15-25
Efficient Fine-Tuning of DINOv3 Pretrained on Natural Images for Atypical Mitotic Figure Classification
- Open Access
- 17 June 2026
- Published by American Association for Cancer Research (AACR)
Supplementary Video S1 from TREM2-Expressing Multinucleated Giant Macrophages Are a Biomarker of Good Prognosis in Head and Neck Squamous Cell Carcinoma
Representative video of an isolated MGC in oral cavity SCC from GR cohort
- 17 June 2026
- Published by American Association for Cancer Research (AACR)
Open AccessSupplementary Video S1 from TREM2-Expressing Multinucleated Giant Macrophages Are a Biomarker of Good Prognosis in Head and Neck Squamous Cell Carcinoma
Representative video of an isolated MGC in oral cavity SCC from GR cohort
- Open Access
- 17 June 2026
- Published by American Association for Cancer Research (AACR)
Supplementary Videos Legends from TREM2-Expressing Multinucleated Giant Macrophages Are a Biomarker of Good Prognosis in Head and Neck Squamous Cell Carcinoma
Legends of the two videos S1 and S2
- 17 June 2026
- Published by American Association for Cancer Research (AACR)
Open AccessSupplementary Videos Legends from TREM2-Expressing Multinucleated Giant Macrophages Are a Biomarker of Good Prognosis in Head and Neck Squamous Cell Carcinoma
Legends of the two videos S1 and S2
- Open Access
- 17 June 2026
- Published by American Association for Cancer Research (AACR)
Supplementary Tables S1 to S7 from TREM2-Expressing Multinucleated Giant Macrophages Are a Biomarker of Good Prognosis in Head and Neck Squamous Cell Carcinoma
Clinical Tables and Statistical Analyses
- 17 June 2026
- Published by American Association for Cancer Research (AACR)
Open AccessSupplementary Tables S1 to S7 from TREM2-Expressing Multinucleated Giant Macrophages Are a Biomarker of Good Prognosis in Head and Neck Squamous Cell Carcinoma
Clinical Tables and Statistical Analyses
- Open Access
- 17 June 2026
- Published by American Association for Cancer Research (AACR)
Figure S7 from TREM2-Expressing Multinucleated Giant Macrophages Are a Biomarker of Good Prognosis in Head and Neck Squamous Cell Carcinoma
CosMx 64-plex human immuno-oncology protein panel
- 17 June 2026
- Published by American Association for Cancer Research (AACR)
Open AccessFigure S7 from TREM2-Expressing Multinucleated Giant Macrophages Are a Biomarker of Good Prognosis in Head and Neck Squamous Cell Carcinoma
CosMx 64-plex human immuno-oncology protein panel
- Open Access
- 17 June 2026
- Published by American Association for Cancer Research (AACR)
Figure S1 from TREM2-Expressing Multinucleated Giant Macrophages Are a Biomarker of Good Prognosis in Head and Neck Squamous Cell Carcinoma
Association between keratin, MGC and clinical outcome
- 17 June 2026
- Published by American Association for Cancer Research (AACR)
Open AccessFigure S1 from TREM2-Expressing Multinucleated Giant Macrophages Are a Biomarker of Good Prognosis in Head and Neck Squamous Cell Carcinoma
Association between keratin, MGC and clinical outcome
- Open Access
- 17 June 2026
- Published by American Association for Cancer Research (AACR)
Figure S9 from TREM2-Expressing Multinucleated Giant Macrophages Are a Biomarker of Good Prognosis in Head and Neck Squamous Cell Carcinoma
Microscopic visualization of MGC
- 17 June 2026
- Published by American Association for Cancer Research (AACR)
Open AccessFigure S9 from TREM2-Expressing Multinucleated Giant Macrophages Are a Biomarker of Good Prognosis in Head and Neck Squamous Cell Carcinoma
Microscopic visualization of MGC
- Open Access
- 17 June 2026
- Published by American Association for Cancer Research (AACR)
Figure S4 from TREM2-Expressing Multinucleated Giant Macrophages Are a Biomarker of Good Prognosis in Head and Neck Squamous Cell Carcinoma
Performances of the deep-learning cell detection model in TCGA cohorts (oral cavity, uterine cervix and larynx SCC) and GR cohorts (oral cavity SCC)
- 17 June 2026
- Published by American Association for Cancer Research (AACR)
Open AccessFigure S4 from TREM2-Expressing Multinucleated Giant Macrophages Are a Biomarker of Good Prognosis in Head and Neck Squamous Cell Carcinoma
Performances of the deep-learning cell detection model in TCGA cohorts (oral cavity, uterine cervix and larynx SCC) and GR cohorts (oral cavity SCC)