Chang-Claude, Jenny

Deep learning can predict microsatellite instability directly from histology in gastrointestinal cancer

Kather, J. N., Pearson, A. T., Halama, N., Jäger, D., Krause, J., Loosen, S. H., Marx, A., Boor, P., Tacke, F., Neumann, U. P., et al. (2019) · Nature Medicine

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

Cited by 1,458

Predicting survival from colorectal cancer histology slides using deep learning: A retrospective multicenter study

Kather, J. N., Krisam, J., Charoentong, P., Luedde, T., Herpel, E., Weis, C.-A., Gaiser, T., Marx, A., Valous, N. A., Ferber, D., et al. (2019) · PLOS Medicine

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

Cited by 1,082

Associations of breast cancer risk factors with tumor subtypes: A pooled analysis from the breast cancer association consortium studies

Yang, X. R., Chang-Claude, J., Goode, E. L., Couch, F. J., Nevanlinna, H., Milne, R. L., Gaudet, M., Schmidt, M. K., Broeks, A., Cox, A., et al. (2011) · JNCI: Journal of the National Cancer Institute

Cancer Risks and FactorsBreast Cancer Treatment Studies

Cited by 691

Parent-of-origin-specific allelic associations among 106 genomic loci for age at menarche

Study, A. O. C., Perry, J. R. B., The GENICA Network, kConFab, Study, T. L. C., The InterAct Consortium, Early Growth Genetics (EGG) Consortium, Day, F., Elks, C. E., Sulem, P., et al. (2014) · Nature

Hypothalamic control of reproductive hormonesGenetic Associations and Epidemiology

Cited by 604

Genomic analyses identify hundreds of variants associated with age at menarche and support a role for puberty timing in cancer risk

Study, T. L. C., Day, F. R., The InterAct Consortium, kConFab/AOCS Investigators, Endometrial Cancer Association Consortium, Ovarian Cancer Association Consortium, PRACTICAL consortium, Thompson, D. J., Helgason, H., Chasman, D. I., et al. (2017) · Nature Genetics

Hypothalamic control of reproductive hormonesGenetic Associations and Epidemiology

Cited by 587

Accelerometry and physical activity questionnaires - a systematic review

Skender, S., Ose, J., Chang-Claude, J., Paskow, M., Brühmann, B., Siegel, E. M., Steindorf, K., & Ulrich, C. M. (2016) · BMC Public Health

Physical Activity and HealthContext-Aware Activity Recognition Systems

Cited by 449

Large-scale genomic analyses link reproductive aging to hypothalamic signaling, breast cancer susceptibility and BRCA1-mediated DNA repair

The PRACTICAL Consortium, Day, F. R., kConFab Investigators, AOCS Investigators, Scotland, G., EPIC-InterAct Consortium, Study, L. C., Ruth, K. S., Thompson, D. J., Lunetta, K. L., et al. (2015) · Nature Genetics

Genetic Associations and EpidemiologyBRCA gene mutations in cancer

Cited by 402

Clinical-Grade Detection of Microsatellite Instability in Colorectal Tumors by Deep Learning

Echle, A., Grabsch, H. I., Quirke, P., van den Brandt, P. A., West, N. P., Hutchins, G. G. A., Heij, L. R., Tan, X., Richman, S. D., Krause, J., et al. (2020) · Gastroenterology

Genetic factors in colorectal cancerAI in cancer detection

Cited by 376

Swarm learning for decentralized artificial intelligence in cancer histopathology

Saldanha, O. L., Quirke, P., West, N. P., James, J. A., Loughrey, M. B., Grabsch, H. I., Salto-Tellez, M., Alwers, E., Cifci, D., Ghaffari Laleh, N., et al. (2022) · Nature Medicine

AI in cancer detectionArtificial Intelligence in Healthcare and Education

Cited by 227

Age- and Tumor Subtype–Specific Breast Cancer Risk Estimates for CH EK 2 *1100delC Carriers

Schmidt, M. K., Hogervorst, F., van Hien, R., Cornelissen, S., Broeks, A., Adank, M. A., Meijers, H., Waisfisz, Q., Hollestelle, A., Schutte, M., et al. (2016) · Journal of Clinical Oncology

BRCA gene mutations in cancerBreast Lesions and Carcinomas

Cited by 173

Breast cancer risk variants at 6q25 display different phenotype associations and regulate ESR1, RMND1 and CCDC170

EMBRACE, Dunning, A. M., Collaborators, G. S., HEBON, kConFab Investigators, Michailidou, K., Kuchenbaecker, K. B., Thompson, D., French, J. D., Beesley, J., et al. (2016) · Nature Genetics

Genetic Associations and EpidemiologyEstrogen and related hormone effects

Cited by 161

Benefit finding and post-traumatic growth in long-term colorectal cancer survivors: prevalence, determinants, and associations with quality of life

Jansen, L., Hoffmeister, M., Chang-Claude, J., Brenner, H., & Arndt, V (2011) · British Journal of Cancer

Cancer survivorship and careChildhood Cancer Survivors' Quality of Life

Cited by 152

Artificial intelligence for detection of microsatellite instability in colorectal cancer—a multicentric analysis of a pre-screening tool for clinical application

Echle, A., Ghaffari Laleh, N., Quirke, P., Grabsch, H. I., Muti, H. S., Saldanha, O. L., Brockmoeller, S. F., van den Brandt, P. A., Hutchins, G. G. A., Richman, S. D., et al. (2022) · ESMO Open

AI in cancer detectionGenetic factors in colorectal cancer

Cited by 111

The association between dietary lignans, phytoestrogen-rich foods, and fiber intake and postmenopausal breast cancer risk: a German case-control study

Zaineddin, A. K., Buck, K., Vrieling, A., Heinz, J., Flesch-Janys, D., Linseisen, J., & Chang-Claude, J. (2012) · Nutrition and Cancer

Phytoestrogen effects and researchNutritional Studies and Diet

Cited by 90

Body mass index and breast cancer survival: a Mendelian randomization analysis

Guo, Q., Burgess, S., Turman, C., Bolla, M. K., Wang, Q., Lush, M., Abraham, J., Aittomäki, K., Andrulis, I. L., Apicella, C., et al. (2017) · International Journal of Epidemiology

Cancer Risks and FactorsGenetic Associations and Epidemiology

Cited by 64

N-acetyltransferase 2 phenotype, occupation, and bladder cancer risk: results from the EPIC cohort

Pesch, B., Gawrych, K., Rabstein, S., Weiss, T., Casjens, S., Rihs, H.-P., Ding, H., Angerer, J., Illig, T., Klopp, N., et al. (2013) · Cancer Epidemiology, Biomarkers & Prevention

Pharmacogenetics and Drug MetabolismCarcinogens and Genotoxicity Assessment

Cited by 35

Genetic modifiers of menopausal hormone replacement therapy and breast cancer risk: A genome-wide interaction study

Rudolph, A., Hein, R., Lindström, S., Beckmann, L., Behrens, S., Liu, J., Aschard, H., Bolla, M. K., Wang, J., Truong, T., et al. (2013) · Endocrine-Related Cancer

Genetic Associations and EpidemiologyMenopause: Health Impacts and Treatments

Cited by 28

A comprehensive evaluation of interaction between genetic variants and use of menopausal hormone therapy on mammographic density

Rudolph, A., Fasching, P. A., Behrens, S., Eilber, U., Bolla, M. K., Wang, Q., Thompson, D., Czene, K., Brand, J. S., Li, J., et al. (2015) · Breast Cancer Research

Digital Radiography and Breast ImagingGenetic Associations and Epidemiology

Cited by 24

Genetic variants in DNA repair genes as potential predictive markers for oxaliplatin chemotherapy in colorectal cancer

Kap, E. J., Seibold, P., Richter, S., Scherer, D., Habermann, N., Balavarca, Y., Jansen, L., Becker, N., Pfütze, K., Popanda, O., et al. (2015) · The Pharmacogenomics Journal

Genetic factors in colorectal cancerColorectal Cancer Treatments and Studies

Cited by 20

Pleiotropy-guided transcriptome imputation from normal and tumor tissues identifies candidate susceptibility genes for breast and ovarian cancer

Kar, S. P., Considine, D. P. C., Tyrer, J. P., Plummer, J. T., Chen, S., Dezem, F. S., Barbeira, A. N., Rajagopal, P. S., Rosenow, W. T., Moreno, F., et al. (2021) · Human Genetics and Genomics Advances

Genetic Associations and EpidemiologyBRCA gene mutations in cancer

Cited by 18

Dose-Response Relationship between Serum Retinol Levels and Survival in Patients with Colorectal Cancer: Results from the DACHS Study

Maalmi, H., Walter, V., Jansen, L., Owen, R. W., Ulrich, A., Schöttker, B., Chang-Claude, J., Hoffmeister, M., & Brenner, H. (2018) · Nutrients

Vitamin D Research StudiesColorectal Cancer Treatments and Studies

Cited by 16

Benchmarking artificial intelligence methods for end-to-end computational pathology

Laleh, N. G., Muti, H. S., Lavinia Loeffler, C. M., Echle, A., Saldanha, O. L., Mahmood, F., Lu, M. Y., Trautwein, C., Langer, R., Dislich, B., et al. (2021) · bioRxiv (Cold Spring Harbor Laboratory)

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

Cited by 13