T. Brinker

T. Brinker, A. Ignatius, M. Haffner-Luntzer, 2017, FASEB journal : official publication of the Federation of American Societies for Experimental Biology.

EAT-Brazil Award for Tobacco Control: a brief description of its first edition.

Lucas Guimarães de Azevedo, T. Brinker, Breno Bernardes-Souza, 2019, Revista da Associacao Medica Brasileira.

A Dermatologist's Ammunition in the War Against Smoking: A Photoaging App

A. Enk, J. Klode, D. Schadendorf, 2017, Journal of medical Internet research.

Artificial Intelligence and Its Effect on Dermatologists’ Accuracy in Dermoscopic Melanoma Image Classification: Web-Based Survey Study

Roman C. Maron, R. Maron, M. Weichenthal, 2020, Journal of medical Internet research.

A Face-Aging App for Smoking Cessation in a Waiting Room Setting: Pilot Study in an HIV Outpatient Clinic

A. Enk, C. Berking, J. Klode, 2018, Journal of medical Internet research.

Education Against Tobacco (EAT): a quasi-experimental prospective evaluation of a multinational medical-student-delivered smoking prevention programme for secondary schools in Germany

T. Brinker, D. Groneberg, S. Stamm-Balderjahn, 2015, BMJ Open.

Patient Perception of Mobile Phone Apps for the Care and Prevention of Sexually Transmitted Diseases: Cross-Sectional Study

C. Berking, T. Brinker, M. Heppt, 2020, JMIR mHealth and uHealth.

A Face-Aging Smoking Prevention/Cessation Intervention for Nursery School Students in Germany: An Appearance-Focused Interventional Study

A. Enk, C. von Kalle, T. Brinker, 2018, International journal of environmental research and public health.

[External scientific evaluation of the first teledermatology app without direct patient contact in Germany (Online Dermatologist-AppDoc)].

J. Utikal, D. Schadendorf, C. von Kalle, 2020, Der Hautarzt; Zeitschrift fur Dermatologie, Venerologie, und verwandte Gebiete.

Teledermatology: Comparison of Store-and-Forward Versus Live Interactive Video Conferencing (Preprint)

A. Enk, J. Utikal, A. Hekler, 2018 .

[Computer-assisted skin cancer diagnosis : Is it time for artificial intelligence in clinical practice?]

T. Brinker, H. Kittler, T. Jutzi, 2020, Der Hautarzt; Zeitschrift fur Dermatologie, Venerologie, und verwandte Gebiete.

Deep learning can predict survival directly from histology in clear cell renal cell carcinoma

Jakob Nikolas Kather, J. Utikal, C. von Kalle, 2022, PloS one.

Photoaging Mobile Apps in School-Based Tobacco Prevention: The Mirroring Approach

T. Brinker, W. Seeger, Fabian Buslaff, 2016, Journal of medical Internet research.

Patient Perception of Mobile Phone Apps for the Care and Prevention of Sexually Transmitted Diseases: Cross-Sectional Study (Preprint)

C. Berking, T. Brinker, M. Heppt, 2019 .

Education Against Tobacco (EAT): a quasi-experimental prospective evaluation of a programme for preventing smoking in secondary schools delivered by medical students: a study protocol

T. Brinker, D. Groneberg, S. Stamm-Balderjahn, 2014, BMJ Open.

Facial-Aging Mobile Apps for Smoking Prevention in Secondary Schools in Brazil: Appearance-Focused Interventional Study

A. Enk, C. Berking, C. von Kalle, 2018, JMIR public health and surveillance.

2‐mm surgical margins are adequate for most basal cell carcinomas in Japanese: a retrospective multicentre study on 1000 basal cell carcinomas

T. Brinker, Y. Fujisawa, Y. Nakamura, 2020, Journal of the European Academy of Dermatology and Venereology : JEADV.

Effect of a Face-Aging Mobile App–Based Intervention on Skin Cancer Protection Behavior in Secondary Schools in Brazil

J. Utikal, J. Klode, D. Schadendorf, 2020, JAMA dermatology.

Model soups improve performance of dermoscopic skin cancer classifiers.

Jakob Nikolas Kather, R. Maron, J. Utikal, 2022, European journal of cancer.

Uncertainty Estimation in Medical Image Classification: Systematic Review

Jakob Nikolas Kather, A. Hekler, C. von Kalle, 2022, JMIR medical informatics.

Benchmarking common uncertainty estimation methods with histopathological images under domain shift and label noise

T. Brinker, Alexander Kurz, H. A. Mehrtens, 2023, 2301.01054.

A single-cell landscape of high-grade serous ovarian cancer

A. Regev, T. Brinker, P. Sorger, 2020, Nature Medicine.

The Value of Total Body Photography for the Early Detection of Melanoma: A Systematic Review

C. Berking, T. Brinker, M. Heppt, 2021, International journal of environmental research and public health.

The prognostic value of sentinel lymph nodes on distant metastasis-free survival in patients with high-risk squamous cell carcinoma.

J. Klode, D. Schadendorf, P. Jansen, 2019, European journal of cancer.

Deep learning in cancer pathology: a new generation of clinical biomarkers

Jakob Nikolas Kather, Titus Josef Brinker, Amelie Echle, 2020, British Journal of Cancer.

Integration of deep learning-based image analysis and genomic data in cancer pathology: A systematic review.

Jakob Nikolas Kather, A. Hekler, S. Fröhling, 2021, European journal of cancer.

Inhibition of Haspin kinase promotes cell-intrinsic and extrinsic anti-tumor activity.

D. Schadendorf, T. Brinker, P. Sorger, 2019, Cancer research.

Deep learning identifies inflamed fat as a risk factor for lymph node metastasis in early colorectal cancer

Jakob Nikolas Kather, T. Brinker, H. Grabsch, 2021, The Journal of pathology.

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

T. Brinker, H. Grabsch, J. Chang-Claude, 2022, ESMO open.

Gastrointestinal cancer classification and prognostication from histology using deep learning: Systematic review.

Jakob Nikolas Kather, J. Utikal, A. Hekler, 2021, European journal of cancer.

Salivary cortisol levels and anxiety in melanoma patients undergoing sentinel lymph node excision under local anesthesia versus general anesthesia: a prospective study

J. Klode, D. Schadendorf, P. Jansen, 2020, World Journal of Surgical Oncology.

A skin cancer prevention photoageing intervention for secondary schools in Brazil delivered by medical students: protocol for a randomised controlled trial

Dirk Schadendorf, Titus Josef Brinker, D. Schadendorf, 2018, BMJ Open.

A Skin Cancer Prevention Facial-Aging Mobile App for Secondary Schools in Brazil: Appearance-Focused Interventional Study

Sven Schneider, Wiebke Sondermann, Dirk Schadendorf, 2018, JMIR mHealth and uHealth.

Artificial Intelligence-based Detection of FGFR3 Mutational Status Directly from Routine Histology in Bladder Cancer: A Possible Preselection for Molecular Testing?

Jakob Nikolas Kather, T. Brinker, C. Trautwein, 2021, European urology focus.

Logistics Workers Are a Key Factor for SARS-CoV-2 Spread in Brazilian Small Towns: Case-Control Study

T. Brinker, A. B. Reis, D. Silva, 2021, JMIR public health and surveillance.

A Medical Student–Delivered Smoking Prevention Program, Education Against Tobacco, for Secondary Schools in Brazil: Study Protocol for a Randomized Trial

T. Brinker, D. Groneberg, W. Seeger, 2017, JMIR Research Protocols.

Skin cancer classification via convolutional neural networks: systematic review of studies involving human experts.

Jakob Nikolas Kather, Roman C. Maron, H. Haenssle, 2021, European journal of cancer.

Assessment of Nonradioactive Multispectral Optoacoustic Tomographic Imaging With Conventional Lymphoscintigraphic Imaging for Sentinel Lymph Node Biopsy in Melanoma

J. Klode, D. Schadendorf, P. Jansen, 2019, JAMA network open.

Artificial Intelligence and Its Effect on Dermatologists’ Accuracy in Dermoscopic Melanoma Image Classification: Web-Based Survey Study (Preprint)

R. Maron, M. Weichenthal, J. Utikal, 2020 .

Multimodal integration of image, epigenetic and clinical data to predict BRAF mutation status in melanoma.

J. Utikal, D. Schadendorf, T. Brinker, 2023, European journal of cancer.

Prediction of melanoma evolution in melanocytic nevi via artificial intelligence: A call for prospective data.

Carola Berking, Wiebke Sondermann, Dirk Schadendorf, 2019, European journal of cancer.

Deep learning outperformed 136 of 157 dermatologists in a head-to-head dermoscopic melanoma image classification task.

Achim Hekler, Carola Berking, Dirk Schadendorf, 2019, European journal of cancer.

A convolutional neural network trained with dermoscopic images performed on par with 145 dermatologists in a clinical melanoma image classification task.

Achim Hekler, Carola Berking, Dirk Schadendorf, 2019, European journal of cancer.

Comparing artificial intelligence algorithms to 157 German dermatologists: the melanoma classification benchmark.

Achim Hekler, Carola Berking, Dirk Schadendorf, 2019, European journal of cancer.

Swarm learning for decentralized artificial intelligence in cancer histopathology

Jakob Nikolas Kather, T. Brinker, T. Luedde, 2021, Nature Medicine.

Deep Learning for the detection of microsatellite instability from histology images in colorectal cancer: a systematic literature review

Jakob Nikolas Kather, T. Brinker, P. Boor, 2021, ImmunoInformatics.

Weakly supervised annotation‐free cancer detection and prediction of genotype in routine histopathology

Jakob Nikolas Kather, M. Kloor, T. Brinker, 2021, The Journal of pathology.

Deep learning approach to predict lymph node metastasis directly from primary tumour histology in prostate cancer

R. Maron, J. Utikal, A. Hekler, 2021, BJU international.

Deep learning detects genetic alterations in cancer histology generated by adversarial networks

Philip Quirke, Jakob Nikolas Kather, Peter Boor, 2021, The Journal of pathology.

Primary leiomyosarcoma of the skin: a comprehensive review on diagnosis and treatment

C. Berking, T. Brinker, M. Heppt, 2018, Medical Oncology.

Photoaging Mobile Apps in School-Based Melanoma Prevention: Pilot Study

Wiebke Sondermann, Dirk Schadendorf, Joachim Klode, 2017, Journal of medical Internet research.

Large-scale in-silico identification of a tumor-specific antigen pool for targeted immunotherapy in triple-negative breast cancer

T. Brinker, N. Grabe, N. Wentzensen, 2019, Oncotarget.

Robustness of convolutional neural networks in recognition of pigmented skin lesions.

Jakob Nikolas Kather, R. Maron, J. Utikal, 2021, European journal of cancer.

A Smoking Prevention Program Delivered by Medical Students to Secondary Schools in Brazil Called “Education Against Tobacco”: Randomized Controlled Trial

T. Brinker, Breno Bernardes-Souza, P. C. R. P. Corrêa, 2019, Journal of medical Internet research.

Patient Attitudes and Their Awareness Towards Skin Cancer–Related Apps: Cross-Sectional Survey

C. Berking, T. Brinker, M. Heppt, 2019, JMIR mHealth and uHealth.

Photoaging Mobile Apps as a Novel Opportunity for Melanoma Prevention: Pilot Study

Dirk Schadendorf, Joachim Klode, Titus Josef Brinker, 2017, JMIR mHealth and uHealth.

Combining CNN-based histologic whole slide image analysis and patient data to improve skin cancer classification.

Jakob Nikolas Kather, J. Utikal, A. Hekler, 2021, European journal of cancer.

Deep learning can predict lymph node status directly from histology in colorectal cancer.

Jakob Nikolas Kather, T. Holland-Letz, C. von Kalle, 2021, European journal of cancer.

Enhanced classifier training to improve precision of a convolutional neural network to identify images of skin lesions

Achim Hekler, Christof von Kalle, Titus J Brinker, 2019, PloS one.

Outperforming Dermatologist-Level Skin Cancer Classification via Enhanced Training of Deep Neural Networks (Preprint)

A. Hekler, C. von Kalle, T. Brinker, 2018 .

Psoriasis, cardiovascular risk factors and metabolic disorders: sex‐specific findings of a population‐based study

T. Brinker, W. Sondermann, S. Moebus, 2019, Journal of the European Academy of Dermatology and Venereology : JEADV.

Process Evaluation of a Medical Student–Delivered Smoking Prevention Program for Secondary Schools: Protocol for the Education Against Tobacco Cluster Randomized Trial

A. Enk, C. von Kalle, S. Fröhling, 2019, JMIR research protocols.

Protocol Process Evaluation of a Medical Student – Delivered Smoking Prevention Program for Secondary Schools : Protocol for the Education Against Tobacco Cluster Randomized Trial

Christof, A. Enk, S. Fröhling, 2019 .

Skin Cancer Classification Using Convolutional Neural Networks: Systematic Review

Achim Hekler, Carola Berking, Dirk Schadendorf, 2018, Journal of medical Internet research.

Orbital Blowout Fracture with Complete Dislocation of the Globe into the Maxillary Sinus

T. Brinker, R. Tubbs, M. Loukas, 2017, Cureus.

Evaluation of Long-term Clearance Rates of Interventions for Actinic Keratosis: A Systematic Review and Network Meta-analysis.

C. Berking, T. Brinker, M. Heppt, 2021, JAMA dermatology.

Photoaging smartphone app promoting poster campaign to reduce smoking prevalence in secondary schools: the Smokerface Randomized Trial: design and baseline characteristics

T. Brinker, N. Rigotti, A. Batra, 2016, BMJ Open.

Explainable artificial intelligence in skin cancer recognition: A systematic review.

Jakob Nikolas Kather, R. Maron, J. Utikal, 2022, European journal of cancer.

Digital Natives’ Preferences on Mobile Artificial Intelligence Apps for Skin Cancer Diagnostics: Survey Study

J. Utikal, T. Brinker, T. Jutzi, 2021, JMIR mHealth and uHealth.

2A-DUB/Mysm1 Regulates Epidermal Development in Part by Suppressing p53-Mediated Programs

T. Brinker, S. Kilo, A. Hainzl, 2018, International journal of molecular sciences.

Patient Attitudes and Their Awareness Towards Skin Cancer–Related Apps: Cross-Sectional Survey (Preprint)

C. Berking, T. Brinker, M. Heppt, 2019 .

A smoking prevention photoageing intervention for secondary schools in Brazil delivered by medical students: protocol for a randomised trial

J. Klode, D. Schadendorf, T. Brinker, 2017, BMJ Open.

Implementation of cell-free tumor DNA sequencing from the cerebrospinal fluid to guide treatment in a patient with primary leptomeningeal melanoma: A case report.

T. Brinker, J. Mier, Rohit Thummalapalli, 2018, Molecular and clinical oncology.

A benchmark for neural network robustness in skin cancer classification.

Jakob Nikolas Kather, R. Maron, J. Utikal, 2021, European Journal of Cancer.

Deep learning approach to predict sentinel lymph node status directly from routine histology of primary melanoma tumours.

Jakob Nikolas Kather, M. Weichenthal, J. Utikal, 2021, European journal of cancer.

Artificial Intelligence in Skin Cancer Diagnostics: The Patients' Perspective

R. Maron, J. Utikal, A. Hekler, 2020, Frontiers in Medicine.

Superior skin cancer classification by the combination of human and artificial intelligence.

Tim Holland-Letz, Achim Hekler, Carola Berking, 2019, European journal of cancer.

Integrating Patient Data Into Skin Cancer Classification Using Convolutional Neural Networks: Systematic Review

Jakob Nikolas Kather, R. Maron, J. Utikal, 2021, Journal of medical Internet research.

A Medical Student-Delivered Smoking Prevention Program, Education Against Tobacco, for Secondary Schools in Germany: Randomized Controlled Trial

J. Klode, D. Schadendorf, P. Jansen, 2017, Journal of medical Internet research.

Teledermatology: Comparison of Store-and-Forward Versus Live Interactive Video Conferencing

Achim Hekler, Carola Berking, Wiebke Sondermann, 2018, Journal of medical Internet research.

Artificial intelligence to predict oncological outcome directly from hematoxylin & eosin-stained slides in urology: a systematic review.

S. Fröhling, T. Brinker, Sara Kuntz, 2022, Minerva urology and nephrology.

Pathologist-level classification of histopathological melanoma images with deep neural networks.

Tim Holland-Letz, Achim Hekler, Carola Berking, 2019, European journal of cancer.

Facial-Aging App Availability in Waiting Rooms as a Potential Opportunity for Skin Cancer Prevention

Dirk Schadendorf, Titus J. Brinker, Joachim Klode, 2018, JAMA dermatology.

Generalizable biomarker prediction from cancer pathology slides with self-supervised deep learning: A retrospective multi-centric study

Jakob Nikolas Kather, T. Brinker, H. Grabsch, 2023, Cell reports. Medicine.

Effects of Label Noise on Deep Learning-Based Skin Cancer Classification

Benjamin Izar, Achim Hekler, Jakob N. Kather, 2020, Frontiers in Medicine.

Hidden Variables in Deep Learning Digital Pathology and Their Potential to Cause Batch Effects: Prediction Model Study

Jakob Nikolas Kather, R. Maron, M. Weichenthal, 2021, Journal of medical Internet research.

Using Multiple Dermoscopic Photographs of One Lesion Improves Melanoma Classification via Deep Learning: A Prognostic Diagnostic Accuracy Study

Jakob Nikolas Kather, R. Maron, J. Utikal, 2023, ArXiv.

Otto Mennicke (1876–) and the first description of skull base anomalies causing cerebellar tonsillar ectopia: one of the first mentions of the Chiari I malformation

T. Brinker, R. Tubbs, M. Loukas, 2017, Child's Nervous System.

Long-term recurrence rates of actinic keratosis: a systematic review and pooled analysis of randomized controlled trials.

C. Berking, T. Brinker, M. Heppt, 2021, Journal of the American Academy of Dermatology.

Domain shifts in dermoscopic skin cancer datasets: Evaluation of essential limitations for clinical translation

R. Maron, T. Brinker, Sireesha Chamarthi, 2023, New biotechnology.

Response to letter entitled: Re: Integration of deep learning-based image analysis and genomic data in cancer pathology: A systematic review.

Jakob Nikolas Kather, A. Hekler, S. Fröhling, 2022, European Journal of Cancer.

Diagnostic performance of artificial intelligence for histologic melanoma recognition compared to 18 international expert pathologists.

Jakob Nikolas Kather, J. Utikal, A. Hekler, 2021, Journal of the American Academy of Dermatology.

Photoaging Mobile Apps: A Novel Opportunity for Smoking Cessation?

T. Brinker, W. Seeger, 2015, Journal of medical Internet research.

Multi-domain stain normalization for digital pathology: A cycle-consistent adversarial network for whole slide images

T. Brinker, Tabea-Clara Bucher, Martin J. Hetz, 2023, Medical Image Anal..

A self-supervised vision transformer to predict survival from histopathology in renal cell carcinoma

J. Utikal, C. von Kalle, S. Fröhling, 2023, World Journal of Urology.

A 3-dimensional histology computer model of malignant melanoma and its implications for digital pathology

Jakob Nikolas Kather, J. Utikal, C. von Kalle, 2023, European Journal of Cancer.

Frequent Occurrence of NRAS and BRAF Mutations in Human Acral Naevi

J. Klode, D. Schadendorf, P. Jansen, 2019, Cancers.

Response to letter entitled: Re: Integration of deep learning-based image analysis and genomic data in cancer pathology: A systematic review.

Jakob Nikolas Kather, A. Hekler, S. Fröhling, 2022, European journal of cancer.

Benchmarking common uncertainty estimation methods with histopathological images under domain shift and label noise

T. Brinker, Alexander Kurz, H. A. Mehrtens, 2023, Medical Image Anal..

Reducing the Impact of Confounding Factors on Skin Cancer Classification via Image Segmentation: Technical Model Study

R. Maron, J. Utikal, A. Hekler, 2021, Journal of medical Internet research.

Patient-Centered Mobile Health Data Management Solution for the German Health Care System (The DataBox Project)

Daniela Richter, Christof von Kalle, Titus Josef Brinker, 2018, JMIR cancer.

Evaluating deep learning-based melanoma classification using immunohistochemistry and routine histology: A three center study

T. Brinker, M. Heppt, E. Krieghoff-Henning, 2023, PloS one.

Erratum to 'Benchmarking weakly-supervised deep learning pipelines for whole slide classification in computational pathology' Medical Image Analysis, Volume 79, July 2022, 102474

Ming Y. Lu, Jakob Nikolas Kather, T. Brinker, 2022, Medical Image Anal..

A convolutional neural network trained with dermoscopic images performed on par with 145 dermatologists in a clinical melanoma image classification task.

A. Enk, Therezia Bokor-Billmann, K. Buder-Bakhaya, 2019, European journal of cancer.

Intraoperative use of LIGHTVISION: a novel fluorescence navigation system using indocyanine green for sentinel lymph node biopsy in skin cancer patients

J. Klode, D. Schadendorf, P. Jansen, 2018, European Journal of Dermatology.

Photoaging Mobile Apps as a Novel Opportunity for Melanoma Prevention: Pilot Study

J. Klode, D. Schadendorf, P. Jansen, 2017, JMIR mHealth and uHealth.