Titus J. Brinker

Orcid: 0000-0002-3620-5919

According to our database1, Titus J. Brinker authored at least 18 papers between 2022 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Links

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Bibliography

2024
Multi-domain stain normalization for digital pathology: A cycle-consistent adversarial network for whole slide images.
Medical Image Anal., 2024

Pathologist-like explainable AI for interpretable Gleason grading in prostate cancer.
CoRR, 2024

Dermatologist-like explainable AI enhances melanoma diagnosis accuracy: eye-tracking study.
CoRR, 2024

Prompt Injection Attacks on Large Language Models in Oncology.
CoRR, 2024

Superhuman performance in urology board questions by an explainable large language model enabled for context integration of the European Association of Urology guidelines: the UroBot study.
CoRR, 2024

Advancing dermatological diagnosis: Development of a hyperspectral dermatoscope for enhanced skin imaging.
CoRR, 2024

Clinical Melanoma Diagnosis with Artificial Intelligence: Insights from a Prospective Multicenter Study.
CoRR, 2024

2023
Benchmarking common uncertainty estimation methods with histopathological images under domain shift and label noise.
Medical Image Anal., October, 2023

On the calibration of neural networks for histological slide-level classification.
CoRR, 2023

Mitigating the Influence of Domain Shift in Skin Lesion Classification: A Benchmark Study of Unsupervised Domain Adaptation Methods on Dermoscopic Images.
CoRR, 2023

Evaluating Deep Learning-based Melanoma Classification using Immunohistochemistry and Routine Histology: A Three Center Study.
CoRR, 2023

Using Multiple Dermoscopic Photographs of One Lesion Improves Melanoma Classification via Deep Learning: A Prognostic Diagnostic Accuracy Study.
CoRR, 2023

Domain shifts in dermoscopic skin cancer datasets: Evaluation of essential limitations for clinical translation.
CoRR, 2023

Dermatologist-like explainable AI enhances trust and confidence in diagnosing melanoma.
CoRR, 2023

Pitfalls of Conformal Predictions for Medical Image Classification.
Proceedings of the Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, 2023

Test Time Augmentation Meets Post-hoc Calibration: Uncertainty Quantification under Real-World Conditions.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

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

Benchmarking weakly-supervised deep learning pipelines for whole slide classification in computational pathology.
Medical Image Anal., 2022


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