Ontario Institute for Cancer Research

Transparency and reproducibility in artificial intelligence

Benjamin Haibe‐Kains, George Alexandru Adam, Ahmed Hosny et al.

2020 · 489 Zit.

Assessing and mitigating the effects of class imbalance in machine learning with application to X-ray imaging

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ChatGPT usage in the Reactome curation process

Krishna Kumar Tiwari, Lisa Matthews, Bruce May et al.

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Leveraging domain knowledge for synthetic ultrasound image generation: a novel approach to rare disease AI detection

Mauro Mendez, F. Castillo, Linda Probyn et al.

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SCARF: Auto-Segmentation Clinical Acceptability & Reproducibility Framework for Benchmarking Essential Radiation Therapy Targets in Head and Neck Cancer

Joseph Marsilla, Jun Won Kim, Denis Tkachuck et al.

2022 · 2 Zit.

Development of Machine Learning Systems to Predict Cancer-Related Symptoms With Validation Across a Health Care System

Baijiang Yuan, Muammar Kabir, Jiang Chen He et al.

2025 · 1 Zit.

A practical framework for operationalising responsible and equitable artificial intelligence in health care: tackling bias, inequity, and implementation challenges

Mattea Welch, Benjamin Grant, Christopher Deutschman et al.

2026 · 0 Zit.

Using GPT-4 to Automate the Generation of Lay Summaries for Cancer Publications

Emma Purdie, Tony Yu, Jochen Weile et al.

2025 · 0 Zit.

2619P How clinicians decide – analyzing real-world practice patterns in metastatic renal cell carcinoma (mRCC) with machine learning: Results from the international metastatic renal cell carcinoma database consortium (IMDC)

David Maj, D. O'Sullivan, Martín Zarbá et al.

2025 · 0 Zit.

Evaluating data heterogeneity's impact on convolutional neural network performance in medical imaging

John Valen, Lucie Yang, Jacob Levman et al.

2026 · 0 Zit.