OpenAlex · Aktualisierung stündlich · Letzte Aktualisierung: 25.03.2026, 00:54

Benjamin Haibe‐Kains

1.168 Arbeiten38.772 Zitationen

University of Toronto · CA

Relevante Arbeiten

Meistzitierte Publikationen im Bereich Gesundheit & MedTech

Transparency and reproducibility in artificial intelligence

2020 · 474 Zit. · Nature

Why imaging data alone is not enough: AI-based integration of imaging, omics, and clinical data

2019 · 136 Zit. · European Journal of Nuclear Medicine and Molecular Imaging

Use of artificial intelligence for cancer clinical trial enrollment: a systematic review and meta-analysis

2023 · 46 Zit. · JNCI Journal of the National Cancer Institute

CovidCTNet: An Open-Source Deep Learning Approach to Identify Covid-19 Using CT Image

2020 · 42 Zit. · arXiv (Cornell University)

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

2022 · 2 Zit.

Med-ImageTools: An open-source Python package for robust data processing pipelines and curating medical imaging data

2023 · 2 Zit. · F1000Research

Med-ImageTools: An open-source Python package for robust data processing pipelines and curating medical imaging data

2024 · 2 Zit. · F1000Research

Health Data Nexus: an open data platform for AI research and education in medicine

2025 · 1 Zit. · GigaScience

Abstract PR-04: A practical framework for operationalizing responsible and equitable AI in healthcare: Tackling bias, inequity, and implementation challenges

2025 · 1 Zit. · Clinical Cancer Research

Supplementary Data from Multi-institutional prognostic modelling in head and neck cancer:evaluating impact and generalizability of deep learning and radiomics

2023 · 0 Zit.

Supplementary Figure S2 from Multi-institutional prognostic modelling in head and neck cancer:evaluating impact and generalizability of deep learning and radiomics

2023 · 0 Zit.

TABLE 1 from Multi-institutional Prognostic Modeling in Head and Neck Cancer: Evaluating Impact and Generalizability of Deep Learning and Radiomics

2023 · 0 Zit.

Supplementary Figure S1 from Multi-institutional Prognostic Modeling in Head and Neck Cancer: Evaluating Impact and Generalizability of Deep Learning and Radiomics

2023 · 0 Zit.

Supplementary Figure S1 from Multi-institutional prognostic modelling in head and neck cancer:evaluating impact and generalizability of deep learning and radiomics

2023 · 0 Zit.

Supplementary Figure S3 from Multi-institutional prognostic modelling in head and neck cancer:evaluating impact and generalizability of deep learning and radiomics

2023 · 0 Zit.