Roche (United Kingdom)

Clinical AI tools must convey predictive uncertainty for each individual patient

Christopher R. S. Banerji, Tapabrata Chakraborti, Chris Harbron et al.

2023 · 43 Zit.

irAE-GPT: Leveraging large language models to identify immune-related adverse events in electronic health records and clinical trial datasets

Cosmin A. Bejan, Michelle Wang, Sriram Venkateswaran et al.

2025 · 9 Zit.

Clinicians must participate in the development of multimodal AI

Christopher R. S. Banerji, Aroon Bhardwaj Shah, Ben Dabson et al.

2025 · 6 Zit.

Intraclass correlation metrics for the accuracy of algorithmic definitions in a computerized decision support system for supportive cancer care

Matti Aapro, Ivo Abraham, Karen MacDonald et al.

2007 · 5 Zit.

ARTIFICIAL INTELLIGENCE (AI) AS A TOOL TO IMPROVE PATIENT AWARENESS: EXPLORING THE PATIENT PERSPECTIVE

Raouef Ahmed Bichoo, Dorin Dumitru, Kartikae Grover et al.

2024 · 0 Zit.

Using Natural Language Processing to Explore Patient Perspectives on AI Avatars in Support Materials for Patients With Breast Cancer: Survey Study

Eleanor Cheese, Raouef Ahmed Bichoo, K. Grover et al.

2025 · 0 Zit.

KDD Health Day/DSHealth 2021: Joint KDD 2021 Health Day and 2021 KDD Workshop on Applied Data Science for Healthcare: State of XAI and Trustworthiness in Health

Fei Wang, Prithwish Chakraborty, Tao Xu et al.

2021 · 0 Zit.

122 Predicting progression of paediatric Chronic Kidney Disease using Machine Learning

Aliea Mahmood, Mandy Wan, Victoria Stevens et al.

2026 · 0 Zit.