Artificial Intelligence and Black‐Box Medical Decisions: Accuracy versus Explainability
AJ London - Hastings Center Report, 2019 - Wiley Online Library
Although decision‐making algorithms are not new to medicine, the availability of vast stores
of medical data, gains in computing power, and breakthroughs in machine learning are …
of medical data, gains in computing power, and breakthroughs in machine learning are …
Human-centered explainability for life sciences, healthcare, and medical informatics
Rapid advances in artificial intelligence (AI) and availability of biological, medical, and
healthcare data have enabled the development of a wide variety of models. Significant …
healthcare data have enabled the development of a wide variety of models. Significant …
Informing clinical assessment by contextualizing post-hoc explanations of risk prediction models in type-2 diabetes
Medical experts may use Artificial Intelligence (AI) systems with greater trust if these are
supported by 'contextual explanations' that let the practitioner connect system inferences to …
supported by 'contextual explanations' that let the practitioner connect system inferences to …
AI Explainability 360 Toolkit for Time-Series and Industrial Use Cases
With the growing adoption of AI, trust and explainability have become critical which has
attracted a lot of research attention over the past decade and has led to the development of …
attracted a lot of research attention over the past decade and has led to the development of …
Leveraging Clinical Context for User-Centered Explainability: A Diabetes Use Case
S Chari, P Chakraborty, M Ghalwash… - ar** Safe Automotive Deep Learning Systems for Image Classification
MM Karimi - 2022 - search.proquest.com
Deep Learning (DL) systems are increasingly being used in many safety-critical automotive
applications such as traffic sign recognition. Despite the great success of DL systems in …
applications such as traffic sign recognition. Despite the great success of DL systems in …