Reimbursement in the age of generalist radiology artificial intelligence

S Dogra, E Silva, P Rajpurkar - npj Digital Medicine, 2024 - nature.com
We argue that generalist radiology artificial intelligence (GRAI) challenges current
healthcare reimbursement frameworks. Unlike narrow AI tools, GRAI's multi-task capabilities …

Current status and future directions of explainable artificial intelligence in medical imaging

SN Saw, YY Yan, KH Ng - European Journal of Radiology, 2024 - Elsevier
The inherent “black box” nature of AI algorithms presents a substantial barrier to the
widespread adoption of the technology in clinical settings, leading to a lack of trust among …

Computational pathology: an evolving concept

I Prassas, B Clarke, T Youssef, J Phlamon… - Clinical Chemistry and …, 2024 - degruyter.com
The initial enthusiasm about computational pathology (CP) and artificial intelligence (AI) was
that they will replace pathologists entirely on the way to fully automated diagnostics. It is …

[HTML][HTML] Two-Layer Retrieval-Augmented Generation Framework for Low-Resource Medical Question Answering Using Reddit Data: Proof-of-Concept Study

S Das, Y Ge, Y Guo, S Rajwal, JM Hairston… - Journal of Medical …, 2025 - jmir.org
Background The increasing use of social media to share lived and living experiences of
substance use presents a unique opportunity to obtain information on side effects, use …

Weak Supervision, Strong Results: Achieving High Performance in Intracranial Hemorrhage Detection with Fewer Annotation Labels

KA Wahid, D Fuentes - Radiology: Artificial Intelligence, 2024 - pubs.rsna.org
PhD student affiliated with The University of Texas Medical Scientist Training Program at
Houston. He is currently a postdoctoral fellow at The University of Texas MD Anderson …

The Role of Industry to Grow Clinical Artificial Intelligence Applications in Gastroenterology and Endoscopy

AL Chiang, H Hong - Gastrointestinal Endoscopy Clinics, 2025 - giendo.theclinics.com
Artificial intelligence (AI) is a broad term that describes a range of computational approaches
designed to mimic or simulate human cognitive functions, including making predictions and …

Two-layer retrieval augmented generation framework for low-resource medical question-answering: proof of concept using Reddit data

S Das, Y Ge, Y Guo, S Rajwal, JM Hairston… - arxiv preprint arxiv …, 2024 - arxiv.org
Retrieval augmented generation (RAG) provides the capability to constrain generative
model outputs, and mitigate the possibility of hallucination, by providing relevant in-context …

Advancements in Clinical Evaluation and Regulatory Frameworks for AI-Driven Software as a Medical Device (SaMD)

SR Yang, JT Chien, CY Lee - IEEE Open Journal of …, 2024 - ieeexplore.ieee.org
Owing to the rapid progress in artificial intelligence (AI) and the widespread use of
generative learning, the problem of sparse data has been solved effectively in various …