The current and future state of AI interpretation of medical images

P Rajpurkar, MP Lungren - New England Journal of Medicine, 2023 - Mass Medical Soc
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Algorithmic fairness in artificial intelligence for medicine and healthcare

RJ Chen, JJ Wang, DFK Williamson, TY Chen… - Nature biomedical …, 2023 - nature.com
In healthcare, the development and deployment of insufficiently fair systems of artificial
intelligence (AI) can undermine the delivery of equitable care. Assessments of AI models …

A systematic review of trustworthy and explainable artificial intelligence in healthcare: Assessment of quality, bias risk, and data fusion

AS Albahri, AM Duhaim, MA Fadhel, A Alnoor… - Information …, 2023 - Elsevier
In the last few years, the trend in health care of embracing artificial intelligence (AI) has
dramatically changed the medical landscape. Medical centres have adopted AI applications …

Heterogeneity and predictors of the effects of AI assistance on radiologists

F Yu, A Moehring, O Banerjee, T Salz, N Agarwal… - Nature Medicine, 2024 - nature.com
The integration of artificial intelligence (AI) in medical image interpretation requires effective
collaboration between clinicians and AI algorithms. Although previous studies demonstrated …

Med-unic: Unifying cross-lingual medical vision-language pre-training by diminishing bias

Z Wan, C Liu, M Zhang, J Fu, B Wang… - Advances in …, 2024 - proceedings.neurips.cc
The scarcity of data presents a critical obstacle to the efficacy of medical vision-language pre-
training (VLP). A potential solution lies in the combination of datasets from various language …

[HTML][HTML] Artificial intelligence in liver cancers: Decoding the impact of machine learning models in clinical diagnosis of primary liver cancers and liver cancer …

A Bakrania, N Joshi, X Zhao, G Zheng, M Bhat - Pharmacological research, 2023 - Elsevier
Liver cancers are the fourth leading cause of cancer-related mortality worldwide. In the past
decade, breakthroughs in the field of artificial intelligence (AI) have inspired development of …

Imitate: Clinical prior guided hierarchical vision-language pre-training

C Liu, S Cheng, M Shi, A Shah, W Bai… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
In the field of medical Vision-Language Pretraining (VLP), significant efforts have been
devoted to deriving text and image features from both clinical reports and associated …

Deep learning generates synthetic cancer histology for explainability and education

JM Dolezal, R Wolk, HM Hieromnimon… - NPJ precision …, 2023 - nature.com
Artificial intelligence methods including deep neural networks (DNN) can provide rapid
molecular classification of tumors from routine histology with accuracy that matches or …

[HTML][HTML] Explainable digital forensics AI: Towards mitigating distrust in AI-based digital forensics analysis using interpretable models

AA Solanke - Forensic science international: digital investigation, 2022 - Elsevier
The present level of skepticism expressed by courts, legal practitioners, and the general
public over Artificial Intelligence (AI) based digital evidence extraction techniques has been …

Towards evaluating explanations of vision transformers for medical imaging

P Komorowski, H Baniecki… - Proceedings of the IEEE …, 2023 - openaccess.thecvf.com
As deep learning models increasingly find applications in critical domains such as medical
imaging, the need for transparent and trustworthy decision-making becomes paramount …