Explainable AI in medical imaging: An overview for clinical practitioners–Beyond saliency-based XAI approaches
K Borys, YA Schmitt, M Nauta, C Seifert… - European journal of …, 2023 - Elsevier
Driven by recent advances in Artificial Intelligence (AI) and Computer Vision (CV), the
implementation of AI systems in the medical domain increased correspondingly. This is …
implementation of AI systems in the medical domain increased correspondingly. This is …
Biomedical question answering: a survey of approaches and challenges
Automatic Question Answering (QA) has been successfully applied in various domains such
as search engines and chatbots. Biomedical QA (BQA), as an emerging QA task, enables …
as search engines and chatbots. Biomedical QA (BQA), as an emerging QA task, enables …
Mmbert: Multimodal bert pretraining for improved medical vqa
Images in the medical domain are fundamentally different from the general domain images.
Consequently, it is infeasible to directly employ general domain Visual Question Answering …
Consequently, it is infeasible to directly employ general domain Visual Question Answering …
Multiple meta-model quantifying for medical visual question answering
Transfer learning is an important step to extract meaningful features and overcome the data
limitation in the medical Visual Question Answering (VQA) task. However, most of the …
limitation in the medical Visual Question Answering (VQA) task. However, most of the …
Medical visual question answering: A survey
Abstract Medical Visual Question Answering (VQA) is a combination of medical artificial
intelligence and popular VQA challenges. Given a medical image and a clinically relevant …
intelligence and popular VQA challenges. Given a medical image and a clinically relevant …
Open-ended medical visual question answering through prefix tuning of language models
T Van Sonsbeek, MM Derakhshani… - … Conference on Medical …, 2023 - Springer
Abstract Medical Visual Question Answering (VQA) is an important challenge, as it would
lead to faster and more accurate diagnoses and treatment decisions. Most existing methods …
lead to faster and more accurate diagnoses and treatment decisions. Most existing methods …
MedFuseNet: An attention-based multimodal deep learning model for visual question answering in the medical domain
D Sharma, S Purushotham, CK Reddy - Scientific Reports, 2021 - nature.com
Medical images are difficult to comprehend for a person without expertise. The scarcity of
medical practitioners across the globe often face the issue of physical and mental fatigue …
medical practitioners across the globe often face the issue of physical and mental fatigue …
Cross-modal self-attention with multi-task pre-training for medical visual question answering
Due to the severe lack of labeled data, existing methods of medical visual question
answering usually rely on transfer learning to obtain effective image feature representation …
answering usually rely on transfer learning to obtain effective image feature representation …
Surface defect detection of steel strips based on classification priority YOLOv3-dense network
The steel strip is an essential raw material in the machinery industry. Besides, the surface
defects of the steel strip directly determine its performance. To achieve rapid and effective …
defects of the steel strip directly determine its performance. To achieve rapid and effective …
Improving visual question answering for bridge inspection by pre‐training with external data of image–text pairs
T Kunlamai, T Yamane, M Suganuma… - … ‐Aided Civil and …, 2024 - Wiley Online Library
This paper explores the application of visual question answering (VQA) in bridge inspection
using recent advancements in multimodal artificial intelligence (AI) systems. VQA involves …
using recent advancements in multimodal artificial intelligence (AI) systems. VQA involves …