Advances in medical image analysis with vision transformers: a comprehensive review
The remarkable performance of the Transformer architecture in natural language processing
has recently also triggered broad interest in Computer Vision. Among other merits …
has recently also triggered broad interest in Computer Vision. Among other merits …
Vision-language models for medical report generation and visual question answering: A review
I Hartsock, G Rasool - Frontiers in Artificial Intelligence, 2024 - frontiersin.org
Medical vision-language models (VLMs) combine computer vision (CV) and natural
language processing (NLP) to analyze visual and textual medical data. Our paper reviews …
language processing (NLP) to analyze visual and textual medical data. Our paper reviews …
A generalist vision–language foundation model for diverse biomedical tasks
Traditional biomedical artificial intelligence (AI) models, designed for specific tasks or
modalities, often exhibit limited flexibility in real-world deployment and struggle to utilize …
modalities, often exhibit limited flexibility in real-world deployment and struggle to utilize …
Biomedgpt: A unified and generalist biomedical generative pre-trained transformer for vision, language, and multimodal tasks
Conventional task-and modality-specific artificial intelligence (AI) models are inflexible in
real-world deployment and maintenance for biomedicine. At the same time, the growing …
real-world deployment and maintenance for biomedicine. At the same time, the growing …
Artificial general intelligence for medical imaging analysis
Large-scale Artificial General Intelligence (AGI) models, including Large Language Models
(LLMs) such as ChatGPT/GPT-4, have achieved unprecedented success in a variety of …
(LLMs) such as ChatGPT/GPT-4, have achieved unprecedented success in a variety of …
Federated learning for healthcare applications
Due to the fast advancement of artificial intelligence (AI), centralized-based models have
become critical for healthcare tasks like in medical image analysis and human behavior …
become critical for healthcare tasks like in medical image analysis and human behavior …
CoTCoNet: An optimized coupled transformer-convolutional network with an adaptive graph reconstruction for leukemia detection
Background: Swift and accurate blood smear analyses are crucial for diagnosing leukemia
and other hematological malignancies. However, manual leukocyte count and …
and other hematological malignancies. However, manual leukocyte count and …
Chest X-ray Images for Lung Disease Detection Using Deep Learning Techniques: A Comprehensive Survey
MAA Al-qaness, J Zhu, D AL-Alimi, A Dahou… - … Methods in Engineering, 2024 - Springer
In medical imaging, the last decade has witnessed a remarkable increase in the availability
and diversity of chest X-ray (CXR) datasets. Concurrently, there has been a significant …
and diversity of chest X-ray (CXR) datasets. Concurrently, there has been a significant …
Improving adversarial robustness of medical imaging systems via adding global attention noise
Y Dai, Y Qian, F Lu, B Wang, Z Gu, W Wang… - Computers in Biology …, 2023 - Elsevier
Recent studies have found that medical images are vulnerable to adversarial attacks.
However, it is difficult to protect medical imaging systems from adversarial examples in that …
However, it is difficult to protect medical imaging systems from adversarial examples in that …
An efficient medical image classification network based on multi-branch CNN, token grouping Transformer and mixer MLP
S Liu, L Wang, W Yue - Applied Soft Computing, 2024 - Elsevier
In recent years, medical image classification techniques based on deep learning have made
remarkable achievements, but most of the current models sacrifice the efficiency of the …
remarkable achievements, but most of the current models sacrifice the efficiency of the …