AIMC Topic: Humans

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Supporting vision-language model few-shot inference with confounder-pruned knowledge prompt.

Neural networks : the official journal of the International Neural Network Society
Vision-language models are pre-trained by aligning image-text pairs in a common space to deal with open-set visual concepts. Recent works adopt fixed or learnable prompts, i.e., classification weights are synthesized from natural language description...

ACformer: A unified transformer for arbitrary-frame image exposure correction.

Neural networks : the official journal of the International Neural Network Society
Both the single-image exposure correction (SEC) methods and multi-image exposure fusion (MEF) methods aim to obtain a well-exposed image, but from different number of input image(s). Despite their promising performance on the specific SEC or MEF task...

DCTCNet: Sequency discrete cosine transform convolution network for visual recognition.

Neural networks : the official journal of the International Neural Network Society
The discrete cosine transform (DCT) has been widely used in computer vision tasks due to its ability of high compression ratio and high-quality visual presentation. However, conventional DCT is usually affected by the size of transform region and res...

A Novel session-based recommendation system using capsule graph neural network.

Neural networks : the official journal of the International Neural Network Society
Session-based recommendation systems (SBRS) are essential for enhancing the customer experience, improving sales and loyalty, and providing the possibility to discover products in dynamic and real-world scenarios without needing user history. Despite...

Impact of Artificial Intelligence on Gastroenterology Trainee Education.

Gastrointestinal endoscopy clinics of North America
Artificial intelligence (AI) is transforming gastroenterology, particularly in endoscopy, which has a direct impact on trainees and their education. AI can serve as a valuable resource, providing real-time feedback and aiding in tasks like polyp dete...

Artificial Intelligence in Endoscopy Quality Measures.

Gastrointestinal endoscopy clinics of North America
Quality of gastrointestinal endoscopy is a major determinant of its effectiveness. Artificial intelligence (AI) has the potential to enhance quality monitoring and improve endoscopy outcomes. This article reviews the current literature on AI algorith...

The Role of Artificial Intelligence for Advanced Endoscopy.

Gastrointestinal endoscopy clinics of North America
Artificial intelligence (AI) application in gastroenterology has grown in the last decade and continues to evolve very rapidly. Early promising results have opened the door to explore its potential application to advanced endoscopy (AE). The aim of t...

Role of Artificial Intelligence in the Detection and Management of Premalignant and Malignant Lesions of the Esophagus and Stomach.

Gastrointestinal endoscopy clinics of North America
The advent of artificial intelligence (AI) and deep learning algorithms, particularly convolutional neural networks, promises to address pitfalls, bridging the care for patients at high risk with improved detection (computer-aided detection [CADe]) a...

Natural Language Processing in Gastroenterology: Current Applications and Future Directions.

Gastrointestinal endoscopy clinics of North America
Natural language processing (NLP), a branch of artificial intelligence, has rapidly gained importance in health care for converting unstructured clinical data into structured formats, enhancing decision-making, research, and patient care. Gastroenter...

Enhancing lesion detection in automated breast ultrasound using unsupervised multi-view contrastive learning with 3D DETR.

Medical image analysis
The inherent variability of lesions poses challenges in leveraging AI in 3D automated breast ultrasound (ABUS) for lesion detection. Traditional methods based on single scans have fallen short compared to comprehensive evaluations by experienced sono...