AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Semantics

Showing 471 to 480 of 1350 articles

Clear Filters

Joint Feature Synthesis and Embedding: Adversarial Cross-Modal Retrieval Revisited.

IEEE transactions on pattern analysis and machine intelligence
Recently, generative adversarial network (GAN) has shown its strong ability on modeling data distribution via adversarial learning. Cross-modal GAN, which attempts to utilize the power of GAN to model the cross-modal joint distribution and to learn c...

An Improved BERT and Syntactic Dependency Representation Model for Sentiment Analysis.

Computational intelligence and neuroscience
Text representation of social media is an important task for users' sentiment analysis. Utilizing the better representation, we can accurately acquire the real semantic information expressed by online users. However, existing works cannot achieve the...

Breast cancer histopathological images classification based on deep semantic features and gray level co-occurrence matrix.

PloS one
Breast cancer is regarded as the leading killer of women today. The early diagnosis and treatment of breast cancer is the key to improving the survival rate of patients. A method of breast cancer histopathological images recognition based on deep sem...

Translating medical image to radiological report: Adaptive multilevel multi-attention approach.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Medical imaging techniques are widely employed in disease diagnosis and treatment. A readily available medical report can be a useful tool in assisting an expert for investigating the patient's health. A radiologist can bene...

A catalogue with semantic annotations makes multilabel datasets FAIR.

Scientific reports
Multilabel classification (MLC) is a machine learning task where the goal is to learn to label an example with multiple labels simultaneously. It receives increasing interest from the machine learning community, as evidenced by the increasing number ...

Domain Adaptation Meets Zero-Shot Learning: An Annotation-Efficient Approach to Multi-Modality Medical Image Segmentation.

IEEE transactions on medical imaging
Due to the lack of properly annotated medical data, exploring the generalization capability of the deep model is becoming a public concern. Zero-shot learning (ZSL) has emerged in recent years to equip the deep model with the ability to recognize uns...

Painting Classification in Art Teaching under Machine Learning from the Perspective of Emotional Semantic Analysis.

Computational intelligence and neuroscience
This paper aims to explore the Painting Classification in art teaching under Machine Learning. Based on Emotional Semantics and Machine Learning, the Emotional Semantics of the traditional image are expounded. Firstly, Emotional Semantics are applied...

Deep parameter-free attention hashing for image retrieval.

Scientific reports
Deep hashing method is widely applied in the field of image retrieval because of its advantages of low storage consumption and fast retrieval speed. There is a defect of insufficiency feature extraction when existing deep hashing method uses the conv...

Emotion Analysis Model of Microblog Comment Text Based on CNN-BiLSTM.

Computational intelligence and neuroscience
Aiming at the problems of over reliance on labor and low generalization of traditional emotion analysis methods based on dictionary and machine learning, an emotion analysis model of microblog comment text based on deep learning is proposed. Firstly,...

Using DeepLab v3 + -based semantic segmentation to evaluate platelet activation.

Medical & biological engineering & computing
This research used DeepLab v3 + -based semantic segmentation to automatically evaluate the platelet activation process and count the number of platelets from scanning electron microscopy (SEM) images. Current activated platelet recognition and counti...