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A Bi-level representation learning model for medical visual question answering.

Journal of biomedical informatics
Medical Visual Question Answering (VQA) targets at answering questions related to given medical images and it contains tremendous potential in healthcare services. However, researches on medical VQA are still facing challenges, particularly on how to...

Eliminating Data Duplication in CQA Platforms Using Deep Neural Model.

Computational intelligence and neuroscience
Primary research to detect duplicate question pairs within community-based question answering systems is based on datasets made of English questions only. This research put forward a solution to the problem of duplicate question detection by matching...

Regional Language Speech Recognition from Bone-Conducted Speech Signals through Different Deep Learning Architectures.

Computational intelligence and neuroscience
Bone-conducted microphone (BCM) senses vibrations from bones in the skull during speech to electrical audio signal. When transmitting speech signals, bone-conduction microphones (BCMs) capture speech signals based on the vibrations of the speaker's s...

Sentiment Analysis and Emotion Recognition from Speech Using Universal Speech Representations.

Sensors (Basel, Switzerland)
The study of understanding sentiment and emotion in speech is a challenging task in human multimodal language. However, in certain cases, such as telephone calls, only audio data can be obtained. In this study, we independently evaluated sentiment an...

Analysis of Cross-Cultural Communication in English Subjects and the Realization of Deep Learning Teaching.

Computational intelligence and neuroscience
In subject teaching, subject characteristics are the logical starting point for teaching development, and a deep understanding of subject characteristics is the basis for effective teaching. In practice, due to ignoring the cross-cultural understandi...

Bi-directional long short term memory-gated recurrent unit model for Amharic next word prediction.

PloS one
The next word prediction is useful for the users and helps them to write more accurately and quickly. Next word prediction is vital for the Amharic Language since different characters can be written by pressing the same consonants along with differen...

AdaDiag: Adversarial Domain Adaptation of Diagnostic Prediction with Clinical Event Sequences.

Journal of biomedical informatics
Early detection of heart failure (HF) can provide patients with the opportunity for more timely intervention and better disease management, as well as efficient use of healthcare resources. Recent machine learning (ML) methods have shown promising pe...

Evaluating Patients' Experiences with Healthcare Services: Extracting Domain and Language-Specific Information from Free-Text Narratives.

International journal of environmental research and public health
Evaluating patients’ experience and satisfaction often calls for analyses of free-text data. Language and domain-specific information extraction can reduce costly manual preprocessing and enable the analysis of extensive collections of experience-bas...

A pre-trained BERT for Korean medical natural language processing.

Scientific reports
With advances in deep learning and natural language processing (NLP), the analysis of medical texts is becoming increasingly important. Nonetheless, despite the importance of processing medical texts, no research on Korean medical-specific language m...

Design of Convolutional Neural Network Processor Based on FPGA Resource Multiplexing Architecture.

Sensors (Basel, Switzerland)
As CNNs are widely used in fields such as image classification and target detection, the total number of parameters and computation of the models is gradually increasing. In addition, the requirements on hardware resources and power consumption for d...