AIMC Topic: Language

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Improving Alzheimer's Disease Detection for Speech Based on Feature Purification Network.

Frontiers in public health
Alzheimer's disease (AD) is a neurodegenerative disease involving the decline of cognitive ability with illness progresses. At present, the diagnosis of AD mainly depends on the interviews between patients and doctors, which is slow, expensive, and s...

FlauBERT vs. CamemBERT: Understanding patient's answers by a French medical chatbot.

Artificial intelligence in medicine
In a number of circumstances, obtaining health-related information from a patient is time-consuming, whereas a chatbot interacting efficiently with that patient might help saving health care professional time and better assisting the patient. Making ...

Connecting Text Classification with Image Classification: A New Preprocessing Method for Implicit Sentiment Text Classification.

Sensors (Basel, Switzerland)
As a research hotspot in the field of natural language processing (NLP), sentiment analysis can be roughly divided into explicit sentiment analysis and implicit sentiment analysis. However, due to the lack of obvious emotion words in the implicit sen...

A Multilevel Transfer Learning Technique and LSTM Framework for Generating Medical Captions for Limited CT and DBT Images.

Journal of digital imaging
Medical image captioning has been recently attracting the attention of the medical community. Also, generating captions for images involving multiple organs is an even more challenging task. Therefore, any attempt toward such medical image captioning...

Leveraging Multi-source knowledge for Chinese clinical named entity recognition via relational graph convolutional network.

Journal of biomedical informatics
OBJECTIVE: External knowledge, such as lexicon of words in Chinese and domain knowledge graph (KG) of concepts, has been recently adopted to improve the performance of machine learning methods for named entity recognition (NER) as it can provide addi...

A multipurpose TNM stage ontology for cancer registries.

Journal of biomedical semantics
BACKGROUND: Population-based cancer registries are a critical reference source for the surveillance and control of cancer. Cancer registries work extensively with the internationally recognised TNM classification system used to stage solid tumours, b...

TraceBERT-A Feasibility Study on Reconstructing Spatial-Temporal Gaps from Incomplete Motion Trajectories via BERT Training Process on Discrete Location Sequences.

Sensors (Basel, Switzerland)
Trajectory data represent an essential source of information on travel behaviors and human mobility patterns, assuming a central role in a wide range of services related to transportation planning, personalized recommendation strategies, and resource...

Towards more patient friendly clinical notes through language models and ontologies.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Clinical notes are an efficient way to record patient information but are notoriously hard to decipher for non-experts. Automatically simplifying medical text can empower patients with valuable information about their health, while saving clinicians ...

Hybrid Ensemble-Rule Algorithm for Improved MEDLINE® Sentence Boundary Detection.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Sentence boundary detection (SBD) is a fundamental building block in the Natural Language Processing (NLP) pipeline. Incorrect SBD may impact subsequent processing stages resulting in decreased performance. In well-behaved corpora, a few simple rules...

Pea-KD: Parameter-efficient and accurate Knowledge Distillation on BERT.

PloS one
Knowledge Distillation (KD) is one of the widely known methods for model compression. In essence, KD trains a smaller student model based on a larger teacher model and tries to retain the teacher model's level of performance as much as possible. Howe...