Application of artificial intelligence in orthodontics: current state and future perspectives
In recent years, there has been the notable emergency of artificial intelligence (AI) as a
transformative force in multiple domains, including orthodontics. This review aims to provide …
transformative force in multiple domains, including orthodontics. This review aims to provide …
Assessing the utility of large language models for phenotype-driven gene prioritization in the diagnosis of rare genetic disease
Phenotype-driven gene prioritization is fundamental to diagnosing rare genetic disorders.
While traditional approaches rely on curated knowledge graphs with phenotype-gene …
While traditional approaches rely on curated knowledge graphs with phenotype-gene …
A Systematic Review on Graph Neural Network-based Methods for Stock Market Forecasting
Financial technology (FinTech) is a field that uses artificial intelligence to automate financial
services. One area of FinTech is stock analysis, which aims to predict future stock prices to …
services. One area of FinTech is stock analysis, which aims to predict future stock prices to …
Few-shot learning-based human behavior recognition model
Scope The challenges of human behavior recognition based on sensor data often require
addressing the needs of various new users in real-world situations, which leads to difficulties …
addressing the needs of various new users in real-world situations, which leads to difficulties …
Physics-informed reinforcement learning for probabilistic wind power forecasting under extreme events
Y Liu, J Wang, L Liu - Applied Energy, 2024 - Elsevier
With wind power penetration increases, accurate and reliable wind power forecasting is
becoming gradually critical, and data driven model is a promising solution to implement this …
becoming gradually critical, and data driven model is a promising solution to implement this …
GPT for medical entity recognition in Spanish
Á García-Barragán, A González Calatayud… - Multimedia Tools and …, 2024 - Springer
In recent years, there has been a remarkable surge in the development of Natural Language
Processing (NLP) models, particularly in the realm of Named Entity Recognition (NER) …
Processing (NLP) models, particularly in the realm of Named Entity Recognition (NER) …
Dimensional measures of psychopathology in children and adolescents using large language models
Background To enable greater use of National Institute of Mental Health Research Domain
Criteria (RDoC) in real-world settings, we applied large language models (LLMs) to estimate …
Criteria (RDoC) in real-world settings, we applied large language models (LLMs) to estimate …
[HTML][HTML] Predicting ICU Readmission from Electronic Health Records via BERTopic with Long Short Term Memory Network Approach
CC Chiu, CM Wu, TN Chien, LJ Kao, C Li - Journal of Clinical Medicine, 2024 - mdpi.com
Background: The increasing rate of intensive care unit (ICU) readmissions poses significant
challenges in healthcare, impacting both costs and patient outcomes. Predicting patient …
challenges in healthcare, impacting both costs and patient outcomes. Predicting patient …
[HTML][HTML] Development and Validation of a Literature Screening Tool: Few-Shot Learning Approach in Systematic Reviews
P Wiwatthanasetthakarn, W Ponthongmak… - Journal of medical …, 2024 - jmir.org
Background Systematic reviews (SRs) are considered the highest level of evidence, but their
rigorous literature screening process can be time-consuming and resource-intensive. This is …
rigorous literature screening process can be time-consuming and resource-intensive. This is …
Learning to explain is a good biomedical few-shot learner
Motivation Significant progress has been achieved in biomedical text mining using deep
learning methods, which rely heavily on large amounts of high-quality data annotated by …
learning methods, which rely heavily on large amounts of high-quality data annotated by …