AIMC Journal:
Studies in health technology and informatics

Showing 231 to 240 of 1224 articles

Machine Learning-Based Predictive Models for Early Detection of Cardiovascular Diseases: A Study Utilizing Patient Samples from a Tertiary Health Promotion Center in Korea.

Studies in health technology and informatics
A machine learning model was developed for cardiovascular diseases prediction based on 21,118 patient checkups data from a tertiary medical institution in Seoul, Korea, collected between 2009 and 2021. XGBoost algorithm showed the highest predictive ...

Synthetic Generation of Patient Service Utilization Data: A Scalability Study.

Studies in health technology and informatics
To address privacy and ethical issues in using health data for machine learning, we evaluate the scalability of advanced synthetic data generation methods like GANs, VAEs, copulaGAN, and transformer models specifically for patient service utilization...

Enhancing Asthma Self-Management with Environmental Passive-Monitoring Data and Machine Learning-Based Predictions.

Studies in health technology and informatics
Monitoring enables timely action which is critical in avoiding asthma attacks. With the abundance of local weather and pollution data, when augmented with machine learning, it is becoming possible to replace traditional tedious active monitoring in c...

Term Candidate Generation to Enrich Clinical Terminologies with Large Language Models.

Studies in health technology and informatics
Annotated language resources derived from clinical routine documentation form an intriguing asset for secondary use case scenarios. In this investigation, we report on how such a resource can be leveraged to identify additional term candidates for a ...

On Entity Embeddings for Ordinal Features as Representation Learning in Recurrence Prediction of Urothelial Bladder Cancer.

Studies in health technology and informatics
BACKGROUND: Urothelial Bladder Cancer (UBC) is a common cancer with a high risk of recurrence, which is influenced by the TNM classification, grading, age, and other factors. Recent studies demonstrate reliable and accurate recurrence prediction usin...

Deep Learning Models for Health-Driven Forecasting of Indoor Temperatures in Heat Waves in Canada: An Exploratory Study Using Smart Thermostats.

Studies in health technology and informatics
In Canada, extreme heat occurrences present significant risks to public health, particularly for vulnerable groups like older individuals and those with pre-existing health conditions. Accurately predicting indoor temperatures during these events is ...

Deep Learning-Based Prediction of Daily COVID-19 Cases Using X (Twitter) Data.

Studies in health technology and informatics
Due to the importance of COVID-19 control, innovative methods for predicting cases using social network data are increasingly under attention. This study aims to predict confirmed COVID-19 cases using X (Twitter) social network data (tweets) and deep...

Performance of a NLP Tool for Text Classification from Orthopaedic Operative Reports, Using Data from the Large Network of Clinical Data Warehouses of the West of France: The HACRO-HUGORTHO Project.

Studies in health technology and informatics
Electronic health data concerning implantable medical devices (IMD) opens opportunities for dynamic real-world monitoring to assess associated risks related to implanted materials. Due to population ageing and expanding demands, total hip, knee, and ...

Leveraging Rule-Based NLP to Translate Textual Reports as Structured Inputs Automatically Processed by a Clinical Decision Support System.

Studies in health technology and informatics
Using clinical decision support systems (CDSSs) for breast cancer management necessitates to extract relevant patient data from textual reports which is a complex task although efficiently achieved by machine learning but black box methods. We propos...

SemOntoMap: A Hybrid Approach for Semantic Annotation of Clinical Texts.

Studies in health technology and informatics
This study addresses the challenge of leveraging free-text descriptions in Electronic Health Records (EHR) for clinical research and healthcare improvement. Despite the potential of this data, its direct interpretation by computers is limited. Semant...