AIMC Topic: Machine Learning

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Design of a Digital Twin of the Heart for the Management of Heart Failure Patients.

Studies in health technology and informatics
Heart failure poses a significant global health burden with high prevalence and mortality rates. A promising possibility in this context is the constant monitoring of the patients through telemedicine. The aim of this work is to present a digital twi...

Machine Learning upon RDF Knowledge Graphs for Drug Safety: A Case Study on Reactome Data.

Studies in health technology and informatics
Artificial Intelligence (AI), particularly Machine Learning (ML), has gained attention for its potential in various domains. However, approaches integrating symbolic AI with ML on Knowledge Graphs have not gained significant focus yet. We argue that ...

Advancing Cardiovascular Mortality Trend Analysis: A Machine Learning Approach to Predict Future Health Policy Needs.

Studies in health technology and informatics
This study investigates the forecasting of cardiovascular mortality trends in Greece's elderly population. Utilizing mortality data from 2001 to 2020, we employ two forecasting models: the Autoregressive Integrated Moving Average (ARIMA) and Facebook...

Comparative Analysis of Macular and Optic Disc Perfusion Pre and Post Silicone Oil Removal: A Machine Learning Approach.

Studies in health technology and informatics
In the realm of ophthalmic surgeries, silicone oil is often utilized as a tamponade agent for repairing retinal detachments, but it necessitates subsequent removal. This study harnesses the power of machine learning to analyze the macular and optic d...

A Novel Method and Python Library for ECG Signal Quality Assessment.

Studies in health technology and informatics
Electrocardiogram (ECG) is one of the reference cardiovascular diagnostic exams. However, the ECG signal is very prone to being distorted through different sources of artifacts that can later interfere with the diagnostic. For this reason, signal qua...

Exploring Explainable AI Techniques for Text Classification in Healthcare: A Scoping Review.

Studies in health technology and informatics
Text classification plays an essential role in the medical domain by organizing and categorizing vast amounts of textual data through machine learning (ML) and deep learning (DL). The adoption of Artificial Intelligence (AI) technologies in healthcar...

Application of Artificial Intelligence in Clinical Practice - Perception of a Multinational Group of Nephrologists.

Studies in health technology and informatics
This study investigates the perception of a multinational group of nephrologists on artificial intelligence (AI) application in clinical practice. A validated on-line survey was performed in March 2024, in 4 continents. The results revealed a prevale...

Multi-Objective Performance Optimization of Machine Learning Models in Healthcare.

Studies in health technology and informatics
Multi-objective optimization holds particular significance for medical applications, wherein enhancing sensitivity is crucial to avoid costly missed diagnoses, and maintaining high specificity is imperative to prevent unnecessary procedures. In parti...

From EHR to Machine Learning: A Preliminary Report on an Ingestion Pipeline Based on JSON-LD.

Studies in health technology and informatics
In this paper, we present the preliminary experiments for the development of an ingestion mechanism to move data from Electronic Health Records to machine learning processes, based on the concept of Linked Data and the JSON-LD format.

How Trueness of Clinical Decision Support Systems Based on Machine Learning Is Assessed?

Studies in health technology and informatics
The application of machine learning algorithms in clinical decision support systems (CDSS) holds great promise for advancing patient care, yet practical implementation faces significant evaluation challenges. Through a scoping review, we investigate ...