AIMC Topic: Machine Learning

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Identifying Key Factors Associated with Assistive Technology Availability for Dementia Care Using Machine Learning.

Studies in health technology and informatics
This study explores the factors influencing the availability of assistive technology for people with dementia through the application of machine learning. The analysis identified key factors, including carer support, protective legislation, and acces...

Practical Approach for Evaluating Machine Learning Anomaly Detection Algorithms for Epidemic Early Warning Systems.

Studies in health technology and informatics
Anomaly detection methods in time series data can play a pivotal role in epidemic surveillance Early Warning Systems (EWS). Statistical and rules-based methods have been traditionally employed in such systems, but are challenged by data dynamics and ...

Assessment of Machine Learning Algorithms to Predict Medical Specialty Choice.

Studies in health technology and informatics
Equitable distribution of physicians across specialties is a significant public health challenge. While previous studies primarily relied on classic statistics models to estimate factors affecting medical students' career choices, this study explores...

Machine Learning-Based Hospital Readmission Prediction: A Comparative Analysis of Speciality-Specific vs. All-Specialities Models.

Studies in health technology and informatics
Hospital readmissions are a major challenge for healthcare systems, leading to increased costs and adverse patient outcomes. Predicting which patients are at risk of readmission is critical for improving care and optimizing resource allocation. This ...

Long Short-Term Memory Network for Accelerometer-Based Hypertension Classification.

Studies in health technology and informatics
This study investigates the application of a Long Short-Term Memory (LSTM) architecture for classifying hypertension using accelerometer data, specifically focusing on physical activity and sleep from the publicly available NHANES 2011-2012 dataset. ...

Domain Shift in Part-of-Speech Tagging.

Studies in health technology and informatics
This study highlights domain shift in dataset distributions that impact machine learning performance in clinical natural language processing, analyzing linguistic differences across clinical narratives, biomedical abstracts, and news articles in Engl...

Automating Performance Status Annotation in Oncology Using Llama-3.

Studies in health technology and informatics
This work explores the automated extraction of medical information from Dutch clinical notes using Llama-3 and a limited amount of annotations. We compared zero-, one- and few-shot learning for the extraction of performance status of patients with pa...

Using Machine Learning for the Fusion of Tumor Records on a Real-World Dataset.

Studies in health technology and informatics
Cancer registries collect multiple reports describing the same tumor, potentially leading to duplicate or conflicting values across different records. This complicates further use of cancer data. Data fusion addresses this issue by consolidating mult...

Federated Learning for Predictive Analytics in Weaning from Mechanical Ventilation.

Studies in health technology and informatics
Mechanical ventilation is crucial for critically ill patients in ICUs, requiring accurate weaning and extubations timing for optimal outcomes. Current prediction models struggle with generalizability across datasets like MIMIC-IV and eICU-CRD. We pro...

FLANDERS: Fast Learning COVID-19 Care System.

Studies in health technology and informatics
The COVID-19 pandemic highlighted the complexities of diagnosing and managing acute Respiratory Failure (RF). Early prediction of RF remains a key challenge, with no established tools currently available. This study developed a machine learning model...