AIMC Topic: Machine Learning

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Development of a Computer-Aided Dosage and Telemonitoring System for Patients Under Oral Anticoagulation Therapy.

Studies in health technology and informatics
In this paper, we present a system that allows patients who require anticoagulation medicine an opportunity to independently manage their dosage concentration with the help of two machine learning algorithms. The basic idea is to predict the next dos...

Automated Error Detection in Physiotherapy Training.

Studies in health technology and informatics
BACKGROUND: Manual skills teaching, such as physiotherapy education, requires immediate teacher feedback for the students during the learning process, which to date can only be performed by expert trainers.

Cleansing and Imputation of Body Mass Index Data and Its Impact on a Machine Learning Based Prediction Model.

Studies in health technology and informatics
BACKGROUND: A challenge of using electronic health records for secondary analyses is data quality. Body mass index (BMI) is an important predictor for various diseases but often not documented properly.

A New Machine Learning Framework for Understanding the Link Between Cannabis Use and First-Episode Psychosis.

Studies in health technology and informatics
Lately, several studies started to investigate the existence of links between cannabis use and psychotic disorders. This work proposes a refined Machine Learning framework for understanding the links between cannabis use and 1st episode psychosis. Th...

Classification of single-channel EEG signals for epileptic seizures detection based on hybrid features.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Epilepsy is a common chronic neurological disorder of the brain. Clinically, epileptic seizures are usually detected via the continuous monitoring of electroencephalogram (EEG) signals by experienced neurophysiologists.

Objective Prediction of Hearing Aid Benefit Across Listener Groups Using Machine Learning: Speech Recognition Performance With Binaural Noise-Reduction Algorithms.

Trends in hearing
The simulation framework for auditory discrimination experiments (FADE) was adopted and validated to predict the individual speech-in-noise recognition performance of listeners with normal and impaired hearing with and without a given hearing-aid alg...

Probabilistic and machine learning-based retrieval approaches for biomedical dataset retrieval.

Database : the journal of biological databases and curation
The bioCADDIE dataset retrieval challenge brought together different approaches to retrieval of biomedical datasets relevant to a user’s query, expressed as a text description of a needed dataset. We describe experiments in applying a data-driven, ma...

Selection of Semantic Relevant Healthcare Services Subsets.

Studies in health technology and informatics
We describe an approach to select semantically coherent specialty subsets based on the historical use of terminology by different service areas. Our approach uses rule-based and machine learning techniques to obtain a reduced set of 29 specialties.

Applications of Machine Learning in Fatty Live Disease Prediction.

Studies in health technology and informatics
: Fatty liver disease (FLD) is considered the most prevalent form of chronic liver disease worldwide. The prediction of fatty liver disease is an important factor for effective treatment and reduce serious health consequences. We, therefore construct...

Impact of Imputing Missing Data in Bayesian Network Structure Learning for Obstructive Sleep Apnea Diagnosis.

Studies in health technology and informatics
Numerous diagnostic decisions are made every day by healthcare professionals. Bayesian networks can provide a useful aid to the process, but learning their structure from data generally requires the absence of missing data, a common problem in medica...