AIMC Topic: Machine Learning

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Machine Learning-Based Identification of Obesity from Positive and Unlabelled Electronic Health Records.

Studies in health technology and informatics
INTRODUCTION: Prevalence of overweight and obesity are increas- ing in the last decades, and with them, diseases and health conditions such as diabetes, hypertension or cardiovascular diseases. However, hos- pital databases usually do not record such...

Comparison of Unplanned 30-Day Readmission Prediction Models, Based on Hospital Warehouse and Demographic Data.

Studies in health technology and informatics
Anticipating unplanned hospital readmission episodes is a safety and medico-economic issue. We compared statistics (Logistic Regression) and machine learning algorithms (Gradient Boosting, Random Forest, and Neural Network) for predicting the risk of...

Negation Detection for Clinical Text Mining in Russian.

Studies in health technology and informatics
Developing predictive modeling in medicine requires additional features from unstructured clinical texts. In Russia, there are no instruments for natural language processing to cope with problems of medical records. This paper is devoted to a module ...

Machine Learning for Automatic Encoding of French Electronic Medical Records: Is More Data Better?

Studies in health technology and informatics
The encoding of Electronic Medical Records is a complex and time-consuming task. We report on a machine learning model for proposing diagnoses and procedures codes, from a large realistic dataset of 245 000 electronic medical records at the Universit...

Machine Learning Assisted Citation Screening for Systematic Reviews.

Studies in health technology and informatics
Evidence-based practice is highly dependent upon up-to-date systematic reviews (SR) for decision making. However, conducting and updating systematic reviews, especially the citation screening for identification of relevant studies, requires much huma...

Introducing New Measures of Inter- and Intra-Rater Agreement to Assess the Reliability of Medical Ground Truth.

Studies in health technology and informatics
In this paper, we present and discuss two new measures of inter- and intra-rater agreement to assess the reliability of the raters, and hence of their labeling, in multi-rater setings, which are common in the production of ground truth for machine le...

Emerging Concepts and Applied Machine Learning Research in Patients with Drug-Induced Repolarization Disorders.

Studies in health technology and informatics
The paper presents a review of current research to develop predictive models for automated detection of drug-induced repolarization disorders and shows a feasibility study for developing machine learning tools trained on massive multimodal datasets o...

Digitalisation of the Brief Visuospatial Memory Test-Revised and Evaluation with a Machine Learning Algorithm.

Studies in health technology and informatics
The disease multiple sclerosis (MS) is characterized by various neurological symptoms. This paper deals with a novel tool to assess cognitive dysfunction. The Brief Visuospatial Memory Test-Revised (BVMT-R) is a recognized method to measure optical r...

Blood Lactate Concentration Prediction in Critical Care.

Studies in health technology and informatics
Blood lactate concentration is a reliable risk indicator of deterioration in critical care requiring frequent blood sampling. However, lactate measurement is an invasive procedure that can increase risk of infections. Yet there is no clinical consens...

Evaluation of transfer learning of pre-trained CNNs applied to breast cancer detection on infrared images.

Applied optics
Breast cancer accounts for the highest number of female deaths worldwide. Early detection of the disease is essential to increase the chances of treatment and cure of patients. Infrared thermography has emerged as a promising technique for diagnosis ...