AIMC Topic: Humans

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Publicly available machine learning models for identifying opioid misuse from the clinical notes of hospitalized patients.

BMC medical informatics and decision making
BACKGROUND: Automated de-identification methods for removing protected health information (PHI) from the source notes of the electronic health record (EHR) rely on building systems to recognize mentions of PHI in text, but they remain inadequate at e...

Development, Implementation, and Evaluation of a Personalized Machine Learning Algorithm for Clinical Decision Support: Case Study With Shingles Vaccination.

Journal of medical Internet research
BACKGROUND: Although clinical decision support (CDS) alerts are effective reminders of best practices, their effectiveness is blunted by clinicians who fail to respond to an overabundance of inappropriate alerts. An electronic health record (EHR)-int...

Identification of the Facial Features of Patients With Cancer: A Deep Learning-Based Pilot Study.

Journal of medical Internet research
BACKGROUND: Cancer has become the second leading cause of death globally. Most cancer cases are due to genetic mutations, which affect metabolism and result in facial changes.

Olle Höök Lectureship 2019: The changing world of stroke rehabilitation.

Journal of rehabilitation medicine
The paper presents a summary of the Olle Höök lecture, which was presented at the Baltic North-Sea Forum in Oslo, Sweden, in October 2019. The paper aims to provide a worldwide picture of stroke, developments in this field, and the evolution of strok...

Predicting Glaucoma before Onset Using Deep Learning.

Ophthalmology. Glaucoma
PURPOSE: To assess the accuracy of deep learning models to predict glaucoma development from fundus photographs several years before disease onset.

Deep learning in rare disease. Detection of tubers in tuberous sclerosis complex.

PloS one
OBJECTIVE: To develop and test a deep learning algorithm to automatically detect cortical tubers in magnetic resonance imaging (MRI), to explore the utility of deep learning in rare disorders with limited data, and to generate an open-access deep lea...

QUATgo: Protein quaternary structural attributes predicted by two-stage machine learning approaches with heterogeneous feature encoding.

PloS one
Many proteins exist in natures as oligomers with various quaternary structural attributes rather than as single chains. Predicting these attributes is an essential task in computational biology for the advancement of proteomics. However, the existing...

Prediction of Postoperative Length of Hospital Stay Based on Differences in Nursing Narratives in Elderly Patients with Epithelial Ovarian Cancer.

Methods of information in medicine
OBJECTIVES:  The current study sought to evaluate whether nursing narratives can be used to predict postoperative length of hospital stay (LOS) following curative surgery for ovarian cancer.

Analysis of Feature Extraction Methods for Prediction of 30-Day Hospital Readmissions.

Methods of information in medicine
OBJECTIVES:  This article aims to determine possible improvements made by feature extraction methods to the machine learning prediction methods for predicting 30-day hospital readmissions.

Machine Learning Classification Algorithms to Predict aGvHD following Allo-HSCT: A Systematic Review.

Methods of information in medicine
BACKGROUND:  The acute graft-versus-host disease (aGvHD) is the most important cause of mortality in patients receiving allogeneic hematopoietic stem cell transplantation. Given that it occurs at the stage of severe tissue damage, its diagnosis is la...