AIMC Topic: Machine Learning

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Developing a short-term prediction model for asthma exacerbations from Swedish primary care patients' data using machine learning - Based on the ARCTIC study.

Respiratory medicine
OBJECTIVE: The ability to predict impending asthma exacerbations may allow better utilization of healthcare resources, prevention of hospitalization and improve patient outcomes. We aimed to develop models using machine learning to predict risk of ex...

For whom should psychotherapy focus on problem coping? A machine learning algorithm for treatment personalization.

Psychotherapy research : journal of the Society for Psychotherapy Research
OBJECTIVE: We aimed to develop and test an algorithm for individual patient predictions of problem coping experiences (PCE) (i.e., patients' understanding and ability to deal with their problems) effects in cognitive-behavioral therapy. In an outpat...

Predictors of real-time fMRI neurofeedback performance and improvement - A machine learning mega-analysis.

NeuroImage
Real-time fMRI neurofeedback is an increasingly popular neuroimaging technique that allows an individual to gain control over his/her own brain signals, which can lead to improvements in behavior in healthy participants as well as to improvements of ...

Cost-sensitive learning for semi-supervised hit-and-run analysis.

Accident; analysis and prevention
Hit-and-run crashes not only degrade the morality, but also result in delays of medical services provided to victims. However, class imbalance problem exists as the number of hit-and-run crashes is much smaller than that of non-hit-and-run crashes. T...

Cortical Thickness from MRI to Predict Conversion from Mild Cognitive Impairment to Dementia in Parkinson Disease: A Machine Learning-based Model.

Radiology
Background Group comparison results associating cortical thinning and Parkinson disease (PD) dementia (PDD) are limited in their application to clinical settings. Purpose To investigate whether cortical thickness from MRI can help predict conversion ...

Transferable Ring Corrections for Predicting Enthalpy of Formation of Cyclic Compounds.

Journal of chemical information and modeling
Computational predictions of the thermodynamic properties of molecules and materials play a central role in contemporary reaction prediction and kinetic modeling. Due to the lack of experimental data and computational cost of high-level quantum chemi...

Prediction of Bedridden Duration of Hospitalized Patients by Machine Learning Based on EMRs at Admission.

Computers, informatics, nursing : CIN
Being bedridden is a frequent comorbid condition that leads to a series of complications in clinical practice. The present study aimed to predict bedridden duration of hospitalized patients based on EMR at admission by machine learning. The medical d...

Translational Applications of Artificial Intelligence and Machine Learning for Diagnostic Pathology in Lymphoid Neoplasms: A Comprehensive and Evolutive Analysis.

Biomolecules
Genomic analysis and digitalization of medical records have led to a big data scenario within hematopathology. Artificial intelligence and machine learning tools are increasingly used to integrate clinical, histopathological, and genomic data in lymp...

Prediction of Head Movement in 360-Degree Videos Using Attention Model.

Sensors (Basel, Switzerland)
In this paper, we propose a prediction algorithm, the combination of Long Short-Term Memory (LSTM) and attention model, based on machine learning models to predict the vision coordinates when watching 360-degree videos in a Virtual Reality (VR) or Au...