AIMC Topic: Algorithms

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Claims-Based Algorithms for Identifying Patients With Pulmonary Hypertension: A Comparison of Decision Rules and Machine-Learning Approaches.

Journal of the American Heart Association
Background Real-world healthcare data are an important resource for epidemiologic research. However, accurate identification of patient cohorts-a crucial first step underpinning the validity of research results-remains a challenge. We developed and e...

EEG-Based Epilepsy Recognition via Multiple Kernel Learning.

Computational and mathematical methods in medicine
In the field of brain-computer interfaces, it is very common to use EEG signals for disease diagnosis. In this study, a style regularized least squares support vector machine based on multikernel learning is proposed and applied to the recognition of...

Predicting Procedure Step Performance From Operator and Text Features: A Critical First Step Toward Machine Learning-Driven Procedure Design.

Human factors
OBJECTIVE: The goal of this study is to assess machine learning for predicting procedure performance from operator and procedure characteristics.

Practical applications of deep learning: classifying the most common categories of plain radiographs in a PACS using a neural network.

European radiology
OBJECTIVES: The goal of the present study was to classify the most common types of plain radiographs using a neural network and to validate the network's performance on internal and external data. Such a network could help improve various radiologica...

Deep convolutional neural network recovers pure absorbance spectra from highly scatter-distorted spectra of cells.

Journal of biophotonics
Infrared spectroscopy of cells and tissues is prone to Mie scattering distortions, which grossly obscure the relevant chemical signals. The state-of-the-art Mie extinction extended multiplicative signal correction (ME-EMSC) algorithm is a powerful to...

Application of artificial intelligence models and optimization algorithms in plant cell and tissue culture.

Applied microbiology and biotechnology
Artificial intelligence (AI) models and optimization algorithms (OA) are broadly employed in different fields of technology and science and have recently been applied to improve different stages of plant tissue culture. The usefulness of the applicat...

Multi-view radiomics and dosiomics analysis with machine learning for predicting acute-phase weight loss in lung cancer patients treated with radiotherapy.

Physics in medicine and biology
We propose a multi-view data analysis approach using radiomics and dosiomics (R&D) texture features for predicting acute-phase weight loss (WL) in lung cancer radiotherapy. Baseline weight of 388 patients who underwent intensity modulated radiation t...

THEIA™ development, and testing of artificial intelligence-based primary triage of diabetic retinopathy screening images in New Zealand.

Diabetic medicine : a journal of the British Diabetic Association
AIM: To develop and evaluate an artificial intelligence triage system with high sensitivity for detecting referable diabetic retinopathy and maculopathy, while maintaining high specificity for non-referable disease, for clinical implementation within...

DeepRescore: Leveraging Deep Learning to Improve Peptide Identification in Immunopeptidomics.

Proteomics
The identification of major histocompatibility complex (MHC)-binding peptides in mass spectrometry (MS)-based immunopeptideomics relies largely on database search engines developed for proteomics data analysis. However, because immunopeptidomics expe...

Reinforcement Learning Based Fast Self-Recalibrating Decoder for Intracortical Brain-Machine Interface.

Sensors (Basel, Switzerland)
BACKGROUND: For the nonstationarity of neural recordings in intracortical brain-machine interfaces, daily retraining in a supervised manner is always required to maintain the performance of the decoder. This problem can be improved by using a reinfor...