AIMC Topic: Algorithms

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DeepNetBim: deep learning model for predicting HLA-epitope interactions based on network analysis by harnessing binding and immunogenicity information.

BMC bioinformatics
BACKGROUND: Epitope prediction is a useful approach in cancer immunology and immunotherapy. Many computational methods, including machine learning and network analysis, have been developed quickly for such purposes. However, regarding clinical applic...

Pain Assessment Tool With Electrodermal Activity for Postoperative Patients: Method Validation Study.

JMIR mHealth and uHealth
BACKGROUND: Accurate, objective pain assessment is required in the health care domain and clinical settings for appropriate pain management. Automated, objective pain detection from physiological data in patients provides valuable information to hosp...

Against spatial-temporal discrepancy: contrastive learning-based network for surgical workflow recognition.

International journal of computer assisted radiology and surgery
PURPOSE: Automatic workflow recognition from surgical videos is fundamental and significant for developing context-aware systems in modern operating rooms. Although many approaches have been proposed to tackle challenges in this complex task, there a...

Design of a soft sensing technique for measuring pitch and yaw angular positions for a Twin Rotor MIMO System.

F1000Research
: This paper presents a soft sensor design technique for the estimation of pitch and yaw angular positions of a Twin Rotor MIMO System (TRMS). The objective of the proposed work was to calculate the value of pitch and yaw angular positions using a st...

Hybrid Pyramid Convolutional Network for Multiscale Face Detection.

Computational intelligence and neuroscience
Face detection remains a challenging problem due to the high variability of scale and occlusion despite the strong representational power of deep convolutional neural networks and their implicit robustness. To handle hard face detection under extreme...

NeuroCrypt: Machine Learning Over Encrypted Distributed Neuroimaging Data.

Neuroinformatics
The field of neuroimaging can greatly benefit from building machine learning models to detect and predict diseases, and discover novel biomarkers, but much of the data collected at various organizations and research centers is unable to be shared due...

Aiding clinical assessment of neonatal sepsis using hematological analyzer data with machine learning techniques.

International journal of laboratory hematology
INTRODUCTION: Early diagnosis and antibiotic administration are essential for reducing sepsis morbidity and mortality; however, diagnosis remains difficult due to complex pathogenesis and presentation. We created a machine learning model for bacteria...

Projecting COVID-19 disease severity in cancer patients using purposefully-designed machine learning.

BMC infectious diseases
BACKGROUND: Accurately predicting outcomes for cancer patients with COVID-19 has been clinically challenging. Numerous clinical variables have been retrospectively associated with disease severity, but the predictive value of these variables, and how...

Denoising of 3D Brain MR Images with Parallel Residual Learning of Convolutional Neural Network Using Global and Local Feature Extraction.

Computational intelligence and neuroscience
Magnetic resonance (MR) images often suffer from random noise pollution during image acquisition and transmission, which impairs disease diagnosis by doctors or automated systems. In recent years, many noise removal algorithms with impressive perform...

Diagnosis of Cervical Cancer based on Ensemble Deep Learning Network using Colposcopy Images.

BioMed research international
Traditional screening of cervical cancer type classification majorly depends on the pathologist's experience, which also has less accuracy. Colposcopy is a critical component of cervical cancer prevention. In conjunction with precancer screening and ...