AIMC Topic: Algorithms

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Development and validation of deep learning algorithms for scoliosis screening using back images.

Communications biology
Adolescent idiopathic scoliosis is the most common spinal disorder in adolescents with a prevalence of 0.5-5.2% worldwide. The traditional methods for scoliosis screening are easily accessible but require unnecessary referrals and radiography exposur...

Anomaly Detection of Moderate Traumatic Brain Injury Using Auto-Regularized Multi-Instance One-Class SVM.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Detection and quantification of functional deficits due to moderate traumatic brain injury (mTBI) is crucial for clinical decision-making and timely commencement of functional therapy. In this work, we explore magnetoencephalography (MEG) based funct...

Texture analysis and multiple-instance learning for the classification of malignant lymphomas.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Malignant lymphomas are cancers of the immune system and are characterized by enlarged lymph nodes that typically spread across many different sites. Many different histological subtypes exist, whose diagnosis is typically ...

Next generation pathology: artificial intelligence enhances histopathology practice.

The Journal of pathology
Deep learning algorithms have shown benefits for pathology in the context of risk stratification of tumors. Although the results are promising, several steps have to be made to confirm clinical utility. In a recent issue of The Journal of Pathology, ...

A hybrid machine learning approach to cerebral stroke prediction based on imbalanced medical dataset.

Artificial intelligence in medicine
BACKGROUND AND OBJECTIVE: Cerebral stroke has become a significant global public health issue in recent years. The ideal solution to this concern is to prevent in advance by controlling related metabolic factors. However, it is difficult for medical ...

A New Approach for Brain Tumor Segmentation and Classification Based on Score Level Fusion Using Transfer Learning.

Journal of medical systems
Brain tumor is one of the most death defying diseases nowadays. The tumor contains a cluster of abnormal cells grouped around the inner portion of human brain. It affects the brain by squeezing/ damaging healthy tissues. It also amplifies intra crani...

Optimized fast GPU implementation of robust artificial-neural-networks for k-space interpolation (RAKI) reconstruction.

PloS one
BACKGROUND: Robust Artificial-neural-networks for k-space Interpolation (RAKI) is a recently proposed deep-learning-based reconstruction algorithm for parallel imaging. Its main premise is to perform k-space interpolation using convolutional neural n...

Glaucoma management in the era of artificial intelligence.

The British journal of ophthalmology
Glaucoma is a result of irreversible damage to the retinal ganglion cells. While an early intervention could minimise the risk of vision loss in glaucoma, its asymptomatic nature makes it difficult to diagnose until a late stage. The diagnosis of gla...

Improving automatic delineation for head and neck organs at risk by Deep Learning Contouring.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
INTRODUCTION: Adequate head and neck (HN) organ-at-risk (OAR) delineation is crucial for HN radiotherapy and for investigating the relationships between radiation dose to OARs and radiation-induced side effects. The automatic contouring algorithms th...