AIMC Topic: Algorithms

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Representation Learning by Rotating Your Faces.

IEEE transactions on pattern analysis and machine intelligence
The large pose discrepancy between two face images is one of the fundamental challenges in automatic face recognition. Conventional approaches to pose-invariant face recognition either perform face frontalization on, or learn a pose-invariant represe...

Parkinson's Disease Diagnosis via Joint Learning From Multiple Modalities and Relations.

IEEE journal of biomedical and health informatics
Parkinson's disease (PD) is a neurodegenerative progressive disease that mainly affects the motor systems of patients. To slow this disease deterioration, early and accurate diagnosis of PD is an effective way, which alleviates mental and physical su...

An End-to-End Deep Learning Histochemical Scoring System for Breast Cancer TMA.

IEEE transactions on medical imaging
One of the methods for stratifying different molecular classes of breast cancer is the Nottingham prognostic index plus, which uses breast cancer relevant biomarkers to stain tumor tissues prepared on tissue microarray (TMA). To determine the molecul...

eDoctor: machine learning and the future of medicine.

Journal of internal medicine
Machine learning (ML) is a burgeoning field of medicine with huge resources being applied to fuse computer science and statistics to medical problems. Proponents of ML extol its ability to deal with large, complex and disparate data, often found with...

An EM-based semi-supervised deep learning approach for semantic segmentation of histopathological images from radical prostatectomies.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Automated Gleason grading is an important preliminary step for quantitative histopathological feature extraction. Different from the traditional task of classifying small pre-selected homogeneous regions, semantic segmentation provides pixel-wise Gle...

Personalized prediction model for seizure-free epilepsy with levetiracetam therapy: a retrospective data analysis using support vector machine.

British journal of clinical pharmacology
AIMS: To predict the probability of a seizure-free (SF) state in patients with epilepsy (PWEs) after treatment with levetiracetam and to identify the clinical and electroencephalographic (EEG) factors that affect outcomes.

Novel symmetry-based gene-gene dissimilarity measures utilizing Gene Ontology: Application in gene clustering.

Gene
In recent years DNA microarray technology, leading to the generation of high-volume biological data, has gained significant attention. To analyze this high volume gene-expression data, one such powerful tool is Clustering. For any clustering algorith...

A kernel machine method for detecting higher order interactions in multimodal datasets: Application to schizophrenia.

Journal of neuroscience methods
BACKGROUND: Technological advances are enabling us to collect multimodal datasets at an increasing depth and resolution while with decreasing labors. Understanding complex interactions among multimodal datasets, however, is challenging.