AIMC Topic: Machine Learning

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Prediction of inherited genomic susceptibility to 20 common cancer types by a supervised machine-learning method.

Proceedings of the National Academy of Sciences of the United States of America
Prevention and early intervention are the most effective ways of avoiding or minimizing psychological, physical, and financial suffering from cancer. However, such proactive action requires the ability to predict the individual's susceptibility to ca...

The Early Psychosis Screener (EPS): Quantitative validation against the SIPS using machine learning.

Schizophrenia research
Machine learning techniques were used to identify highly informative early psychosis self-report items and to validate an early psychosis screener (EPS) against the Structured Interview for Psychosis-risk Syndromes (SIPS). The Prodromal Questionnaire...

Machine learning in cardiovascular medicine: are we there yet?

Heart (British Cardiac Society)
Artificial intelligence (AI) broadly refers to analytical algorithms that iteratively learn from data, allowing computers to find hidden insights without being explicitly programmed where to look. These include a family of operations encompassing sev...

IMU-to-Segment Assignment and Orientation Alignment for the Lower Body Using Deep Learning.

Sensors (Basel, Switzerland)
Human body motion analysis based on wearable inertial measurement units (IMUs) receives a lot of attention from both the research community and the and industrial community. This is due to the significant role in, for instance, mobile health systems,...

Generating Quantitative Cell Identity Labels with Marker Enrichment Modeling (MEM).

Current protocols in cytometry
Multiplexed single-cell experimental techniques like mass cytometry measure 40 or more features and enable deep characterization of well-known and novel cell populations. However, traditional data analysis techniques rely extensively on human experts...

A Two-Stream Deep Fusion Framework for High-Resolution Aerial Scene Classification.

Computational intelligence and neuroscience
One of the challenging problems in understanding high-resolution remote sensing images is aerial scene classification. A well-designed feature representation method and classifier can improve classification accuracy. In this paper, we construct a new...

On the Generalization Ability of Online Gradient Descent Algorithm Under the Quadratic Growth Condition.

IEEE transactions on neural networks and learning systems
Online learning has been successfully applied in various machine learning problems. Conventional analysis of online learning achieves a sharp generalization bound with a strongly convex assumption. In this paper, we study the generalization ability o...

Characterization of Adrenal Lesions on Unenhanced MRI Using Texture Analysis: A Machine-Learning Approach.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Adrenal adenomas (AA) are the most common benign adrenal lesions, often characterized based on intralesional fat content as either lipid-rich (LRA) or lipid-poor (LPA). The differentiation of AA, particularly LPA, from nonadenoma adrenal ...