AIMC Topic: Humans

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Machine learning uncovers the most robust self-report predictors of relationship quality across 43 longitudinal couples studies.

Proceedings of the National Academy of Sciences of the United States of America
Given the powerful implications of relationship quality for health and well-being, a central mission of relationship science is explaining why some romantic relationships thrive more than others. This large-scale project used machine learning (i.e., ...

Pan-cancer computational histopathology reveals mutations, tumor composition and prognosis.

Nature cancer
We use deep transfer learning to quantify histopathological patterns across 17,355 hematoxylin and eosin-stained histopathology slide images from 28 cancer types and correlate these with matched genomic, transcriptomic and survival data. This approac...

Pan-cancer image-based detection of clinically actionable genetic alterations.

Nature cancer
Molecular alterations in cancer can cause phenotypic changes in tumor cells and their micro-environment. Routine histopathology tissue slides - which are ubiquitously available - can reflect such morphological changes. Here, we show that deep learnin...

3D Printed Robot Hand Structure Using Four-Bar Linkage Mechanism for Prosthetic Application.

Sensors (Basel, Switzerland)
Trans-radial prosthesis is a wearable device that intends to help amputees under the elbow to replace the function of the missing anatomical segment that resembles an actual human hand. However, there are some challenging aspects faced mainly on the ...

Revealing architectural order with quantitative label-free imaging and deep learning.

eLife
We report quantitative label-free imaging with phase and polarization (QLIPP) for simultaneous measurement of density, anisotropy, and orientation of structures in unlabeled live cells and tissue slices. We combine QLIPP with deep neural networks to ...

Machine Learning Algorithms Identify Pathogen-Specific Biomarkers of Clinical and Metabolomic Characteristics in Septic Patients with Bacterial Infections.

BioMed research international
Sepsis is a high-mortality disease that is infected by bacteria, but pathogens in individual patients are difficult to diagnosis. Metabolomic changes triggered by microbial activity provide us with the possibility of accurately identifying infection....

Inexpensive, non-invasive biomarkers predict Alzheimer transition using machine learning analysis of the Alzheimer's Disease Neuroimaging (ADNI) database.

PloS one
The Alzheimer's Disease Neuroimaging (ADNI) database is an expansive undertaking by government, academia, and industry to pool resources and data on subjects at various stage of symptomatic severity due to Alzheimer's disease. As expected, magnetic r...

Automatic characterization of myocardial perfusion imaging polar maps employing deep learning and data augmentation.

Hellenic journal of nuclear medicine
OBJECTIVE: To investigate a deep learning technique, more specifically state-of-the-art convolutional neural networks (CNN), for automatic characterization of polar maps derived from myocardial perfusion imaging (MPI) studies for the diagnosis of cor...

The automaton as a surgeon: the future of artificial intelligence in emergency and general surgery.

European journal of trauma and emergency surgery : official publication of the European Trauma Society
BACKGROUND: Artificial intelligence (AI) is a field involving computational simulation of human intelligence processes; these applications of deep learning could have implications in the specialty of emergency surgery (ES). ES is a rapidly advancing ...

Machine learning and wearable devices of the future.

Epilepsia
Machine learning (ML) is increasingly recognized as a useful tool in healthcare applications, including epilepsy. One of the most important applications of ML in epilepsy is seizure detection and prediction, using wearable devices (WDs). However, not...