AIMC Topic: Machine Learning

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Automated renal segmentation in healthy and chronic kidney disease subjects using a convolutional neural network.

Magnetic resonance in medicine
PURPOSE: Total kidney volume (TKV) is an important measure in renal disease detection and monitoring. We developed a fully automated method to segment the kidneys from T -weighted MRI to calculate TKV of healthy control (HC) and chronic kidney diseas...

Evaluation of supervised machine-learning methods for predicting appearance traits from DNA.

Forensic science international. Genetics
The prediction of human externally visible characteristics (EVCs) based solely on DNA information has become an established approach in forensic and anthropological genetics in recent years. While for a large set of EVCs, predictive models have alrea...

MSA-Regularized Protein Sequence Transformer toward Predicting Genome-Wide Chemical-Protein Interactions: Application to GPCRome Deorphanization.

Journal of chemical information and modeling
Small molecules play a critical role in modulating biological systems. Knowledge of chemical-protein interactions helps address fundamental and practical questions in biology and medicine. However, with the rapid emergence of newly sequenced genes, t...

Machine learning-based reclassification of germline variants of unknown significance: The RENOVO algorithm.

American journal of human genetics
The increasing scope of genetic testing allowed by next-generation sequencing (NGS) dramatically increased the number of genetic variants to be interpreted as pathogenic or benign for adequate patient management. Still, the interpretation process oft...

A Novel Graph Neural Network Methodology to Investigate Dihydroorotate Dehydrogenase Inhibitors in Small Cell Lung Cancer.

Biomolecules
Small cell lung cancer (SCLC) is a particularly aggressive tumor subtype, and dihydroorotate dehydrogenase (DHODH) has been demonstrated to be a therapeutic target for SCLC. Network pharmacology analysis and virtual screening were utilized to find ou...

From convolutional neural networks to models of higher-level cognition (and back again).

Annals of the New York Academy of Sciences
The remarkable successes of convolutional neural networks (CNNs) in modern computer vision are by now well known, and they are increasingly being explored as computational models of the human visual system. In this paper, we ask whether CNNs might al...

Experimental support for genomic prediction of climate maladaptation using the machine learning approach Gradient Forests.

Molecular ecology resources
Gradient Forests (GF) is a machine learning algorithm that is gaining in popularity for studying the environmental drivers of genomic variation and for incorporating genomic information into climate change impact assessments. Here we (i) provide the ...

How do you feel? Using natural language processing to automatically rate emotion in psychotherapy.

Behavior research methods
Emotional distress is a common reason for seeking psychotherapy, and sharing emotional material is central to the process of psychotherapy. However, systematic research examining patterns of emotional exchange that occur during psychotherapy sessions...

Interpretable machine learning model to detect chemically adulterated urine samples analyzed by high resolution mass spectrometry.

Clinical chemistry and laboratory medicine
OBJECTIVES: Urine sample manipulation including substitution, dilution, and chemical adulteration is a continuing challenge for workplace drug testing, abstinence control, and doping control laboratories. The simultaneous detection of sample manipula...

IHG-MA: Inductive heterogeneous graph multi-agent reinforcement learning for multi-intersection traffic signal control.

Neural networks : the official journal of the International Neural Network Society
Multi-agent deep reinforcement learning (MDRL) has been widely applied in multi-intersection traffic signal control. The MDRL algorithms produce the decentralized cooperative traffic-signal policies via specialized multi-agent settings in certain tra...