AIMC Topic: Computer Simulation

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Predicting differential ion mobility behaviour using machine learning.

The Analyst
Although there has been a surge in popularity of differential mobility spectrometry (DMS) within analytical workflows, determining separation conditions within the DMS parameter space still requires manual optimization. A means of accurately predicti...

Predicting the interaction biomolecule types for lncRNA: an ensemble deep learning approach.

Briefings in bioinformatics
Long noncoding RNAs (lncRNAs) play significant roles in various physiological and pathological processes via their interactions with biomolecules like DNA, RNA and protein. The existing in silico methods used for predicting the functions of lncRNA ma...

Creative Approaches for Assessing Long-term Outcomes in Children.

Pediatrics
Advances in new technologies, when incorporated into routine health screening, have tremendous promise to benefit children. The number of health screening tests, many of which have been developed with machine learning or genomics, has exploded. To as...

Toward a living soft microrobot through optogenetic locomotion control of .

Science robotics
Learning from the locomotion of natural organisms is one of the most effective strategies for designing microrobots. However, the development of bioinspired microrobots is still challenging because of technical bottlenecks such as design and seamless...

Multimodal, multitask, multiattention (M3) deep learning detection of reticular pseudodrusen: Toward automated and accessible classification of age-related macular degeneration.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Reticular pseudodrusen (RPD), a key feature of age-related macular degeneration (AMD), are poorly detected by human experts on standard color fundus photography (CFP) and typically require advanced imaging modalities such as fundus autoflu...

Pix2pix Conditional Generative Adversarial Networks for Scheimpflug Camera Color-Coded Corneal Tomography Image Generation.

Translational vision science & technology
PURPOSE: To assess the ability of pix2pix conditional generative adversarial network (pix2pix cGAN) to create plausible synthesized Scheimpflug camera color-coded corneal tomography images based upon a modest-sized original dataset to be used for ima...

Modeling, learning, perception, and control methods for deformable object manipulation.

Science robotics
Perceiving and handling deformable objects is an integral part of everyday life for humans. Automating tasks such as food handling, garment sorting, or assistive dressing requires open problems of modeling, perceiving, planning, and control to be sol...

DTI-MLCD: predicting drug-target interactions using multi-label learning with community detection method.

Briefings in bioinformatics
Identifying drug-target interactions (DTIs) is an important step for drug discovery and drug repositioning. To reduce the experimental cost, a large number of computational approaches have been proposed for this task. The machine learning-based model...

Manipulation for self-Identification, and self-Identification for better manipulation.

Science robotics
The process of modeling a series of hand-object parameters is crucial for precise and controllable robotic in-hand manipulation because it enables the mapping from the hand's actuation input to the object's motion to be obtained. Without assuming tha...

Robotic hand augmentation drives changes in neural body representation.

Science robotics
Humans have long been fascinated by the opportunities afforded through augmentation. This vision not only depends on technological innovations but also critically relies on our brain's ability to learn, adapt, and interface with augmentation devices....