AIMC Topic: Probability

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Reconstructing faces from fMRI patterns using deep generative neural networks.

Communications biology
Although distinct categories are reliably decoded from fMRI brain responses, it has proved more difficult to distinguish visually similar inputs, such as different faces. Here, we apply a recently developed deep learning system to reconstruct face im...

Genetic and firefly metaheuristic algorithms for an optimized neuro-fuzzy prediction modeling of wildfire probability.

Journal of environmental management
In the terrestrial ecosystems, perennial challenges of increased frequency and intensity of wildfires are exacerbated by climate change and unplanned human activities. Development of robust management and suppression plans requires accurate estimates...

Extracting chemical-protein interactions from biomedical literature via granular attention based recurrent neural networks.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The extraction of interactions between chemicals and proteins from biomedical literature is important for many biomedical tasks such as drug discovery and precision medicine. In the existing systems, the methods achieving co...

The Four Horsemen of the 'Omicsalypse': ontology, replicability, probability and epistemology.

Human genetics
Much of modern genomics and the other 'omics' that tag along, assert that the causal bases of biomedical outcomes are genomically enumerable lists whose effects are predictable with 'precision', extensible from samples to all, and enabled by ever-gre...

A Deep Learning Approach to the Screening of Oncogenic Gene Fusions in Humans.

International journal of molecular sciences
Gene fusions have a very important role in the study of cancer development. In this regard, predicting the probability of protein fusion transcripts of developing into a cancer is a very challenging and yet not fully explored research problem. To thi...

A Transition Control Mechanism for Artificial Bee Colony (ABC) Algorithm.

Computational intelligence and neuroscience
Artificial Bee Colony (ABC) algorithm inspired by the complex search and foraging behaviors of real honey bees is one of the most promising implementations of the Swarm Intelligence- (SI-) based optimization algorithms. Due to its robust and phase-di...

Kirsch's, and everyone's, bind: How to build models for the wild?

Cognitive processing
Alexandra Kirsch proposed a general formal model of decision making. She proposed it as a model both of human psychology and of artificial intelligence. As one might expect, and as Don Ross explicated, this is a challenging, albeit fascinating, posit...

Hybrid Degradation Equipment Remaining Useful Life Prediction Oriented Parallel Simulation considering Model Soft Switch.

Computational intelligence and neuroscience
Equipment parallel simulation is an emerging simulation technology in recent years, and equipment remaining useful life (RUL) prediction oriented parallel simulation is an important branch of parallel simulation. An important concept in equipment par...

Reinforcement learning-based control of tumor growth under anti-angiogenic therapy.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: In recent decades, cancer has become one of the most fatal and destructive diseases which is threatening humans life. Accordingly, different types of cancer treatment are studied with the main aim to have the best treatment...