AI Medical Compendium Journal:
Annals of the New York Academy of Sciences

Showing 1 to 10 of 28 articles

Shared autonomy between human electroencephalography and TD3 deep reinforcement learning: A multi-agent copilot approach.

Annals of the New York Academy of Sciences
Deep reinforcement learning (RL) algorithms enable the development of fully autonomous agents that can interact with the environment. Brain-computer interface (BCI) systems decipher human implicit brain signals regardless of the explicit environment....

A multi-level feature fusion artificial neural network for classification of acoustic emission signals.

Annals of the New York Academy of Sciences
In this paper, we introduce FUSION-ANN, a novel artificial neural network (ANN) designed for acoustic emission (AE) signal classification. FUSION-ANN comprises four distinct ANN branches, each housing an independent multilayer perceptron. We extract ...

Credit and blame for AI-generated content: Effects of personalization in four countries.

Annals of the New York Academy of Sciences
Generative artificial intelligence (AI) raises ethical questions concerning moral and legal responsibility-specifically, the attributions of credit and blame for AI-generated content. For example, if a human invests minimal skill or effort to produce...

Neuromorphic engineering: Artificial brains for artificial intelligence.

Annals of the New York Academy of Sciences
Neuromorphic engineering is a research discipline that tries to bridge the gaps between neuroscience and engineering, cognition and algorithms, and natural and artificial intelligence. Neuromorphic engineering promises revolutionary breakthroughs tha...

Advanced framework for multilevel detection of digital video forgeries.

Annals of the New York Academy of Sciences
The rapid expansion of digital media has sparked significant concerns regarding the swift dissemination and potential misuse of forged video content. Existing forgery detection technologies primarily focus on simple forgeries and are still evolving, ...

The role of artificial intelligence in optimizing management of atrial fibrillation in acute ischemic stroke.

Annals of the New York Academy of Sciences
Atrial fibrillation (AF) is a severe condition associated with high morbidity and mortality, including an increased risk of stroke and poor outcomes poststroke. Our understanding of the prognosis in AF remains poor. Machine learning (ML) has been app...

Artificial intelligence and psychedelic medicine.

Annals of the New York Academy of Sciences
Artificial intelligence (AI) and psychedelic medicines are among the most high-profile evolving disruptive innovations within mental healthcare in recent years. Although AI and psychedelics may not have historically shared any common ground, there ex...

Comparison of water and terrestrial jumping in natural and robotic insects.

Annals of the New York Academy of Sciences
Jumping requires high actuation power for achieving high speed in a short time. Especially, organisms and robots at the insect scale jump in order to overcome size limits on the speed of locomotion. As small jumpers suffer from intrinsically small po...

Application of a novel deep learning-based 3D videography workflow to bat flight.

Annals of the New York Academy of Sciences
Studying the detailed biomechanics of flying animals requires accurate three-dimensional coordinates for key anatomical landmarks. Traditionally, this relies on manually digitizing animal videos, a labor-intensive task that scales poorly with increas...

Can large language models reason and plan?

Annals of the New York Academy of Sciences
While humans sometimes do show the capability of correcting their own erroneous guesses with self-critiquing, there seems to be no basis for that assumption in the case of LLMs.