AIMC Topic: Medicine

Clear Filters Showing 161 to 170 of 241 articles

Creation and Adoption of Large Language Models in Medicine.

JAMA
IMPORTANCE: There is increased interest in and potential benefits from using large language models (LLMs) in medicine. However, by simply wondering how the LLMs and the applications powered by them will reshape medicine instead of getting actively in...

SleepSIM: Conditional GAN-based non-REM sleep EEG Signal Generator.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Synthetic data generation has become increasingly popular with the increasing use of generative networks. Recently, Generative Adversarial Network (GAN) architectures have produced exceptional results in synthetic image generation. However, time seri...

ARGO 2.0: a Hybrid NLP/ML Framework for Diagnosis Standardization.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
A relevant problem in medicine is the standardization of the diagnosis associated with a clinical case. Although diagnosis formulation is an intrinsically subjective and uncertain process, its standardization may take benefit from digital solutions a...

[Is possible to decrease the risk of development of undesirable effects of medications applying computer technologies? (a review)].

Problemy sotsial'noi gigieny, zdravookhraneniia i istorii meditsiny
The article presents overview of modern concepts about application of artificial intelligence (AI) in pharmacotherapy to decrease risk of developing undesirable side effects of medications. The possibilities of applying AI in selection of optimal med...

Making decisions: Bias in artificial intelligence and data‑driven diagnostic tools.

Australian journal of general practice
BACKGROUND: Although numerous studies have shown the potential of artificial intelligence (AI) systems in drastically improving clinical practice, there are concerns that these AI systems could replicate existing biases.