AIMC Topic: Artificial Intelligence

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What have we learned about artificial intelligence from studying the brain?

Biological cybernetics
Neuroscience and artificial intelligence (AI) share a long, intertwined history. It has been argued that discoveries in neuroscience were (and continue to be) instrumental in driving the development of new AI technology. Scrutinizing these historical...

Respiratory Diseases Diagnosis Using Audio Analysis and Artificial Intelligence: A Systematic Review.

Sensors (Basel, Switzerland)
Respiratory diseases represent a significant global burden, necessitating efficient diagnostic methods for timely intervention. Digital biomarkers based on audio, acoustics, and sound from the upper and lower respiratory system, as well as the voice,...

Prediction of xerostomia in elderly based on clinical characteristics and salivary flow rate with machine learning.

Scientific reports
Xerostomia may be accompanied by changes in salivary flow rate and the incidence increases in elderly. We aimed to use machine learning algorithms, to identify significant predictors for the presence of xerostomia. This study is the first to predict ...

The current state of artificial intelligence generative language models is more creative than humans on divergent thinking tasks.

Scientific reports
The emergence of publicly accessible artificial intelligence (AI) large language models such as ChatGPT has given rise to global conversations on the implications of AI capabilities. Emergent research on AI has challenged the assumption that creative...

Artificial Intelligence to Determine Fetal Sex.

American journal of perinatology
OBJECTIVE:  This proof-of-concept study assessed how confidently an artificial intelligence (AI) model can determine the sex of a fetus from an ultrasound image.

Assessing Fuchs Corneal Endothelial Dystrophy Using Artificial Intelligence-Derived Morphometric Parameters From Specular Microscopy Images.

Cornea
PURPOSE: The aim of this study was to evaluate the efficacy of artificial intelligence-derived morphometric parameters in characterizing Fuchs corneal endothelial dystrophy (FECD) from specular microscopy images.

Erratum to "MO-11.2 - Explainable artificial intelligence applied to machine learning for radiomics" [Physica Medica 115S1 (2023) 102870].

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)

Perspectives on Preparedness for Chemical, Biological, Radiological, and Nuclear Threats in the Middle East and North Africa Region: Application of Artificial Intelligence Techniques.

Health security
Over the past 3 decades, the diversity of ethnic, religious, and political backgrounds worldwide, particularly in countries of the Middle East and North Africa (MENA), has led to an increase in the number of intercountry conflicts and terrorist attac...

An artificial intelligence-driven predictive model for pediatric allogeneic hematopoietic stem cell transplantation using clinical variables.

European journal of haematology
BACKGROUND: Hematopoietic stem cell transplantation (HSCT) is a procedure with high morbidity and mortality. Identifying patients for maximum benefit and risk assessment is crucial in the decision-making process. This has led to the development of pr...

Spine surgeon versus AI algorithm full-length radiographic measurements: a validation study of complex adult spinal deformity patients.

Spine deformity
INTRODUCTION: Spinal measurements play an integral role in surgical planning for a variety of spine procedures. Full-length imaging eliminates distortions that can occur with stitched images. However, these images take radiologists significantly long...