AIMC Topic: Artificial Intelligence

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Diagnostic accuracy of radiomics and artificial intelligence models in diagnosing lymph node metastasis in head and neck cancers: a systematic review and meta-analysis.

Neuroradiology
INTRODUCTION: Head and neck cancers are the seventh most common globally, with lymph node metastasis (LNM) being a critical prognostic factor, significantly reducing survival rates. Traditional imaging methods have limitations in accurately diagnosin...

Artificial intelligence driven clustering of blood pressure profiles reveals frailty in orthostatic hypertension.

Experimental physiology
Gravity, an invisible but constant force , challenges the regulation of blood pressure when transitioning between postures. As physiological reserve diminishes with age, individuals grow more susceptible to such stressors over time, risking inadequat...

Unveiling the power of artificial intelligence for image-based diagnosis and treatment in endodontics: An ally or adversary?

International endodontic journal
BACKGROUND: Artificial intelligence (AI), a field within computer science, uses algorithms to replicate human intelligence tasks such as pattern recognition, decision-making and problem-solving through complex datasets. In endodontics, AI is transfor...

Bio-Inspired Neuromorphic Sensory Systems from Intelligent Perception to Nervetronics.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Inspired by the extensive signal processing capabilities of the human nervous system, neuromorphic artificial sensory systems have emerged as a pivotal technology in advancing brain-like computing for applications in humanoid robotics, prosthetics, a...

Online public opinion attention, digital transformation, and green investment: A deep learning model based on artificial intelligence.

Journal of environmental management
The digital economy is rising at an unprecedented pace, becoming a key driver of the comprehensive transformation and upgrading of the global economy and society. Existing research widely demonstrates the multifaceted positive impacts of green invest...

Microplastics and Trash Cleaning and Harmonization (MaTCH): Semantic Data Ingestion and Harmonization Using Artificial Intelligence.

Environmental science & technology
With the rapid expansion of microplastic research and reliance on semantic descriptors, there is an increasing need for plastic pollution data harmonization. Data standards have been developed but are seldom implemented across research sectors, geogr...

Artificial Intelligence-Assisted Automatic Raman-Activated Cell Sorting (AI-RACS) System for Mining Specific Functional Microorganisms in the Microbiome.

Analytical chemistry
The microbiome represents the natural presence of microorganisms, and exploring, understanding, and leveraging its functions will bring about significant breakthroughs in life sciences and applications. Raman-activated cell sorting (RACS) enables the...

Modification and Validation of the System Causability Scale Using AI-Based Therapeutic Recommendations for Urological Cancer Patients: A Basis for the Development of a Prospective Comparative Study.

Current oncology (Toronto, Ont.)
The integration of artificial intelligence, particularly Large Language Models (LLMs), has the potential to significantly enhance therapeutic decision-making in clinical oncology. Initial studies across various disciplines have demonstrated that LLM-...

A bibliometrics analysis based on the application of artificial intelligence in the field of radiotherapy from 2003 to 2023.

Radiation oncology (London, England)
BACKGROUND: Recent research has demonstrated that the use of artificial intelligence (AI) in radiotherapy (RT) has significantly streamlined the process for physicians to treat patients with tumors; however, bibliometric studies examining the correla...

Representation of intensivists' race/ethnicity, sex, and age by artificial intelligence: a cross-sectional study of two text-to-image models.

Critical care (London, England)
BACKGROUND: Integrating artificial intelligence (AI) into intensive care practices can enhance patient care by providing real-time predictions and aiding clinical decisions. However, biases in AI models can undermine diversity, equity, and inclusion ...