AIMC Topic: Artificial Intelligence

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From materials to applications: a review of research on artificial olfactory memory.

Materials horizons
Olfactory memory forms the basis for biological perception and environmental adaptation. Advancing artificial intelligence to replicate this biological perception as artificial olfactory memory is essential. The widespread use of various robotic syst...

Artificial Intelligence-Generated Editorials in Radiology: Can Expert Editors Detect Them?

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Artificial intelligence is capable of generating complex texts that may be indistinguishable from those written by humans. We aimed to evaluate the ability of GPT-4 to write radiology editorials and to compare these with human...

Prospective Clinical Implementation of Paige Prostate Detect Artificial Intelligence Assistance in the Detection of Prostate Cancer in Prostate Biopsies: CONFIDENT P Trial Implementation of Artificial Intelligence Assistance in Prostate Cancer Detection.

JCO clinical cancer informatics
PURPOSE: Pathologists diagnose prostate cancer (PCa) on hematoxylin and eosin (HE)-stained sections of prostate needle biopsies (PBx). Some laboratories use costly immunohistochemistry (IHC) for all cases to optimize workflow, often exceeding reimbur...

More intelligent faculty development: Integrating GenAI in curriculum development programs.

Medical teacher
EDUCATIONAL CHALLENGE: Generative Artificial Intelligence (GenAI) has rapidly emerged as a potentially transformative tool in education. Faculty development (FD) programs, particularly in curriculum development (CD), are ideal settings for incorporat...

Detection of canine external ear canal lesions using artificial intelligence.

Veterinary dermatology
BACKGROUND: Early and accurate diagnosis of otitis externa is crucial for correct management yet can often be challenging. Artificial intelligence (AI) is a valuable diagnostic tool in human medicine. Currently, no such tool is available in veterinar...

Advancing laryngology through artificial intelligence: a comprehensive review of implementation frameworks and strategies.

Current opinion in otolaryngology & head and neck surgery
PURPOSE OF REVIEW: This review aims to explore the integration of artificial intelligence (AI) in laryngology, with specific focus on the barriers preventing translation from pilot studies into routine clinical practice and strategies for successful ...

Diagnostic accuracy of artificial intelligence for dental and occlusal parameters using standardized clinical photographs.

American journal of orthodontics and dentofacial orthopedics : official publication of the American Association of Orthodontists, its constituent societies, and the American Board of Orthodontics
INTRODUCTION: SmileMate (SmileMate, Dental Monitoring SAS, Paris, France) is an artificial intelligence (AI)-based Web site that uses intraoral photographs to assess patients' dental and orthodontic parameters and provide a report. This study aimed t...

Potential of AI and ML in oncology research including diagnosis, treatment and future directions: A comprehensive prospective.

Computers in biology and medicine
Artificial intelligence (AI) and machine learning (ML) have emerged as transformative tools in cancer research, offering the ability to process huge data rapidly and make precise therapeutic decisions. Over the last decade, AI, particularly deep lear...

Recent Advances in Structured Illumination Microscopy: From Fundamental Principles to AI-Enhanced Imaging.

Small methods
Structured illumination microscopy (SIM) has emerged as a pivotal super-resolution technique in biological imaging. This review aims to introduce the fundamental principles of SIM, primarily focuses on the latest developments in super-resolution SIM ...

Strategies for mitigating data heterogeneities in AI-based neuro-disease detection.

Neuron
In this NeuroView, we discuss challenges and best practices when dealing with disease-detection AI models that are trained on heterogeneous clinical data, focusing on the interrelated problems of model bias, causality, and rare diseases.