AIMC Topic: Artificial Intelligence

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The Use of Artificial Intelligence in Clinical Care: A Values-Based Guide for Shared Decision Making.

Current oncology (Toronto, Ont.)
Clinical applications of artificial intelligence (AI) in healthcare, including in the field of oncology, have the potential to advance diagnosis and treatment. The literature suggests that patient values should be considered in decision making when u...

Recent Advances in the Applications of Additive Manufacturing (3D Printing) in Drug Delivery: A Comprehensive Review.

AAPS PharmSciTech
There has been a tremendous increase in the investigations of three-dimensional (3D) printing for biomedical and pharmaceutical applications, and drug delivery in particular, ever since the US FDA approved the first 3D printed medicine, SPRITAM® (lev...

Comprehensive AI-assisted tool for ankylosing spondylitis based on multicenter research outperforms human experts.

Frontiers in public health
INTRODUCTION: The diagnosis and treatment of ankylosing spondylitis (AS) is a difficult task, especially in less developed countries without access to experts. To address this issue, a comprehensive artificial intelligence (AI) tool was created to he...

Framework and metrics for the clinical use and implementation of artificial intelligence algorithms into endoscopy practice: recommendations from the American Society for Gastrointestinal Endoscopy Artificial Intelligence Task Force.

Gastrointestinal endoscopy
In the past few years, we have seen a surge in the development of relevant artificial intelligence (AI) algorithms addressing a variety of needs in GI endoscopy. To accept AI algorithms into clinical practice, their effectiveness, clinical value, and...

Rams, hounds and white boxes: Investigating human-AI collaboration protocols in medical diagnosis.

Artificial intelligence in medicine
In this paper, we study human-AI collaboration protocols, a design-oriented construct aimed at establishing and evaluating how humans and AI can collaborate in cognitive tasks. We applied this construct in two user studies involving 12 specialist rad...

ARTIFICIAL INTELLIGENCE (AI) AS AN AID IN RESTORATIVE DENTISTRY IS PROMISING, BUT STILL A WORK IN PROGRESS.

The journal of evidence-based dental practice
ARTICLE TITLE AND BIBLIOGRAPHIC INFORMATION: Artificial intelligence applications in restorative dentistry: A systematic review. Revilla-León, M., Gómez-Polo, M., Vyas, S., Barmak, A. B., Özcan, M., Att, W., & Krishnamurthy, V. R. J Prosthet Dent 202...

ARTIFICIAL INTELLIGENCE MODELS SHOW POTENTIAL IN RECOGNIZING THE DENTAL IMPLANT TYPE, PREDICTING IMPLANT SUCCESS, AND OPTIMIZING IMPLANT DESIGN.

The journal of evidence-based dental practice
ARTICLE TITLE AND BIBLIOGRAPHIC INFORMATION: Revilla-León M, Gómez-Polo M, Vyas S, Barmak BA, Galluci GO,Att W, Krishnamurthy VR. J. Artificial intelligence applications in implant dentistry: A systematic review. J Prosthet Dent 2021:(21);S0022-3913.

Artificial Intelligence-Assisted Meta-Analysis of the Frequency of ACE I/D Polymorphisms in Centenarians and Other Long-Lived Individuals.

International journal of molecular sciences
Current research on the angiotensin-converting-enzyme () gene has yielded controversial results on whether different polymorphisms are linked with human longevity. polymorphisms are a risk factor for Alzheimer's disease and age-onset diseases that ...

Deep learning-based multifeature integration robustly predicts central lymph node metastasis in papillary thyroid cancer.

BMC cancer
BACKGROUND: Few highly accurate tests can diagnose central lymph node metastasis (CLNM) of papillary thyroid cancer (PTC). Genetic sequencing of tumor tissue has allowed the targeting of certain genetic variants for personalized cancer therapy develo...

AlphaFold-multimer predicts ATG8 protein binding motifs crucial for autophagy research.

PLoS biology
In this issue of PLOS Biology, Ibrahim and colleagues demonstrate how AlphaFold-multimer, an artificial intelligence-based structure prediction tool, can be used to identify sequence motifs binding to the ATG8 family of proteins central to autophagy.