AI Medical Compendium Topic

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ARTIFICIAL INTELLIGENCE IN DENTAL SHADE-MATCHING SHOWS PROMISING POTENTIAL FOR PRECISION IN RESTORATIVE DENTISTRY, THOUGH REQUIRING FURTHER IMPROVEMENT.

The journal of evidence-based dental practice
ARTICLE TITLE AND BIBLIOGRAPHIC INFORMATION: Shetty, S., et al. (2023). "Artificial intelligence systems in dental shade-matching: A systematic review." J Prosthodont. DOI: 10.1111/jopr.13805.

Monitoring poultry social dynamics using colored tags: Avian visual perception, behavioral effects, and artificial intelligence precision.

Poultry science
Artificial intelligence (AI) in animal behavior and welfare research is on the rise. AI can detect behaviors and localize animals in video recordings, thus it is a valuable tool for studying social dynamics. However, maintaining the identity of indiv...

Learnable color space conversion and fusion for stain normalization in pathology images.

Medical image analysis
Variations in hue and contrast are common in H&E-stained pathology images due to differences in slide preparation across various institutions. Such stain variations, while not affecting pathologists much in diagnosing the biopsy, pose significant cha...

Identifying the presence of atrial fibrillation during sinus rhythm using a dual-input mixed neural network with ECG coloring technology.

BMC medical research methodology
BACKGROUND: Undetected atrial fibrillation (AF) poses a significant risk of stroke and cardiovascular mortality. However, diagnosing AF in real-time can be challenging as the arrhythmia is often not captured instantly. To address this issue, a deep-l...

Alternative assessment of machine learning to polynomial regression in response surface methodology for predicting decolorization efficiency in textile wastewater treatment.

Chemosphere
This study investigated the potential of machine learning (ML) as a substitute for polynomial regression in conventional response surface methodology (RSM) for decolorizing textile wastewater via a UV/HO process. While polynomial regression offers li...

Porkolor: A deep learning framework for pork color classification.

Meat science
Pork color is crucial for assessing its safety and freshness, and traditional methods of observing through human eyes are inefficient and subjective. In recent years, several methods have been proposed based on computer vision and deep learning have ...

Development of Deep Learning-Based Virtual Lugol Chromoendoscopy for Superficial Esophageal Squamous Cell Carcinoma.

Journal of gastroenterology and hepatology
BACKGROUND: Lugol chromoendoscopy has been shown to increase the sensitivity of detection of esophageal squamous cell carcinoma (ESCC). We aimed to develop a deep learning-based virtual lugol chromoendoscopy (V-LCE) method.

Artificial intelligence-driven quantification of antibiotic-resistant Bacteria in food by color-encoded multiplex hydrogel digital LAMP.

Food chemistry
Antibiotic-resistant bacteria pose considerable risks to global health, particularly through transmission in the food chain. Herein, we developed the artificial intelligence-driven quantification of antibiotic-resistant bacteria in food using a color...

Machine-Learning-Based Spectral Modeling: A Biomimetic Guide for Enhancing Esthetics.

Journal of esthetic and restorative dentistry : official publication of the American Academy of Esthetic Dentistry ... [et al.]
OBJECTIVE: To provide guidelines and means for optimal coverage and distribution of computer models with 1-10 clusters, designed based on an in vivo extensive dental colorimetric database and compare the findings with some reputable shade guides.

Genome-wide association study on color-image-based convolutional neural networks.

PeerJ
BACKGROUND: Convolutional neural networks have excellent modeling abilities to complex large-scale datasets and have been applied to genomics. It requires converting genotype data to image format when employing convolutional neural networks to genome...