AIMC Topic: Humans

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Breast cancer detection and classification with digital breast tomosynthesis: a two-stage deep learning approach.

Diagnostic and interventional radiology (Ankara, Turkey)
PURPOSE: The purpose of this study was to propose a new computer-assisted two-staged diagnosis system that combines a modified deep learning (DL) architecture (VGG19) for the classification of digital breast tomosynthesis (DBT) images with the detect...

A multi-memory-augmented network with a curvy metric method for video anomaly detection.

Neural networks : the official journal of the International Neural Network Society
Anomaly detection task in video mainly refers to identifying anomalous events that do not conform to the learned normal patterns in the inferring phase. However, the Euclidean metric used in the learning and inferring phase by the most of the existin...

MoMA: Momentum contrastive learning with multi-head attention-based knowledge distillation for histopathology image analysis.

Medical image analysis
There is no doubt that advanced artificial intelligence models and high quality data are the keys to success in developing computational pathology tools. Although the overall volume of pathology data keeps increasing, a lack of quality data is a comm...

Utility of a Large Language Model for Extraction of Clinical Findings from Healthcare Data following Lung Ablation: A Feasibility Study.

Journal of vascular and interventional radiology : JVIR
To assess the feasibility of utilizing a large language model (LLM) in extracting clinically relevant information from healthcare data in patients who have undergone microwave ablation for lung tumors. In this single-center retrospective study, radio...

Artificial intelligence applications in smile design dentistry: A scoping review.

Journal of prosthodontics : official journal of the American College of Prosthodontists
PURPOSE: Artificial intelligence (AI) applications are growing in smile design and aesthetic procedures. The current expansion and performance of AI models in digital smile design applications have not yet been systematically documented and analyzed....

An explainable deep learning platform for molecular discovery.

Nature protocols
Deep learning approaches have been increasingly applied to the discovery of novel chemical compounds. These predictive approaches can accurately model compounds and increase true discovery rates, but they are typically black box in nature and do not ...

Artificial Intelligence as a Discriminator of Competence in Urological Training: Are We There?

The Journal of urology
PURPOSE: Assessments in medical education play a central role in evaluating trainees' progress and eventual competence. Generative artificial intelligence is finding an increasing role in clinical care and medical education. The objective of this stu...

Predicting 30-day reoperation following primary total knee arthroplasty: machine learning model outperforms the ACS risk calculator.

Medical & biological engineering & computing
The ACS risk calculator (ARC) has proven less effective in predicting patient-specific risk of early reoperation after primary total knee arthroplasty (TKA), compromising care quality and cost efficiency. This study compared the performance of a mach...

Automated segmentation of dental restorations using deep learning: exploring data augmentation techniques.

Oral radiology
OBJECTIVES: Deep learning has revolutionized image analysis for dentistry. Automated segmentation of dental radiographs is of great importance towards digital dentistry. The performance of deep learning models heavily relies on the quality and divers...

Explainable AI and trust: How news media shapes public support for AI-powered autonomous passenger drones.

Public understanding of science (Bristol, England)
This study delves into the intricate relationships between attention to AI in news media, perceived AI explainability, trust in AI, and public support for autonomous passenger drones. Using structural equation modelling ( = 1,002), we found significa...