AIMC Topic: Algorithms

Clear Filters Showing 27081 to 27090 of 28713 articles

[Artificial intelligence and machine learning in oncologic imaging].

Der Pathologe
Machine learning (ML) is entering many areas of society, including medicine. This transformation has the potential to drastically change medicine and medical practice. These aspects become particularly clear when considering the different stages of o...

PheMap: a multi-resource knowledge base for high-throughput phenotyping within electronic health records.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Developing algorithms to extract phenotypes from electronic health records (EHRs) can be challenging and time-consuming. We developed PheMap, a high-throughput phenotyping approach that leverages multiple independent, online resources to s...

Clinical applications of artificial intelligence in urologic oncology.

Current opinion in urology
PURPOSE OF REVIEW: This review aims to shed light on recent applications of artificial intelligence in urologic oncology.

Machine learning in the optimization of robotics in the operative field.

Current opinion in urology
PURPOSE OF REVIEW: The increasing use of robotics in urologic surgery facilitates collection of 'big data'. Machine learning enables computers to infer patterns from large datasets. This review aims to highlight recent findings and applications of ma...

An Explainable Artificial Intelligence Predictor for Early Detection of Sepsis.

Critical care medicine
OBJECTIVES: Early detection of sepsis is critical in clinical practice since each hour of delayed treatment has been associated with an increase in mortality due to irreversible organ damage. This study aimed to develop an explainable artificial inte...

Applications of neural networks in urology: a systematic review.

Current opinion in urology
PURPOSE OF REVIEW: Over the last decade, major advancements in artificial intelligence technology have emerged and revolutionized the extent to which physicians are able to personalize treatment modalities and care for their patients. Artificial inte...

BeadNet: deep learning-based bead detection and counting in low-resolution microscopy images.

Bioinformatics (Oxford, England)
MOTIVATION: An automated counting of beads is required for many high-throughput experiments such as studying mimicked bacterial invasion processes. However, state-of-the-art algorithms under- or overestimate the number of beads in low-resolution imag...

[Discrimination of lung cancer and adjacent normal tissues based on permittivity by optimized probabilistic neural network].

Nan fang yi ke da xue xue bao = Journal of Southern Medical University
OBJECTIVE: To propose a probabilistic neural network classification method optimized by simulated annealing algorithm (SA-PNN) to discriminate lung cancer and adjacent normal tissues based on permittivity.