AIMC Topic: Humans

Clear Filters Showing 41981 to 41990 of 95995 articles

Identification of Human Cell Cycle Phase Markers Based on Single-Cell RNA-Seq Data by Using Machine Learning Methods.

BioMed research international
The cell cycle is composed of a series of ordered, highly regulated processes through which a cell grows and duplicates its genome and eventually divides into two daughter cells. According to the complex changes in cell structure and biosynthesis, th...

Novel Crow Swarm Optimization Algorithm and Selection Approach for Optimal Deep Learning COVID-19 Diagnostic Model.

Computational intelligence and neuroscience
Due to the COVID-19 pandemic, computerized COVID-19 diagnosis studies are proliferating. The diversity of COVID-19 models raises the questions of which COVID-19 diagnostic model should be selected and which decision-makers of healthcare organizations...

Recall Network: A Simple Brain-Inspired Algorithm for Classification.

Computational intelligence and neuroscience
The latest development of neuroscience has deepened the understanding of the information-processing mechanisms in the human brain and inspired a couple of sophisticated computational methods, such as deep learning, memory networks, and hierarchical t...

Deep Learning-Based CT Imaging in the Diagnosis of Treatment Effect of Pulmonary Nodules and Radiofrequency Ablation.

Computational intelligence and neuroscience
To study the effect of computerized tomography (CT) images based on deep learning algorithms on the diagnosis of pulmonary nodules and the effect of radiofrequency ablation (RFA), the -shaped fully convolutional neural network (FCNN) (-Net) was enhan...

Application and Prospect Analysis of Artificial Intelligence in the Field of Physical Education.

Computational intelligence and neuroscience
The development of AI technology has a significant impact on every sector of business. Artificial intelligence uses this technology to reduce the amount of work required, duplicate work, and increase the accuracy of work by modelling human behaviour ...

A Deep Learning Model for Automated Segmentation of Geographic Atrophy Imaged Using Swept-Source OCT.

Ophthalmology. Retina
PURPOSE: To present a deep learning algorithm for segmentation of geographic atrophy (GA) using en face swept-source OCT (SS-OCT) images that is accurate and reproducible for the assessment of GA growth over time.

Development and validation of a deep-learning based assistance system for enhancing laparoscopic control level.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND AND AIMS: Inter-operator variations in the level of intraoperative laparoscope control by surgeons influence surgical outcomes. We aimed to construct a laparoscopic surgery quantification system (LSQS) for real-time evaluation of the surge...

A cumulative sum (CUSUM) analysis studying operative times and complications for a surgeon transitioning from laparoscopic to robot-assisted pediatric pyeloplasty: Defining proficiency and competency.

Journal of pediatric urology
INTRODUCTION: The transition from laparoscopic to robot-assisted procedures leads to potential increase in operative times and health care costs. Cumulative sum (CUSUM) analysis can objectively study the learning curve to detect significant changes i...