AIMC Topic: Humans

Clear Filters Showing 60241 to 60250 of 95995 articles

Artificial intelligence and machine learning in respiratory medicine.

Expert review of respiratory medicine
: The application of artificial intelligence (AI) and machine learning (ML) in medicine and in particular in respiratory medicine is an increasingly relevant topic.: We aimed to identify and describe the studies published on the use of AI and ML in t...

Achieving robotic program best practice performance and cost versus laparoscopy: Two case studies define a framework for optimization.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: Robotic surgery is seen by many hospital administrators and surgeons as slower and more expensive than laparoscopic surgery despite the implementation of commonly held robotic best practices. Multiple factors, including surgeon learning c...

Impact of hybrid supervision approaches on the performance of artificial intelligence for the classification of chest radiographs.

Computers in biology and medicine
PURPOSE: To evaluate the impact of different supervision regimens on the training of artificial intelligence (AI) in the classification of chest radiographs as normal or abnormal in a moderately sized cohort of individuals more likely to be outpatien...

Computer-aided Detection of Brain Metastases in T1-weighted MRI for Stereotactic Radiosurgery Using Deep Learning Single-Shot Detectors.

Radiology
Background Brain metastases are manually identified during stereotactic radiosurgery (SRS) treatment planning, which is time consuming and potentially challenging. Purpose To develop and investigate deep learning (DL) methods for detecting brain meta...

Real-time Concealed Object Detection from Passive Millimeter Wave Images Based on the YOLOv3 Algorithm.

Sensors (Basel, Switzerland)
The detection of objects concealed under people's clothing is a very challenging task, which has crucial applications for security. When testing the human body for metal contraband, the concealed targets are usually small in size and are required to ...

Modeling the Research Landscapes of Artificial Intelligence Applications in Diabetes (GAP).

International journal of environmental research and public health
The rising prevalence and global burden of diabetes fortify the need for more comprehensive and effective management to prevent, monitor, and treat diabetes and its complications. Applying artificial intelligence in complimenting the diagnosis, manag...

A convolutional neural network-based system to classify patients using FDG PET/CT examinations.

BMC cancer
BACKGROUND: As the number of PET/CT scanners increases and FDG PET/CT becomes a common imaging modality for oncology, the demands for automated detection systems on artificial intelligence (AI) to prevent human oversight and misdiagnosis are rapidly ...

MethylNet: an automated and modular deep learning approach for DNA methylation analysis.

BMC bioinformatics
BACKGROUND: DNA methylation (DNAm) is an epigenetic regulator of gene expression programs that can be altered by environmental exposures, aging, and in pathogenesis. Traditional analyses that associate DNAm alterations with phenotypes suffer from mul...

Identifying Lung Cancer Risk Factors in the Elderly Using Deep Neural Networks: Quantitative Analysis of Web-Based Survey Data.

Journal of medical Internet research
BACKGROUND: Lung cancer is one of the most dangerous malignant tumors, with the fastest-growing morbidity and mortality, especially in the elderly. With a rapid growth of the elderly population in recent years, lung cancer prevention and control are ...

Application of a Deep Machine Learning Model for Automatic Measurement of EZ Width in SD-OCT Images of RP.

Translational vision science & technology
PURPOSE: We applied a deep convolutional neural network model for automatic identification of ellipsoid zone (EZ) in spectral domain optical coherence tomography B-scans of retinitis pigmentosa (RP).