AIMC Topic: Female

Clear Filters Showing 20991 to 21000 of 29210 articles

Are computational applications the "crystal ball" in the IVF laboratory? The evolution from mathematics to artificial intelligence.

Journal of assisted reproduction and genetics
Mathematics rules the world of science. Innovative technologies based on mathematics have paved the way for implementation of novel strategies in assisted reproduction. Ascertaining efficient embryo selection in order to secure optimal pregnancy rate...

A robot-based gait training therapy for pediatric population with cerebral palsy: goal setting, proposal and preliminary clinical implementation.

Journal of neuroengineering and rehabilitation
BACKGROUND: The use of robotic trainers has increased with the aim of improving gait function in patients with limitations. Nevertheless, there is an absence of studies that deeply describe detailed guidelines of how to correctly implement robot-base...

Diagnostic Accuracy of Different Machine Learning Algorithms for Breast Cancer Risk Calculation: a Meta-Analysis.

Asian Pacific journal of cancer prevention : APJCP
Objective: The aim of this study was to determine the diagnostic accuracy of different machine learning algorithms for breast cancer risk calculation. Methods: A meta-analysis was conducted of published research articles on diagnostic test accuracy o...

Computer-aided diagnosis of lung nodule classification between benign nodule, primary lung cancer, and metastatic lung cancer at different image size using deep convolutional neural network with transfer learning.

PloS one
We developed a computer-aided diagnosis (CADx) method for classification between benign nodule, primary lung cancer, and metastatic lung cancer and evaluated the following: (i) the usefulness of the deep convolutional neural network (DCNN) for CADx o...

Tumor Detection in Automated Breast Ultrasound Using 3-D CNN and Prioritized Candidate Aggregation.

IEEE transactions on medical imaging
Automated whole breast ultrasound (ABUS) has been widely used as a screening modality for examination of breast abnormalities. Reviewing hundreds of slices produced by ABUS, however, is time consuming. Therefore, in this paper, a fast and effective c...

Convolutional Neural Networks for Neuroimaging in Parkinson's Disease: Is Preprocessing Needed?

International journal of neural systems
Spatial and intensity normalizations are nowadays a prerequisite for neuroimaging analysis. Influenced by voxel-wise and other univariate comparisons, where these corrections are key, they are commonly applied to any type of analysis and imaging moda...

Classification of Tumor Epithelium and Stroma by Exploiting Image Features Learned by Deep Convolutional Neural Networks.

Annals of biomedical engineering
The tumor-stroma ratio (TSR) reflected on hematoxylin and eosin (H&E)-stained histological images is a potential prognostic factor for survival. Automatic image processing techniques that allow for high-throughput and precise discrimination of tumor ...

Complex-valued unsupervised convolutional neural networks for sleep stage classification.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Despite numerous deep learning methods being developed for automatic sleep stage classification, almost all the models need labeled data. However, obtaining labeled data is a subjective process. Therefore, the labels will be...

Automation of the Differential Digestion Process of Sexual Assault Evidence.

Journal of forensic sciences
Sexual assault evidence samples require the use of a specific process known as a differential digestion to separate sperm from nonsperm cells prior to DNA extraction. An automated differential digestion process was developed using a selective degrada...

Reading the (functional) writing on the (structural) wall: Multimodal fusion of brain structure and function via a deep neural network based translation approach reveals novel impairments in schizophrenia.

NeuroImage
This work presents a novel approach to finding linkage/association between multimodal brain imaging data, such as structural MRI (sMRI) and functional MRI (fMRI). Motivated by the machine translation domain, we employ a deep learning model, and consi...