AIMC Topic: Humans

Clear Filters Showing 56551 to 56560 of 95995 articles

PyHIST: A Histological Image Segmentation Tool.

PLoS computational biology
The development of increasingly sophisticated methods to acquire high-resolution images has led to the generation of large collections of biomedical imaging data, including images of tissues and organs. Many of the current machine learning methods th...

A Method for Identifying Vesicle Transport Proteins Based on LibSVM and MRMD.

Computational and mathematical methods in medicine
With the development of computer technology, many machine learning algorithms have been applied to the field of biology, forming the discipline of bioinformatics. Protein function prediction is a classic research topic in this subject area. Though ma...

Deep pyramid local attention neural network for cardiac structure segmentation in two-dimensional echocardiography.

Medical image analysis
Automatic semantic segmentation in 2D echocardiography is vital in clinical practice for assessing various cardiac functions and improving the diagnosis of cardiac diseases. However, two distinct problems have persisted in automatic segmentation in 2...

Artificial intelligence-based detection of lymph node metastases by PET/CT predicts prostate cancer-specific survival.

Clinical physiology and functional imaging
INTRODUCTION: Lymph node metastases are a key prognostic factor in prostate cancer (PCa), but detecting lymph node lesions from PET/CT images is a subjective process resulting in inter-reader variability. Artificial intelligence (AI)-based methods ca...

Findings from machine learning in clinical medical imaging applications - Lessons for translation to the forensic setting.

Forensic science international
Machine learning (ML) techniques are increasingly being used in clinical medical imaging to automate distinct processing tasks. In post-mortem forensic radiology, the use of these algorithms presents significant challenges due to variability in organ...

Identification and Classification of Enhancers Using Dimension Reduction Technique and Recurrent Neural Network.

Computational and mathematical methods in medicine
Enhancers are noncoding fragments in DNA sequences, which play an important role in gene transcription and translation. However, due to their high free scattering and positional variability, the identification and classification of enhancers have a h...

How to Design AI-Driven Clinical Trials in Nuclear Medicine.

Seminars in nuclear medicine
Artificial intelligence (AI) is an overarching term for a multitude of technologies which are currently being discussed and introduced in several areas of medicine and in medical imaging specifically. There is, however, limited literature and informa...

Pseudo-nuclear staining of cells by deep learning improves the accuracy of automated cell counting in a label-free cellular population.

Journal of bioscience and bioengineering
Deep learning has emerged as a breakthrough tool for the segmentation of images without supporting human experts. Here, we propose an automated approach that uses deep learning to generate pseudo-nuclear staining of cells from phase contrast images. ...

Accuracy of Pedicle Screw Placement and Four Other Clinical Outcomes of Robotic Guidance Technique versus Computer-Assisted Navigation in Thoracolumbar Surgery: A Meta-Analysis.

World neurosurgery
BACKGROUND: Robotic guidance (RG) pedicle screw placement has been increasingly used to improve the rate of insertion accuracy. However, the superiority of the RG technique over computer-assisted navigation (CAN) remains debatable.

CEGAN: Classification Enhancement Generative Adversarial Networks for unraveling data imbalance problems.

Neural networks : the official journal of the International Neural Network Society
The data imbalance problem in classification is a frequent but challenging task. In real-world datasets, numerous class distributions are imbalanced and the classification result under such condition reveals extreme bias in the majority data class. R...