AIMC Topic: Databases, Factual

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Does including machine learning predictions in ALS clinical trial analysis improve statistical power?

Annals of clinical and translational neurology
OBJECTIVE: Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease which leads to progressive muscle weakness and eventually death. The increasing availability of large ALS clinical trial datasets have generated much interest in developing...

Applications of Artificial Intelligence and Big Data Analytics in m-Health: A Healthcare System Perspective.

Journal of healthcare engineering
Mobile health (m-health) is the term of monitoring the health using mobile phones and patient monitoring devices etc. It has been often deemed as the substantial breakthrough in technology in this modern era. Recently, artificial intelligence (AI) an...

PASCAL: a pseudo cascade learning framework for breast cancer treatment entity normalization in Chinese clinical text.

BMC medical informatics and decision making
BACKGROUNDS: Knowledge discovery from breast cancer treatment records has promoted downstream clinical studies such as careflow mining and therapy analysis. However, the clinical treatment text from electronic health data might be recorded by differe...

Clinically applicable histopathological diagnosis system for gastric cancer detection using deep learning.

Nature communications
The early detection and accurate histopathological diagnosis of gastric cancer increase the chances of successful treatment. The worldwide shortage of pathologists offers a unique opportunity for the use of artificial intelligence assistance systems ...

Robustness study of noisy annotation in deep learning based medical image segmentation.

Physics in medicine and biology
Partly due to the use of exhaustive-annotated data, deep networks have achieved impressive performance on medical image segmentation. Medical imaging data paired with noisy annotation are, however, ubiquitous, but little is known about the effect of ...

Deep Learning Based Software to Identify Large Vessel Occlusion on Noncontrast Computed Tomography.

Stroke
BACKGROUND AND PURPOSE: Reliable recognition of large vessel occlusion (LVO) on noncontrast computed tomography (NCCT) may accelerate identification of endovascular treatment candidates. We aim to validate a machine learning algorithm (MethinksLVO) t...

Learning image features with fewer labels using a semi-supervised deep convolutional network.

Neural networks : the official journal of the International Neural Network Society
Learning feature embeddings for pattern recognition is a relevant task for many applications. Deep learning methods such as convolutional neural networks can be employed for this assignment with different training strategies: leveraging pre-trained m...

Computer-Aided System for the Detection of Multicategory Pulmonary Tuberculosis in Radiographs.

Journal of healthcare engineering
The early screening and diagnosis of tuberculosis plays an important role in the control and treatment of tuberculosis infections. In this paper, an integrated computer-aided system based on deep learning is proposed for the detection of multiple cat...

Calculation of immune cell proportion from batch tumor gene expression profile based on support vector regression.

Journal of bioinformatics and computational biology
In addition to tumor cells, a large number of immune cells are found in the tumor microenvironment (TME) of cancer patients. Tumor-infiltrating immune cells play an important role in tumor progression and patient outcome. We improved the relative pro...