AIMC Topic: Humans

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Machine learning algorithms as new screening approach for patients with endometriosis.

Scientific reports
Endometriosis-a systemic and chronic condition occurring in women of childbearing age-is a highly enigmatic disease with unresolved questions. While multiple biomarkers, genomic analysis, questionnaires, and imaging techniques have been advocated as ...

Comparison of different feature extraction methods for applicable automated ICD coding.

BMC medical informatics and decision making
BACKGROUND: Automated ICD coding on medical texts via machine learning has been a hot topic. Related studies from medical field heavily relies on conventional bag-of-words (BoW) as the feature extraction method, and do not commonly use more complicat...

Self-relabeling for noise-tolerant retina vessel segmentation through label reliability estimation.

BMC medical imaging
BACKGROUND: Retinal vessel segmentation benefits significantly from deep learning. Its performance relies on sufficient training images with accurate ground-truth segmentation, which are usually manually annotated in the form of binary pixel-wise lab...

PRCTC: a machine learning model for prediction of response to corticosteroid therapy in COVID-19 patients.

Aging
Corticosteroid has been proved to be one of the few effective treatments for COVID-19 patients. However, not all the patients were suitable for corticosteroid therapy. In this study, we aimed to propose a machine learning model to forecast the respon...

Trustworthy Augmented Intelligence in Health Care.

Journal of medical systems
Augmented Intelligence (AI) systems have the power to transform health care and bring us closer to the quadruple aim: enhancing patient experience, improving population health, reducing costs, and improving the work life of health care providers. Ear...

Application of Artificial Intelligence in Cardiovascular Imaging.

Journal of healthcare engineering
During the last two decades, as computer technology has matured and business scenarios have diversified, the scale of application of computer systems in various industries has continued to expand, resulting in a huge increase in industry data. As for...

Design of Optimal Deep Learning-Based Pancreatic Tumor and Nontumor Classification Model Using Computed Tomography Scans.

Journal of healthcare engineering
Pancreatic tumor is a lethal kind of tumor and its prediction is really poor in the current scenario. Automated pancreatic tumor classification using computer-aided diagnosis (CAD) model is necessary to track, predict, and classify the existence of p...

Computational Intelligence Method for Detection of White Blood Cells Using Hybrid of Convolutional Deep Learning and SIFT.

Computational and mathematical methods in medicine
Infection diseases are among the top global issues with negative impacts on health, economy, and society as a whole. One of the most effective ways to detect these diseases is done by analysing the microscopic images of blood cells. Artificial intell...

Boosting RGB-D Saliency Detection by Leveraging Unlabeled RGB Images.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Training deep models for RGB-D salient object detection (SOD) often requires a large number of labeled RGB-D images. However, RGB-D data is not easily acquired, which limits the development of RGB-D SOD techniques. To alleviate this issue, we present...

A Hybrid Framework for Intrusion Detection in Healthcare Systems Using Deep Learning.

Frontiers in public health
The unbounded increase in network traffic and user data has made it difficult for network intrusion detection systems to be abreast and perform well. Intrusion Systems are crucial in e-healthcare since the patients' medical records should be kept hig...