AIMC Topic: Humans

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DeepMF: deciphering the latent patterns in omics profiles with a deep learning method.

BMC bioinformatics
BACKGROUND: With recent advances in high-throughput technologies, matrix factorization techniques are increasingly being utilized for mapping quantitative omics profiling matrix data into low-dimensional embedding space, in the hope of uncovering ins...

Deep learning approaches for plethysmography signal quality assessment in the presence of atrial fibrillation.

Physiological measurement
OBJECTIVE: Photoplethysmography (PPG) monitoring has been implemented in many portable and wearable devices we use daily for health and fitness tracking. Its simplicity and cost-effectiveness has enabled a variety of biomedical applications, such as ...

Predicting breast cancer risk using personal health data and machine learning models.

PloS one
Among women, breast cancer is a leading cause of death. Breast cancer risk predictions can inform screening and preventative actions. Previous works found that adding inputs to the widely-used Gail model improved its ability to predict breast cancer ...

Mechanizing medicine - Tomorrows history started yesterday.

American journal of surgery
History is by nature a retrospective subject, there usually being an interval between any event, a review or impact of the subject being considered. This NPSA Historian's paper, takes a long and quick historical view of influences that fostered chang...

Machine Learning Methods for Computer-Aided Breast Cancer Diagnosis Using Histopathology: A Narrative Review.

Journal of medical imaging and radiation sciences
Histopathology is a method used for breast cancer diagnosis. Machine learning (ML) methods have achieved success for supervised learning tasks in the medical domain. In this article, we investigate the impact of ML for the diagnosis of breast cancer ...

Automated detection & classification of knee arthroplasty using deep learning.

The Knee
BACKGROUND: Preoperative identification of knee arthroplasty is important for planning revision surgery. However, up to 10% of implants are not identified prior to surgery. The purposes of this study were to develop and test the performance of a deep...

Artificial intelligence approaches using natural language processing to advance EHR-based clinical research.

The Journal of allergy and clinical immunology
The wide adoption of electronic health record systems in health care generates big real-world data that open new venues to conduct clinical research. As a large amount of valuable clinical information is locked in clinical narratives, natural languag...

A novel machine learning based approach for iPS progenitor cell identification.

PLoS computational biology
Identification of induced pluripotent stem (iPS) progenitor cells, the iPS forming cells in early stage of reprogramming, could provide valuable information for studying the origin and underlying mechanism of iPS cells. However, it is very difficult ...

DMCNN: A Deep Multiscale Convolutional Neural Network Model for Medical Image Segmentation.

Journal of healthcare engineering
Medical image segmentation is one of the hot issues in the related area of image processing. Precise segmentation for medical images is a vital guarantee for follow-up treatment. At present, however, low gray contrast and blurred tissue boundaries ar...