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Total 2 results found since Jan 2013.

A Novel Deep Neural Network Model for Multi-Label Chronic Disease Prediction
Conclusions concludes this work along with future work. Dataset and Data Preprocessing In the work, we mainly focus on multiple chronic disease classification. It can be formulated into a multi-label classification problem. There are three common chronic diseases are selected from the physical examination records: hypertension (H), diabetes (D), and fatty liver (FL). In the experiments, the physical examination datasets are collected from a local medical center, which contain 110,300 physical examination records from about 80,000 anonymous patients (Li et al., 2017a,b). Sixty-two feature items are selected from over 100...
Source: Frontiers in Genetics - April 23, 2019 Category: Genetics & Stem Cells Source Type: research

Consider the Promises and Challenges of Medical Image Analyses Using Machine Learning
Medical imaging saves millions of lives each year, helping doctors detect and diagnose a wide range of diseases, from cancer and appendicitis to stroke and heart disease. Because non-invasive early disease detection saves so many lives, scientific investment continues to increase. Artifical intelligence (AI) has the potential to revolutionize the medical imaging industry by sifting through mountains of scans quickly and offering providers and patients with life-changing insights into a variety of diseases, injuries, and conditions that may be hard to detect without the supplemental technology. Images are the largest source...
Source: MDDI - June 2, 2020 Category: Medical Devices Authors: Partha S. Anbil and Michael T. Ricci Tags: Imaging Source Type: news