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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

Association between Exposure to p,p ′-DDT and Its Metabolite p,p′-DDE with Obesity: Integrated Systematic Review and Meta-Analysis
Conclusions: We classified p,p′-DDT and p,p′-DDE as “presumed” to be obesogenic for humans, based on a moderate level of primary human evidence, a moderate level of primary in vivo evidence, and a moderate level of supporting evidence from in vivo and in vitro studies. https://doi.org/10.1289/EHP527 Received: 17 May 2016 Revised: 04 May 2017 Accepted: 09 May 2017 Published: 18 September 2017 Please address correspondence to M.A. La Merrill, Dept. of Environmental Toxicology, University of California, Davis, 1 Shields Ave., 4245 Meyer Hall, Davis, CA 95616-5270 USA. Telephone: (530) 754-7254. Email: mlamerrill...
Source: EHP Research - September 18, 2017 Category: Environmental Health Authors: Daniil Lyalko Tags: Review Source Type: research