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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

Endocrine Disruptors and Health Effects in Africa: A Call for Action
Conclusion: To address the many challenges posed by EDCs, we argue that Africans should take the lead in prioritization and evaluation of environmental hazards, including EDCs. We recommend the institution of education and training programs for chemical users, adoption of the precautionary principle, establishment of biomonitoring programs, and funding of community-based epidemiology and wildlife research programs led and funded by African institutes and private companies. https://doi.org/10.1289/EHP1774 Received: 16 February 2017 Revised: 22 May 2017 Accepted: 24 May 2017 Published: 22 August 2017 Address correspond...
Source: EHP Research - August 23, 2017 Category: Environmental Health Authors: Daniil Lyalko Tags: Commentary Source Type: research