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Sources used when seeking reproductive health information in the UK are not necessarily the most trusted, with accessibility being an important factor. Ensuring better fertility and reproductive health information during school education may offset the impact of unreliable sources.
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On Rare Disease day, Elsevier has launched a new scientific journal called Rare. Open research in rare diseases. Elsevier dedicates a peer-reviewed publication specifically to these lesser known or unknown disorders, with the aim of having a clinical impact on the lives of patients and their families.
This paper tries to model the expenditure that will be required to attain full UHC in India.
This Article supports SDG 3 by assessing whether access to free health prenatal health care affects adverse outcomes in newborns in Switzerland. The findings suggest that the health-care policy impacted some, but not all, outcomes.
![State-of-the-art lipidomics technologies and assays.](https://sdgresources.relx.com/sites/default/files/styles/sus_content_listing_image/public/1-s2.0-s1367593122001417-gr1_lrg.jpg?itok=QJyhzgL8)
Despite being a relatively new addition to the Omics' landscape, lipidomics is increasingly being recognized as an important tool for the identification of druggable targets and biochemical markers.
![Proposed blockchain-orchestrated deep learning approach for secure data transmission in IoT-enabled healthcare system.](https://sdgresources.relx.com/sites/default/files/styles/sus_content_listing_image/public/1-s2.0-s0743731522002106-gr001_lrg.jpg?itok=QPCHrxvI)
The Internet of Things (IoT) has revolutionized the traditional healthcare systems into intelligent system by allowing remote access and continuous monitoring of patient data. Specifically, first a novel scalable blockchain architecture is proposed to ensure data integrity and secure data transmission by leveraging Zero Knowledge Proof (ZKP) mechanism. Then, BDSDT integrates with the off-chain storage InterPlanetary File System (IPFS) to address difficulties with data storage costs and with an Ethereum smart contract to address data security issues.
The paper looks at the developments on some poorly performing districts on SDGs in India to take stock of how far the country is from their national targets.
Evaluating the bias and fairness of ML models has drawn much attention in the machine learning and statistics community. Researchers have proposed methods to assess and mitigate the bias for various applications that could adversely affect underrepresented groups, like recidivism prediction, credit risk prediction, and income prediction.
Noise and air pollution coexist in many urban/industrial environments, and therefore should be studied using co-exposure models. This study indicates that by investigating one individual stressor at a time, we may significantly underestimate the health risks since noise and air pollution have apparent additive health effects on the cardiovascular system and the brain. The study findings are strongly suggestive of additive/synergistic adverse cardiovascular health effects by environmental stressors that typically co-occur in large cities and urban/industrial settings, with a significant contribution to the disease burden and health care costs that may even exceed the most pessimistic scenarios.
This Article supports SDG 3 by assessing the incidence of HCV infection among people with HIV, during different periods statified by level of access to direct-acting antiviral therapy for HCV. Broader access to this treatment was associated, through a "treatment as prevention" effect, with lower incidence of HCV infection - approximately 50% lower in the period of broad access to the treatment compared with the period before access to the treatment.