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.
Elsevier,
Clinical Decision Support and Beyond (Third Edition): Progress and Opportunities in Knowledge-Enhanced Health and Healthcare, 2023, Pages 715-725
This chapter advances the UN SDG Goal 3: Good Health and Goal 10: Reduced Inequalities by discussing the components of a technical infrastructure to support PHM, including data sources (registries, electronic health records), data analytics tools, patient outreach and engagement tools, and patient tracking dashboards along with real-world examples of PHM programs focused on chronic disease management, genetic testing for hereditary cancers, colorectal cancer screening, COVID-19 testing and vaccination, and tobacco cessation.
This content supports the SDG Goal 3: Good health and well-being by providing the current knowledge regarding standard therapy and suggestions based on the literature for AIH patients being nonresponders to standard therapy and difficult-to-manage AIH patients to standard therapy.
This content supports the SDG Goal 3: Good health and well-being by presenting the antiviral strategies available to treat viral infections, those used to treat chronic viral hepatitis, and the mechanisms of action of drugs approved or at the developmental stage.
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.
This Viewpoint supprts SDG 3 by focusing on the health and wellbeing of people with disabilities in Europe and discussing inclusive health sectors, which could aid the protection of the human rights of people with disabilities and the promotion of their health.
