Omics : a journal of integrative biology
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Artificial intelligence, machine learning, health care robots, and algorithms for clinical decision-making are currently being sought after in diverse fields of clinical medicine and bioengineering. The field of personalized medicine stands to benefit from new technologies so as to harness the omics big data, for example, to individualize and accelerate cancer diagnostics and therapeutics in particular. In this overarching context, breast cancer is one of the most common malignancies worldwide with multiple underlying molecular etiologies and each subtype displaying diverse clinical outcomes. ⋯ This expert review describes and examines, first, the SVM models employed to forecast breast cancer subtypes using diverse systems science data, including transcriptomics, epigenetics, proteomics, and radiomics, as well as biological pathway, clinical, pathological, and biochemical data. Then, we compare the performance of the present SVM and other diagnostic and therapeutic prediction models across the data types. We conclude by emphasizing that data integration is a critical bottleneck in systems science, cancer research and development, and health care innovation and that SVM and machine learning approaches offer new solutions and ways forward in biomedical, bioengineering, and clinical applications.
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Artificial intelligence (AI) is one of the key drivers of digital health. Digital health and AI applications in medicine and biology are emerging worldwide, not only in resource-rich but also resource-limited regions. AI predates to the mid-20th century, but the current wave of AI builds in part on machine learning (ML), big data, and algorithms that can learn from massive amounts of online user data from patients or healthy persons. ⋯ We examine and share here the lessons learned in current attempts to implement AI and digital health in CHD for precision risk prediction and diagnosis in resource-limited settings. These top 10 lessons on AI and digital health summarized in this expert review are relevant broadly beyond CHD in cardiology and medical innovations. As with AI itself that calls for systems approaches to data capture, analysis, and interpretation, both developed and developing countries can usefully learn from their respective experiences as digital health continues to evolve worldwide.
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Digitalization and digital health are transforming research practices, while economic growth is increasingly driven by the information commons. In the case of biological sciences, information commons, such as public biobanks and free/libre open source software (FLOSS), are of paramount importance for both research and the bioeconomy. In a time of digitalization, however, information commons are vulnerable to violations, such as the free-rider problem, that render the commons unsustainable. ⋯ Focusing on the interaction between two biological/bioinformatics commons, namely public biobanks and the FLOSS, we have set up an ecosystem relying on a blockchain technology. The proposed governance mechanism protects the information commons from the free-rider problem and guarantees their sustainability without hampering their operational framework. Our model demonstrates the interdependence and protection of the information commons not as an abstract theoretical exercise, but rather as a physical reality on the digital ontological matrix.
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Review Historical Article
Digging Deeper into Precision/Personalized Medicine: Cracking the Sugar Code, the Third Alphabet of Life, and Sociomateriality of the Cell.
Precision/personalized medicine is a hot topic in health care. Often presented with the motto "the right drug, for the right patient, at the right dose, and the right time," precision medicine is a theory for rational therapeutics as well as practice to individualize health interventions (e.g., drugs, food, vaccines, medical devices, and exercise programs) using biomarkers. Yet, an alien visitor to planet Earth reading the contemporary textbooks on diagnostics might think precision medicine requires only two biomolecules omnipresent in the literature: nucleic acids (e.g., DNA) and proteins, known as the first and second alphabet of biology, respectively. ⋯ The concept of sociomateriality integrates these two explanations by highlighting the inherent entanglement of the social and the material contributions to knowledge and what is presented to us as reality from everyday laboratory life. Hence, we present a hypothesis based on a sociomaterial conceptual lens: because materiality and synthesis of glycans are not directly driven by a template, and thus more complex and open ended than sequencing of a finite length genome, social construction of expectations from unraveling of the sugar code versus the DNA code might have evolved differently, as being future-uncertain versus future-proof, respectively, thus potentially explaining the "sugar lag" in precision/personalized medicine diagnostics over the past decades. We conclude by introducing systems scientists, physicians, and biotechnology industry to the concept, practice, and value of responsible innovation, while glycomedicine and other emerging biomarker technologies (e.g., metagenomics and pharmacomicrobiomics) transition to applications in health care, ecology, pharmaceutical/diagnostic industries, agriculture, food, and bioengineering, among others.
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In May 2019, the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services warned that "around one million animal and plant species are now threatened with extinction." In September 2019, Naomi Klein, an astute writer on environmental change, described the interconnected social and ecological breakdowns on the planet in a new book. Ecological crises noted by these and other scholars speak well to the rise of planetary health as a new scholarship. Loss of biodiversity has manifold negative impacts on health, for example, rise of zoonotic infections and changes in healthy microbiome. ⋯ Third, for critically informed governance of emerging technologies in planetary health (e.g., glycomics, artificial intelligence, health care robots), I refer to a question highlighted recently (Frodeman, 2019): "When Plato (more exactly, Juvenal) asked who guards the guardians, he was questioning whether any group can be trusted to look past its own interests for the common good." Hence, it is time we broaden the question "Who will guard the guardians?" beyond the scientific community, to actors in science policy as well. Policy questions cannot be limited to "which social issues emerge from a new technology?" but ought to include, "who should be framing science and technology policy, and why?" Youth leaders of the global climate movement such as Greta Thunberg and others are now rightly asking these epistemological questions that might contribute toward a new social contract on health for all sentient beings on planet Earth. While ecological changes accelerate and a new space industry is emerging, governance for planetary health will continue to be at the epicenter of systems thinking, responsible innovation and science policy in the 21st century.