| P50 | author | Alessandro Blasimme | Q54455456 |
| | Marcello Ienca | Q57912630 |
| | Effy Vayena | Q46003499 |
| P2860 | cites work | Big data to smart data in Alzheimer's disease: The brain health modeling initiative to foster actionable knowledge | Q26745466 |
| | Stakeholders' views on the ethical challenges of pragmatic trials investigating pharmaceutical drugs | Q27332116 |
| | The diagnosis and management of mild cognitive impairment: a clinical review | Q27693353 |
| | Is dementia research ready for big data approaches? | Q28648089 |
| | Identifying personal genomes by surname inference | Q29619963 |
| | Dementia Prevention: optimizing the use of observational data for personal, clinical, and public health decision-making | Q30978649 |
| | Could Big Data be the end of theory in science? A few remarks on the epistemology of data-driven science | Q30992970 |
| | Big data and data repurposing - using existing data to answer new questions in vascular dementia research | Q33568328 |
| | Towards new human rights in the age of neuroscience and neurotechnology | Q33736238 |
| | A conceptual framework for research on subjective cognitive decline in preclinical Alzheimer's disease | Q35049917 |
| | FDA regulation of mobile health technologies | Q87431235 |
| | Dementia prevention hits the headlines at AAIC17 | Q88683683 |
| | Spontaneous Reversion of Clinical Conditions Measuring the Risk Profile of the Individual: From Frailty to Mild Cognitive Impairment | Q46087950 |
| | The role of big data in understanding late-life cognitive decline: E Unum, Pluribus | Q46991315 |
| | What Is Trust? Ethics and Risk Governance in Precision Medicine and Predictive Analytics | Q47106092 |
| | The sterile controversy on the amyloid cascade hypothesis. | Q48110778 |
| | Big data: could it ever cure Alzheimer's disease? | Q48546732 |
| | From Evidence to Action: Promoting a Multidimensional Approach to Mild Cognitive Impairment. | Q50732474 |
| | Issues about the use of subjective cognitive decline in Alzheimer's disease research. | Q50779388 |
| | Predictive value of APOE-ε4 allele for progression from MCI to AD-type dementia: a meta-analysis. | Q51803759 |
| | Caught in the web: informed consent for online health research | Q56773073 |
| | Big Data: Astronomical or Genomical? | Q35685054 |
| | A cybersecurity primer for translational research | Q35899526 |
| | Spontaneous Reversion of Mild Cognitive Impairment to Normal Cognition: A Systematic Review of Literature and Meta-Analysis | Q36097955 |
| | Becoming partners, retaining autonomy: ethical considerations on the development of precision medicine | Q36181509 |
| | Neuropsychiatric symptoms as early manifestations of emergent dementia: Provisional diagnostic criteria for mild behavioral impairment | Q36385255 |
| | Forecasting the Incidence of Dementia and Dementia-Related Outpatient Visits With Google Trends: Evidence From Taiwan. | Q36440955 |
| | Learning Classification Models of Cognitive Conditions from Subtle Behaviors in the Digital Clock Drawing Test. | Q36767119 |
| | An investigation of the validity of the virtual spatial navigation assessment | Q37388940 |
| | Preclinical Alzheimer's disease and its outcome: a longitudinal cohort study | Q37524511 |
| | The global prevalence of dementia: a systematic review and metaanalysis | Q38073027 |
| | The case for rejecting the amyloid cascade hypothesis. | Q38501528 |
| | Multidimensional Evidence Generation and FDA Regulatory Decision Making: Defining and Using "Real-World" Data | Q38675569 |
| | Intelligent Assistive Technology for Alzheimer's Disease and Other Dementias: A Systematic Review | Q39145454 |
| | Alzheimer's Disease: Biomarkers in the Genome, Blood, and Cerebrospinal Fluid | Q39217840 |
| | Identifying incipient dementia individuals using machine learning and amyloid imaging | Q40170401 |
| | The digital phenotype | Q40279548 |
| | Mild behavioral impairment: Ethical, methodological and clinical reflections | Q40603858 |
| | Retinal amyloid pathology and proof-of-concept imaging trial in Alzheimer's disease | Q41845723 |
| | Alzheimer's disease: From big data to mechanism | Q42590102 |
| | Big data, aging, and dementia: pathways for international harmonization on data sharing | Q42623294 |
| | Alzheimer's disease drug development pipeline: 2017. | Q42655757 |
| | NHS data sharing deal with Google prompts concern | Q42693843 |
| | Biomedical Big Data: New Models of Control Over Access, Use and Governance. | Q45934130 |
| | Prediction of Alzheimer disease in subjects with amnestic and nonamnestic MCI. | Q45960786 |
| P275 | copyright license | Creative Commons Attribution 4.0 International | Q20007257 |
| P6216 | copyright status | copyrighted | Q50423863 |
| P921 | main subject | big data | Q858810 |
| | research ethics | Q1132684 |
| | ethics policy | Q59812666 |
| | big data ethics | Q45029591 |
| | data ethics | Q45933174 |
| P304 | page(s) | 13 | |
| P577 | publication date | 2018-02-06 | |
| P1433 | published in | Frontiers in Medicine | Q27726181 |
| P1476 | title | Big Data and Dementia: Charting the Route Ahead for Research, Ethics, and Policy | |
| P478 | volume | 5 | |