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Oral Implantology

INFERENTIAL ANALYSIS OF BIG DATA IN REAL-TIME: ONE GIANT LEAP FOR SPATIOTEMPORAL DIGITAL EPIDEMIOLOGY IN DENTISTRY

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Epidemiological sciences have been evolving at an exponential rate paralleled only by the comparable growth within the discipline of data science. Digital epidemiological studies are playing a vital role in medical science analytics for the past few decades. To date, there are no published attempts at deploying the use of real-time analytics in connection with the disciplines of dentistry. We implemented a real-time statistical analysis in connection with topics in Dental Anatomy and Dental Pathology represented by the maxillary sinus, posterior maxillary teeth, related oral pathology. The purpose is to infer the digital epidemiology based on a continuous stream of raw data retrieved from Google Trends database. Statistical analysis was carried out via Microsoft Excel 2016 and SPSS version 24. Google Trends database was used to retrieve data for digital epidemiology. Real-time analysis and the statistical inference were based on encoding a programming script using Python high-level programming language. A systematic review of the literature was carried out via PubMed-NCBI, the Cochrane Library, and Elsevier databases. The comprehensive analysis of databases of the literature, based on specific keywords search, yielded 491813 published studies. These were distributed as 488,884 (PubMed- NCBI), 1611 (the Cochrane Library), and 1318 (Elsevier). However, there was no single study attempting real-time analytics. Nevertheless, we succeeded in achieving an automated real-time stream of data accompanied by a statistical inference based on data extrapolated from Google Trends. Real-time analytics are of considerable impact when implemented in biological and life sciences as they will tremendously reduce the required resources for research. Predictive analytics, based on artificial neural networks and machine learning algorithms, can be the next step to be deployed in continuation of the real-time systems to prognosticate changes in the temporal trends and the digital epidemiology of phenomena of interest.

Vol. XII (No. 1) 2019 January-March

  1. INFERENTIAL ANALYSIS OF BIG DATA IN REAL-TIME: ONE GIANT LEAP FOR SPATIOTEMPORAL DIGITAL EPIDEMIOLOGY IN DENTISTRY
    Al-Imam A.
  2. POLY(ɛ-CAPROLACTONE) MEMBRANES COATED WITH POLY(4-STYRENESULFONIC ACID-CO-MALEIC ACID)-SODIUM SALT ENHANCE OSTEOGENIC PROPERTIES OF PRE-OSTEOBLASTS MC3T3-E1
    Angwarawong T., Kanjanamekanant K., Angwaravong O., Pavasant P.
  3. FRACTURE RESISTANCE OF MONOLITHIC ZIRCONIA CANTILEVERED FRAMEWORKS IN COMPLETE ARCH-PROSTHESES SUPPORTED BY TILTED OR PARALLEL IMPLANTS
    De Francesco M., Di Fiore A., Bruno G., Gargari M., Martelli M., Barnaba P., Marino M., Quercia A., Ceruso F.M.
  4. RARE CASE OF INVERTED IMPACTED CANINE IN INFRA-ORBITARY POSITION REQUIRING SURGICAL THERAPY
    Falisi G., Cutilli T., Rastelli E., Bernardi S., Continenza M.A., Vittorini Velasquez P., Severino M.
  5. VERTICAL AND HORIZONTAL BONE REGENERATION
    Ciulli E., Fabretti M., Casale F., Lanzuolo S., Gargari M.
  6. ORTHODONTIC EXTRUSION FOR PRE-IMPLANT SITE ENHANCEMENT IN A POSTERIOR AREA: AN INTERDISCIPLINARY CASE REPORT
    Giannetti L., Consolo U., Vecci F., Apponi R.
  7. PROGNOSIS OF SHORT IMPLANTS IN ORAL REHABILITATION: WHERE DO WE STAND TODAY?
    Rameh S., Menhall A., Younes R.
  8. FRACTURES OF CROWN, ROOT AND AVULSION OF PERMANENT TEETH: CASE REPORT OF COMPLEX TRAUMATIC DENTAL INJURIES
    Di Taranto V., Severino M., Agrestini C., Barlattani A.
  9. ECC FULL REHABILITATION WITH INDIRECT COMPOSITE RESTORATIONS: A CASE REPORT
    Gallusi G., Severino M., Cardelli P., Barlattani jr. A.
  10. DIRECT ADHESIVE REHABILITATION WITH DOUBLE INDEX TECHNIQUE: A CASE REPORT
    Libonati A., Severino M., Dolci A., Barlattani A.
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  1. INFERENTIAL ANALYSIS OF BIG DATA IN REAL-TIME: ONE GIANT LEAP FOR SPATIOTEMPORAL DIGITAL EPIDEMIOLOGY IN DENTISTRY

    Al-Imam A.
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