Data Science

    • The Artificial Intelligence (AI) allows the analysis and qualification of data as well as the extraction of targeted information for:
Voir plus
– Help with diagnosis or personalized medicine through the use of patient data history (Electronic Health Record, Real World Evidence, etc.)
– Medical follow-up (processing of monitoring data, e-Health or connected health)
– Drug discovery (intelligent preselection of candidate molecules)
– Extraction of information from raw data, for example textual and creation of structured databases
– Analysis of results from clinical trials or biological databases
– Optimization of the performance of health establishments (processing of administrative data, etc.)
– Optimization of Marketing operations (time, costs etc.)
– Supply chain
– Market access
    • Data preparation
Voir plus
– Database architecture and management (design, operation and administration of the database)
– Detection and management of missing, duplicate or inconsistent data
– Tools: Oracle SQL, Hadoop, Scala, R, python
    • Business Intelligence – Exploration and Data Analysis
Voir plus
– Data visualization
– Biostatistics and consolidation,
– report
– Tools: Tableau, Spotfire, R Shiny, Python, Oracle SQL, Power BI, QlikView
    • Machine Learning & Deep Learning: classification and prediction through the application of learning algorithms on all types of health data.
Voir plus
– Textual document: medical records, test results, etc.
– Structured file: clinical study, results table, etc.
– Database: patients, molecular, etc.
– Imaging: x-rays, scanner, etc.
    • Example of artificial intelligence methods and their applications in the pharmaceutical/healthcare industry
Voir plus
– NLP (Natural Language Processing): text mining, exploitation and structuring of textual data such as patient records or medical reports
– ANN (Artificial Neural Network), RNN (Recurrent Neural Network): processing of historical patient data for risk prediction, monitoring for follow-up or prevention
– CNN (Convolutional Neural Network): image analysis
– Unsupervised learning: labeling for fraud detection
– Random forest, k-means: classification or clustering from clinical trial data
– Data mining: health insurance fraud detection

Nos publications

Etude des publications scientifiques sur le COVID-19
par des méthodes de NLP (Natural Language Processing) pour analyser l’état de l’art des traitements contre le virus.

Article en cours de rédaction
Votre article sera bientôt disponible.

Article en cours de rédaction
Votre article sera bientôt disponible.