European Symposium on Precision Medicine in Allergy and Airways Diseases: Report of the European Union Parliament Symposium (October 14, 2015)
Bibliographic record
Abstract
The European Academy of Allergy and Clinical Immunology (EAACI), the European Rhinologic Society (ERS), and the European Medical Association (EMA) organized, on October 14, 2015, a symposium in the European Parliament in Brussels on Precision Medicine in Allergy and Airways Diseases, hosted by MEP David Borrelli, and with active participation of the EU Commissioner for Health and Food Safety Vytenis Andriukaitis, MEP Sirpa Pietikainen, Chair of the European Parliament Interest Group on Allergy and Asthma, the European Respiratory Society (ERS), the European Federations of Allergy and Airways Diseases Patients Associations (EFA), the Global Allergy and Asthma European Network (Ga2len), Allergic Rhinitis and Its Impact on Asthma (ARIA), and the Respiratory Effectiveness Group (REG). The socioeconomic impact of allergies and chronic airways diseases cannot be underestimated, as they represent the most frequently diagnosed chronic noncommunicable diseases in the EU; 30% of the total European population is suffering from allergies and asthma, and more than half are deprived from adequate diagnosis and treatment. Precision medicine represents a novel approach, embracing four key features: personalized care based on molecular, immunologic, and functional endotyping of the disease, with participation of the patient in the decision-making process of therapeutic actions, and considering predictive and preventive aspects of the treatment. Implementation of precision medicine into clinical practice may help to achieve the arrest of the epidemic of allergies and chronic airways diseases. Participants underscored the need for optimal patient care in Europe, supporting joint action plans for disease prevention, patient empowerment, and cost-effective treatment strategies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.040 | 0.020 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.018 | 0.012 |
| Insufficient payload (model declined to judge) | 0.019 | 0.012 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".