Notice bibliographique
Résumé
Abstract Advances in genomic technology have expanded the number of tests for which individuals can obtain additional risk estimates about their susceptibilities to disease. Genomic information that predicts disease risk is relevant to insurers because the amount that policyholders pay for insurance coverage is determined by assessing their level of disease risk. Without access to genomic information, insurers are concerned that individuals may purchase more insurance at unadjusted premiums, leading to adverse selection. However, not all genomic information is useful from an insurance viewpoint, and the complexity of interpreting genetic variants, coupled with the possibility of incidental findings, raises ethical issues with using applicants' genomic testing results. Moreover, some people are reluctant to undergo genetic testing or participate in genomic research because of the fear that they may have difficulty in obtaining insurance after disclosing their genomic results to insurers. As genomic testing becomes more prevalent, there are concerns that sections of the population will be denied insurance because of their genetic profile. The question of what governments should do about this is one that has been debated in many countries. Key Concepts Insurers request genetic test results from applicants to enable them to make an accurate assessment of their health risks in the underwriting process. However, patients and the public fear that they may have difficulty in obtaining insurance after disclosing their genomic results to insurers. Not all genetic tests are useful for insurance underwriting; this will depend on the clinical validity and utility of the test, the nature and penetrance of the disease and the availability of treatment or management strategies. Use of genomic data for insurance underwriting also raises ethical concerns due to the complexity of interpreting genomic variants and the possibility of discovering incidental findings from genomic data. The public's fear of genetic discrimination by insurers appears to have consequences for public health and genetic research programme initiatives. Moratoria or legislation to prohibit the use of genetic test results by insurers has been adopted by many countries to prevent insurance discrimination. However, other ways to regulate the use of genetic tests in insurance include human rights or privacy‐based approaches.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».