Challenges in Developing Effective Clinical Decision Support Systems
Notice bibliographique
Résumé
Introduction to CDSSDecision making is one of the most important and frequent aspects of our daily activities.Personal decisions display our characteristics, behavior, successes, failures, and the nature of our personalities.These decisions affect us in different ways, such as reasoning style, relationships, education, purchasing, careers, investments, health, and entertainment.The effectiveness of such decisions is affected by our age, knowledge, environment, economic status, and regulations.Our business related decisions are influenced by our knowledge, experience, and the availability of supporting systems in terms of employed processes, standards and techniques.Due to the importance of decision making, different technologies have been developed to help humans make effective decisions in the shortest time.Current advances in Information and Communication Technology (ICT) have revolutionized the way people communicate, share information, and make effective decisions.Decision making is a complex intellectual task that uses assistance from different resources.In the past, such resources were restricted to personal knowledge, experience, logic, and human mentors.However, the norms of current society and existing technologies have enhanced critical decision making.Educational systems are not restricted to physical classrooms any more; on-line education is gradually taking over.Knowledge about a technical domain can be obtained easily using Internet search engines and free on-line scientific articles.Mentorship has expanded from colleagues and friends to a large community of domain experts through subject-specific social networking facilities.Moreover, due to ubiquitous wireless communication technologies, such facilities are also accessible from small and remote communities.As a result, technology and different web-based tools (browse and search, document sharing, data mining, maps, data bases, web services) can be utilized as computing support for people, to help them make more knowledgeable and effective decisions.The healthcare domain has recently embraced new information and communication technologies to improve the quality of healthcare delivery and medical services.This long overdue opportunity is expected to reduce high costs and medical errors in patient diagnosis and treatment; enhance the way healthcare providers interact; increase personal health knowledge of the public; improve the availability and quality of health services; and promote collaborative and patient-centric healthcare services.To meet demands arising from these improved services, new tools, methods, and business models must emerge.Clinical Decision Support Systems (CDSS) are defined as computer applications that assist practitioners and healthcare providers in decision making, through timely access to 1 www.intechopen.
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 | 0,008 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,003 | 0,005 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,005 |
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; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».