Pourquoi ce travail est dans la base
Une base qui oublie comment elle a trouvé un travail ne peut pas être vérifiée. Voici les voies qui ont admis celui-ci.
Notice bibliographique
Résumé
James C. Eisenach, M.D., is F.M. James III Professor of Anesthesiology and Physiology and Pharmacology, Wake Forest University School of Medicine, Winston-Salem, North Carolina.Anesthesiologists are immersed in technology. We rely on technology to help us perform procedures, provide anesthesia, monitor for safety, and predict which of our patients deserves unusual or special treatments. The Foundation for Anesthesia Education and Research (FAER) provides career development to young physicians whose research will transform the specialty, including in technology. Oftentimes this transformation doesn’t occur for decades from the fundamental discovery to the application, and by the time we see the latest oximetry, capnography, ultrasound, simulator, smart notifications, etc., we have long forgotten, if we were even aware, of how FAER-funded investigators helped made this happen. There is another group of pioneers involved nearer to the time of technology breakthroughs – the innovative entrepreneurs in the specialty – and FAER is now reaching out to help them achieve their goals. Ted Stanley, M.D., a pioneer in pharmacology and technology innovation and former FAER Board member, felt that these individuals more than anything need networking opportunities with other inventors and with the groups which fund them. In the past year FAER has sponsored such opportunities at two national meetings of anesthesiologists in Shark Tank®-like sessions where they present their nearly-ready for prime time ideas and discuss hurdles to market implementation. Here are just a few ideas which FAER helped disseminate at these sessions, some of which might soon appear in your practice: A patient monitoring system for hospitalized patients which records respiratory and heart rate, oxygen saturation and perfusion, without any sensors, wires, or the need for patient cooperation (Atapir, Arthur Wallace, M.D., UCSF).A video laryngoscope which includes a warning system to help avoid pharyngeal trauma that can occur when the operator shifts attention from the laryngoscope to the video screen (Clearsight – Barrett Larson, M.D., Stanford).A simple device to alert and prevent a common problem inside and outside the operative room – I.V. bags running dry (FIVA – Orlando Hung, M.D., Dalhousie University).A propofol prodrug without pain on injection and with near instantaneous conversion to propofol following injection (Accellient – Bill Kerns, D.V.M.).An external fetal heart rate monitor which doubles as a fetal pulse oximeter, providing additional information to obstetrician and anesthesiologist about fetal well-being (Raydiant Oximetry, Neil Ray, M.D., and Mark Rosen, M.D., UCSF).A novel intra-venous anesthetic working on GABA receptors but without hemodynamic depression or adrenal suppression (Ed Bertaccini, M.D., Stanford).A new type of ventilator for patients in acute respiratory failure which uses complex mixing of simultaneous frequencies of volume oscillations to more evenly distribute ventilation in diseased lungs (OscillaVent – David Kaczka, M.D., Ph.D., University of Iowa).FAER and the ASA neither endorse nor invest in these ideas. But thanks in large part to Dr. Stanley, FAER is pleased to encourage the development of innovation aimed to support these anesthesiologists who will change the practice of medicine in our specialty. Please stop by and see more new ideas during the FAER Swimming with Sharks session on Saturday, October 13, from 1-3 p.m. at ANESTHESIOLOGY® 2018!
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.
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) | 0,001 | 0,001 |
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 découle