Notice bibliographique
Résumé
Smartphone-Based Eye Exam for the ED A new smartphone-based retinal camera makes it easier for physicians to perform eye exams in the ED and rural health care centers.Figure: smartphone, eye exam, ED, rural health care, FOP-NM handheld fundus camera, Remidio, non-mydriatic fundus camera, ETDRS, Medios DR, AI, UniDoc Health, DocBox, predictive analytics, Canadian Triage and Acuity Scale, CTAS, STI test, sexually transmitted infections, Visby Medical, point-of-care, sexual health test, pathogens, chlamydia, gonorrhea, trichomoniasisThe FOP-NM handheld fundus camera from Remidio, Inc., is the world's first smartphone-based non-mydriatic fundus camera, according to a company press release. (May 7, 2024; https://tinyurl.com/2n7dshud.) The camera is held a short distance from the eye and provides high-quality images without dilating the eye or discomforting the patient. The FOP-NM features internal fixation and automatically focuses. It also offers a wider field of view, allowing physicians to capture up to eight fields of the retina instead of the standard ETDRS seven-segment montaged image. The camera works with Medios DR, Remidio's AI algorithm, which can automatically detect signs of diabetic retinopathy in the retina in less than seven seconds without requiring an internet connection or teleophthalmology support. The camera is designed to be handheld, but it can also be mounted on a chinrest or a slit lamp with the help of a support bar. AI Program Predicts Patient Decline UniDoc Health Corp. is betting that AI predictive health technology can improve efficiency and patient care in the ED. UniDoc is expanding its partnership with DocBox, Inc., to integrate advanced monitoring and predictive analytics into ED operations, according to a company press release. (May 14, 2024; https://tinyurl.com/58zrm6s5.) Managing non- and less-urgent patients comprises more than 50 percent of ED visits. (CBC. Jan. 10, 2024; https://tinyurl.com/yrr6b3du.) UniDoc's AI predictive health technology uses advanced algorithms to forecast a potential decline in a patient's health and help EPs intervene before a situation escalates. That improves how EDs manage the flow of nonurgent patients and frees up resources for more severe cases. UniDoc will implement DocBox's monitoring systems, which are equipped to handle Canadian Triage and Acuity Scale (CTAS) levels 4 and 5 patients with real-time data analysis and alert capabilities. These nonurgent ED patients still require medical assessment and care, and this system aims to ensure that deviations in a patient's health are promptly addressed, allowing for immediate and appropriate medical responses. The predictive algorithms should also help EDs reduce unnecessary wait times and ease crowding. STI Test Leads to Shorter ED Visits A new test for sexually transmitted infections (STIs) in women shortens ED visits and improves treatment for patients, according to a press release from Visby Medical, which announced findings from a Johns Hopkins Department of Emergency Medicine study evaluating the new point-of-care test. (May 30, 2024; https://tinyurl.com/5ez8fnff.) The data were presented at the 2024 annual meeting of the Society for Academic Emergency Medicine. The study examined how the Visby Medical Sexual Health Test—a polymerase chain reaction test—managed chlamydia, gonorrhea, and trichomoniasis. These pathogens, if left untreated, can cause permanent damage to a woman's reproductive system, including infertility or possibly a fatal ectopic pregnancy. The study showed the test significantly shortened the time from a patient's arrival at the ED to test results, treatment, and discharge. It also reduced the time from specimen collection to STI result to 47 minutes per patient compared with an average of 25 hours for the standard-of-care lab-processed molecular tests. The Visby Medical test also resulted in significantly higher rates of appropriate treatment and lower rates of overtreatment with antibiotics for Chlamydia trachomatis and Neisseria gonorrhoeae infections compared with standard-of-care tests. MR. MATHERS is the associate editor of Emergency Medicine News.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,003 | 0,003 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,006 | 0,007 |
| Science ouverte | 0,002 | 0,003 |
| Intégrité de la recherche | 0,003 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,574 | 0,628 |
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 source (Gemma direct ou Codex distillé), 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 ».