318 related articles for article (PubMed ID: 34669518)
1. An increasing number of convolutional neural networks for fracture recognition and classification in orthopaedics : are these externally validated and ready for clinical application?
Oliveira E Carmo L; van den Merkhof A; Olczak J; Gordon M; Jutte PC; Jaarsma RL; IJpma FFA; Doornberg JN; Prijs J;
Bone Jt Open; 2021 Oct; 2(10):879-885. PubMed ID: 34669518
[TBL] [Abstract][Full Text] [Related]
2. Application of artificial intelligence for overall survival risk stratification in oropharyngeal carcinoma: A validation of ProgTOOL.
Alabi RO; Sjöblom A; Carpén T; Elmusrati M; Leivo I; Almangush A; Mäkitie AA
Int J Med Inform; 2023 Jul; 175():105064. PubMed ID: 37094545
[TBL] [Abstract][Full Text] [Related]
3. What Are the Applications and Limitations of Artificial Intelligence for Fracture Detection and Classification in Orthopaedic Trauma Imaging? A Systematic Review.
Langerhuizen DWG; Janssen SJ; Mallee WH; van den Bekerom MPJ; Ring D; Kerkhoffs GMMJ; Jaarsma RL; Doornberg JN
Clin Orthop Relat Res; 2019 Nov; 477(11):2482-2491. PubMed ID: 31283727
[TBL] [Abstract][Full Text] [Related]
4. Development and external validation of automated detection, classification, and localization of ankle fractures: inside the black box of a convolutional neural network (CNN).
Prijs J; Liao Z; To MS; Verjans J; Jutte PC; Stirler V; Olczak J; Gordon M; Guss D; DiGiovanni CW; Jaarsma RL; IJpma FFA; Doornberg JN;
Eur J Trauma Emerg Surg; 2023 Apr; 49(2):1057-1069. PubMed ID: 36374292
[TBL] [Abstract][Full Text] [Related]
5. Artificial intelligence fracture recognition on computed tomography: review of literature and recommendations.
Dankelman LHM; Schilstra S; IJpma FFA; Doornberg JN; Colaris JW; Verhofstad MHJ; Wijffels MME; Prijs J;
Eur J Trauma Emerg Surg; 2023 Apr; 49(2):681-691. PubMed ID: 36284017
[TBL] [Abstract][Full Text] [Related]
6. Artificial intelligence versus clinicians: systematic review of design, reporting standards, and claims of deep learning studies.
Nagendran M; Chen Y; Lovejoy CA; Gordon AC; Komorowski M; Harvey H; Topol EJ; Ioannidis JPA; Collins GS; Maruthappu M
BMJ; 2020 Mar; 368():m689. PubMed ID: 32213531
[TBL] [Abstract][Full Text] [Related]
7. Automated classification of hip fractures using deep convolutional neural networks with orthopedic surgeon-level accuracy: ensemble decision-making with antero-posterior and lateral radiographs.
Yamada Y; Maki S; Kishida S; Nagai H; Arima J; Yamakawa N; Iijima Y; Shiko Y; Kawasaki Y; Kotani T; Shiga Y; Inage K; Orita S; Eguchi Y; Takahashi H; Yamashita T; Minami S; Ohtori S
Acta Orthop; 2020 Dec; 91(6):699-704. PubMed ID: 32783544
[TBL] [Abstract][Full Text] [Related]
8. Feasibility of a generalized convolutional neural network for automated identification of vertebral compression fractures: The Manitoba Bone Mineral Density Registry.
Monchka BA; Kimelman D; Lix LM; Leslie WD
Bone; 2021 Sep; 150():116017. PubMed ID: 34020078
[TBL] [Abstract][Full Text] [Related]
9. Artificial Intelligence for Hip Fracture Detection and Outcome Prediction: A Systematic Review and Meta-analysis.
Lex JR; Di Michele J; Koucheki R; Pincus D; Whyne C; Ravi B
JAMA Netw Open; 2023 Mar; 6(3):e233391. PubMed ID: 36930153
[TBL] [Abstract][Full Text] [Related]
10. A systematic review of the quality of clinical prediction models in in vitro fertilisation.
Ratna MB; Bhattacharya S; Abdulrahim B; McLernon DJ
Hum Reprod; 2020 Jan; 35(1):100-116. PubMed ID: 31960915
[TBL] [Abstract][Full Text] [Related]
11. Development of a manufacturer-independent convolutional neural network for the automated identification of vertebral compression fractures in vertebral fracture assessment images using active learning.
Monchka BA; Schousboe JT; Davidson MJ; Kimelman D; Hans D; Raina P; Leslie WD
Bone; 2022 Aug; 161():116427. PubMed ID: 35489707
[TBL] [Abstract][Full Text] [Related]
12. Identification of Vertebral Fractures by Convolutional Neural Networks to Predict Nonvertebral and Hip Fractures: A Registry-based Cohort Study of Dual X-ray Absorptiometry.
Derkatch S; Kirby C; Kimelman D; Jozani MJ; Davidson JM; Leslie WD
Radiology; 2019 Nov; 293(2):405-411. PubMed ID: 31526255
[TBL] [Abstract][Full Text] [Related]
13. Performance of externally validated machine learning models based on histopathology images for the diagnosis, classification, prognosis, or treatment outcome prediction in female breast cancer: A systematic review.
Gonzalez R; Nejat P; Saha A; Campbell CJV; Norgan AP; Lokker C
J Pathol Inform; 2024 Dec; 15():100348. PubMed ID: 38089005
[TBL] [Abstract][Full Text] [Related]
14. The future of Cochrane Neonatal.
Soll RF; Ovelman C; McGuire W
Early Hum Dev; 2020 Nov; 150():105191. PubMed ID: 33036834
[TBL] [Abstract][Full Text] [Related]
15. Artificial intelligence to diagnose ischemic stroke and identify large vessel occlusions: a systematic review.
Murray NM; Unberath M; Hager GD; Hui FK
J Neurointerv Surg; 2020 Feb; 12(2):156-164. PubMed ID: 31594798
[TBL] [Abstract][Full Text] [Related]
16. Diagnostic Performance of Artificial Intelligence-Based Models for the Detection of Early Esophageal Cancers in Barret's Esophagus: A Meta-Analysis of Patient-Based Studies.
Bhatti KM; Khanzada ZS; Kuzman M; Ali SM; Iftikhar SY; Small P
Cureus; 2021 Jun; 13(6):e15447. PubMed ID: 34258114
[TBL] [Abstract][Full Text] [Related]
17. Association between different scale bars in dermoscopic images and diagnostic performance of a market-approved deep learning convolutional neural network for melanoma recognition.
Winkler JK; Sies K; Fink C; Toberer F; Enk A; Abassi MS; Fuchs T; Haenssle HA
Eur J Cancer; 2021 Mar; 145():146-154. PubMed ID: 33465706
[TBL] [Abstract][Full Text] [Related]
18. Machine Learning Models for Classifying High- and Low-Grade Gliomas: A Systematic Review and Quality of Reporting Analysis.
Bahar RC; Merkaj S; Cassinelli Petersen GI; Tillmanns N; Subramanian H; Brim WR; Zeevi T; Staib L; Kazarian E; Lin M; Bousabarah K; Huttner AJ; Pala A; Payabvash S; Ivanidze J; Cui J; Malhotra A; Aboian MS
Front Oncol; 2022; 12():856231. PubMed ID: 35530302
[TBL] [Abstract][Full Text] [Related]
19. Evaluation of an artificial intelligence system for diagnosing scaphoid fracture on direct radiography.
Ozkaya E; Topal FE; Bulut T; Gursoy M; Ozuysal M; Karakaya Z
Eur J Trauma Emerg Surg; 2022 Feb; 48(1):585-592. PubMed ID: 32862314
[TBL] [Abstract][Full Text] [Related]
20. Man against machine: diagnostic performance of a deep learning convolutional neural network for dermoscopic melanoma recognition in comparison to 58 dermatologists.
Haenssle HA; Fink C; Schneiderbauer R; Toberer F; Buhl T; Blum A; Kalloo A; Hassen ABH; Thomas L; Enk A; Uhlmann L; ; Alt C; Arenbergerova M; Bakos R; Baltzer A; Bertlich I; Blum A; Bokor-Billmann T; Bowling J; Braghiroli N; Braun R; Buder-Bakhaya K; Buhl T; Cabo H; Cabrijan L; Cevic N; Classen A; Deltgen D; Fink C; Georgieva I; Hakim-Meibodi LE; Hanner S; Hartmann F; Hartmann J; Haus G; Hoxha E; Karls R; Koga H; Kreusch J; Lallas A; Majenka P; Marghoob A; Massone C; Mekokishvili L; Mestel D; Meyer V; Neuberger A; Nielsen K; Oliviero M; Pampena R; Paoli J; Pawlik E; Rao B; Rendon A; Russo T; Sadek A; Samhaber K; Schneiderbauer R; Schweizer A; Toberer F; Trennheuser L; Vlahova L; Wald A; Winkler J; Wölbing P; Zalaudek I
Ann Oncol; 2018 Aug; 29(8):1836-1842. PubMed ID: 29846502
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
