147 related articles for article (PubMed ID: 38332402)
1. Deep Learning for Chest X-ray Diagnosis: Competition Between Radiologists with or Without Artificial Intelligence Assistance.
Guo L; Zhou C; Xu J; Huang C; Yu Y; Lu G
J Imaging Inform Med; 2024 Jun; 37(3):922-934. PubMed ID: 38332402
[TBL] [Abstract][Full Text] [Related]
2. An Artificial Intelligence-Based Chest X-ray Model on Human Nodule Detection Accuracy From a Multicenter Study.
Homayounieh F; Digumarthy S; Ebrahimian S; Rueckel J; Hoppe BF; Sabel BO; Conjeti S; Ridder K; Sistermanns M; Wang L; Preuhs A; Ghesu F; Mansoor A; Moghbel M; Botwin A; Singh R; Cartmell S; Patti J; Huemmer C; Fieselmann A; Joerger C; Mirshahzadeh N; Muse V; Kalra M
JAMA Netw Open; 2021 Dec; 4(12):e2141096. PubMed ID: 34964851
[TBL] [Abstract][Full Text] [Related]
3. Effect of a comprehensive deep-learning model on the accuracy of chest x-ray interpretation by radiologists: a retrospective, multireader multicase study.
Seah JCY; Tang CHM; Buchlak QD; Holt XG; Wardman JB; Aimoldin A; Esmaili N; Ahmad H; Pham H; Lambert JF; Hachey B; Hogg SJF; Johnston BP; Bennett C; Oakden-Rayner L; Brotchie P; Jones CM
Lancet Digit Health; 2021 Aug; 3(8):e496-e506. PubMed ID: 34219054
[TBL] [Abstract][Full Text] [Related]
4. Deep learning for chest radiograph diagnosis: A retrospective comparison of the CheXNeXt algorithm to practicing radiologists.
Rajpurkar P; Irvin J; Ball RL; Zhu K; Yang B; Mehta H; Duan T; Ding D; Bagul A; Langlotz CP; Patel BN; Yeom KW; Shpanskaya K; Blankenberg FG; Seekins J; Amrhein TJ; Mong DA; Halabi SS; Zucker EJ; Ng AY; Lungren MP
PLoS Med; 2018 Nov; 15(11):e1002686. PubMed ID: 30457988
[TBL] [Abstract][Full Text] [Related]
5. Artificial Intelligence Algorithm Detecting Lung Infection in Supine Chest Radiographs of Critically Ill Patients With a Diagnostic Accuracy Similar to Board-Certified Radiologists.
Rueckel J; Kunz WG; Hoppe BF; Patzig M; Notohamiprodjo M; Meinel FG; Cyran CC; Ingrisch M; Ricke J; Sabel BO
Crit Care Med; 2020 Jul; 48(7):e574-e583. PubMed ID: 32433121
[TBL] [Abstract][Full Text] [Related]
6. DeepCOVID-XR: An Artificial Intelligence Algorithm to Detect COVID-19 on Chest Radiographs Trained and Tested on a Large U.S. Clinical Data Set.
Wehbe RM; Sheng J; Dutta S; Chai S; Dravid A; Barutcu S; Wu Y; Cantrell DR; Xiao N; Allen BD; MacNealy GA; Savas H; Agrawal R; Parekh N; Katsaggelos AK
Radiology; 2021 Apr; 299(1):E167-E176. PubMed ID: 33231531
[TBL] [Abstract][Full Text] [Related]
7. Using AI to Improve Radiologist Performance in Detection of Abnormalities on Chest Radiographs.
Bennani S; Regnard NE; Ventre J; Lassalle L; Nguyen T; Ducarouge A; Dargent L; Guillo E; Gouhier E; Zaimi SH; Canniff E; Malandrin C; Khafagy P; Koulakian H; Revel MP; Chassagnon G
Radiology; 2023 Dec; 309(3):e230860. PubMed ID: 38085079
[TBL] [Abstract][Full Text] [Related]
8. Association of Artificial Intelligence-Aided Chest Radiograph Interpretation With Reader Performance and Efficiency.
Ahn JS; Ebrahimian S; McDermott S; Lee S; Naccarato L; Di Capua JF; Wu MY; Zhang EW; Muse V; Miller B; Sabzalipour F; Bizzo BC; Dreyer KJ; Kaviani P; Digumarthy SR; Kalra MK
JAMA Netw Open; 2022 Aug; 5(8):e2229289. PubMed ID: 36044215
[TBL] [Abstract][Full Text] [Related]
9. Validation of a Deep Learning Algorithm for the Detection of Malignant Pulmonary Nodules in Chest Radiographs.
Yoo H; Kim KH; Singh R; Digumarthy SR; Kalra MK
JAMA Netw Open; 2020 Sep; 3(9):e2017135. PubMed ID: 32970157
[TBL] [Abstract][Full Text] [Related]
10. Comparison of Chest Radiograph Interpretations by Artificial Intelligence Algorithm vs Radiology Residents.
Wu JT; Wong KCL; Gur Y; Ansari N; Karargyris A; Sharma A; Morris M; Saboury B; Ahmad H; Boyko O; Syed A; Jadhav A; Wang H; Pillai A; Kashyap S; Moradi M; Syeda-Mahmood T
JAMA Netw Open; 2020 Oct; 3(10):e2022779. PubMed ID: 33034642
[TBL] [Abstract][Full Text] [Related]
11. External validation of deep learning-based automated detection algorithm for chest radiograph: practical issues in outpatient clinic.
Lee DE; Chae KJ; Jin GY; Park SY; Jeong JS; Ahn SY
Acta Radiol; 2023 Nov; 64(11):2898-2907. PubMed ID: 37750179
[TBL] [Abstract][Full Text] [Related]
12. Development and Validation of a Deep Learning-Based Automated Detection Algorithm for Major Thoracic Diseases on Chest Radiographs.
Hwang EJ; Park S; Jin KN; Kim JI; Choi SY; Lee JH; Goo JM; Aum J; Yim JJ; Cohen JG; Ferretti GR; Park CM;
JAMA Netw Open; 2019 Mar; 2(3):e191095. PubMed ID: 30901052
[TBL] [Abstract][Full Text] [Related]
13. AI-based improvement in lung cancer detection on chest radiographs: results of a multi-reader study in NLST dataset.
Yoo H; Lee SH; Arru CD; Doda Khera R; Singh R; Siebert S; Kim D; Lee Y; Park JH; Eom HJ; Digumarthy SR; Kalra MK
Eur Radiol; 2021 Dec; 31(12):9664-9674. PubMed ID: 34089072
[TBL] [Abstract][Full Text] [Related]
14. Artificial intelligence-supported lung cancer detection by multi-institutional readers with multi-vendor chest radiographs: a retrospective clinical validation study.
Ueda D; Yamamoto A; Shimazaki A; Walston SL; Matsumoto T; Izumi N; Tsukioka T; Komatsu H; Inoue H; Kabata D; Nishiyama N; Miki Y
BMC Cancer; 2021 Oct; 21(1):1120. PubMed ID: 34663260
[TBL] [Abstract][Full Text] [Related]
15. Chest Radiograph Interpretation with Deep Learning Models: Assessment with Radiologist-adjudicated Reference Standards and Population-adjusted Evaluation.
Majkowska A; Mittal S; Steiner DF; Reicher JJ; McKinney SM; Duggan GE; Eswaran K; Cameron Chen PH; Liu Y; Kalidindi SR; Ding A; Corrado GS; Tse D; Shetty S
Radiology; 2020 Feb; 294(2):421-431. PubMed ID: 31793848
[TBL] [Abstract][Full Text] [Related]
16. Use of artificial intelligence in triaging of chest radiographs to reduce radiologists' workload.
Yoon SH; Park S; Jang S; Kim J; Lee KW; Lee W; Lee S; Yun G; Lee KH
Eur Radiol; 2024 Feb; 34(2):1094-1103. PubMed ID: 37615766
[TBL] [Abstract][Full Text] [Related]
17. Commercially Available Chest Radiograph AI Tools for Detecting Airspace Disease, Pneumothorax, and Pleural Effusion.
Lind Plesner L; Müller FC; Brejnebøl MW; Laustrup LC; Rasmussen F; Nielsen OW; Boesen M; Brun Andersen M
Radiology; 2023 Sep; 308(3):e231236. PubMed ID: 37750768
[TBL] [Abstract][Full Text] [Related]
18. Deep Convolutional Neural Network-based Software Improves Radiologist Detection of Malignant Lung Nodules on Chest Radiographs.
Sim Y; Chung MJ; Kotter E; Yune S; Kim M; Do S; Han K; Kim H; Yang S; Lee DJ; Choi BW
Radiology; 2020 Jan; 294(1):199-209. PubMed ID: 31714194
[TBL] [Abstract][Full Text] [Related]
19. A deep residual learning network for predicting lung adenocarcinoma manifesting as ground-glass nodule on CT images.
Gong J; Liu J; Hao W; Nie S; Zheng B; Wang S; Peng W
Eur Radiol; 2020 Apr; 30(4):1847-1855. PubMed ID: 31811427
[TBL] [Abstract][Full Text] [Related]
20. Development and Validation of Deep Learning-based Automatic Detection Algorithm for Malignant Pulmonary Nodules on Chest Radiographs.
Nam JG; Park S; Hwang EJ; Lee JH; Jin KN; Lim KY; Vu TH; Sohn JH; Hwang S; Goo JM; Park CM
Radiology; 2019 Jan; 290(1):218-228. PubMed ID: 30251934
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]