170 related articles for article (PubMed ID: 34912282)
1. Automated Machine Learning Model Development for Intracranial Aneurysm Treatment Outcome Prediction: A Feasibility Study.
Ou C; Liu J; Qian Y; Chong W; Liu D; He X; Zhang X; Duan CZ
Front Neurol; 2021; 12():735142. PubMed ID: 34912282
[No Abstract] [Full Text] [Related]
2. Using Automated Machine Learning to Predict the Mortality of Patients With COVID-19: Prediction Model Development Study.
Ikemura K; Bellin E; Yagi Y; Billett H; Saada M; Simone K; Stahl L; Szymanski J; Goldstein DY; Reyes Gil M
J Med Internet Res; 2021 Feb; 23(2):e23458. PubMed ID: 33539308
[TBL] [Abstract][Full Text] [Related]
3. Performance of Automated Machine Learning in Predicting Outcomes of Pneumatic Retinopexy.
Nisanova A; Yavary A; Deaner J; Ali FS; Gogte P; Kaplan R; Chen KC; Nudleman E; Grewal D; Gupta M; Wolfe J; Klufas M; Yiu G; Soltani I; Emami-Naeini P
Ophthalmol Sci; 2024; 4(5):100470. PubMed ID: 38827487
[TBL] [Abstract][Full Text] [Related]
4. Establishment of noninvasive diabetes risk prediction model based on tongue features and machine learning techniques.
Li J; Chen Q; Hu X; Yuan P; Cui L; Tu L; Cui J; Huang J; Jiang T; Ma X; Yao X; Zhou C; Lu H; Xu J
Int J Med Inform; 2021 May; 149():104429. PubMed ID: 33647600
[TBL] [Abstract][Full Text] [Related]
5. Explainable Preoperative Automated Machine Learning Prediction Model for Cardiac Surgery-Associated Acute Kidney Injury.
Thongprayoon C; Pattharanitima P; Kattah AG; Mao MA; Keddis MT; Dillon JJ; Kaewput W; Tangpanithandee S; Krisanapan P; Qureshi F; Cheungpasitporn W
J Clin Med; 2022 Oct; 11(21):. PubMed ID: 36362493
[TBL] [Abstract][Full Text] [Related]
6. Testing the applicability and performance of Auto ML for potential applications in diagnostic neuroradiology.
Musigmann M; Akkurt BH; Krähling H; Nacul NG; Remonda L; Sartoretti T; Henssen D; Brokinkel B; Stummer W; Heindel W; Mannil M
Sci Rep; 2022 Aug; 12(1):13648. PubMed ID: 35953588
[TBL] [Abstract][Full Text] [Related]
7. Clinical performance of automated machine learning: A systematic review.
Thirunavukarasu AJ; Elangovan K; Gutierrez L; Hassan R; Li Y; Tan TF; Cheng H; Teo ZL; Lim G; Ting DSW
Ann Acad Med Singap; 2024 Mar; 53(3):187-207. PubMed ID: 38920245
[TBL] [Abstract][Full Text] [Related]
8. Predicting Postoperative Mortality With Deep Neural Networks and Natural Language Processing: Model Development and Validation.
Chen PF; Chen L; Lin YK; Li GH; Lai F; Lu CW; Yang CY; Chen KC; Lin TY
JMIR Med Inform; 2022 May; 10(5):e38241. PubMed ID: 35536634
[TBL] [Abstract][Full Text] [Related]
9. Use Test of Automated Machine Learning in Cancer Diagnostics.
Musigmann M; Nacul NG; Kasap DN; Heindel W; Mannil M
Diagnostics (Basel); 2023 Jul; 13(14):. PubMed ID: 37510059
[TBL] [Abstract][Full Text] [Related]
10. Evaluation of the performance of traditional machine learning algorithms, convolutional neural network and AutoML Vision in ultrasound breast lesions classification: a comparative study.
Wan KW; Wong CH; Ip HF; Fan D; Yuen PL; Fong HY; Ying M
Quant Imaging Med Surg; 2021 Apr; 11(4):1381-1393. PubMed ID: 33816176
[TBL] [Abstract][Full Text] [Related]
11. Accuracy of automated machine learning in classifying retinal pathologies from ultra-widefield pseudocolour fundus images.
Antaki F; Coussa RG; Kahwati G; Hammamji K; Sebag M; Duval R
Br J Ophthalmol; 2023 Jan; 107(1):90-95. PubMed ID: 34344669
[TBL] [Abstract][Full Text] [Related]
12. A machine learning model for detecting invasive ductal carcinoma with Google Cloud AutoML Vision.
Zeng Y; Zhang J
Comput Biol Med; 2020 Jul; 122():103861. PubMed ID: 32658738
[TBL] [Abstract][Full Text] [Related]
13. Automated machine learning: Review of the state-of-the-art and opportunities for healthcare.
Waring J; Lindvall C; Umeton R
Artif Intell Med; 2020 Apr; 104():101822. PubMed ID: 32499001
[TBL] [Abstract][Full Text] [Related]
14. Automated deep learning design for medical image classification by health-care professionals with no coding experience: a feasibility study.
Faes L; Wagner SK; Fu DJ; Liu X; Korot E; Ledsam JR; Back T; Chopra R; Pontikos N; Kern C; Moraes G; Schmid MK; Sim D; Balaskas K; Bachmann LM; Denniston AK; Keane PA
Lancet Digit Health; 2019 Sep; 1(5):e232-e242. PubMed ID: 33323271
[TBL] [Abstract][Full Text] [Related]
15. AutoML accurately predicts endovascular mechanical thrombectomy in acute large vessel ischemic stroke.
Raj R; Kannath SK; Mathew J; Sylaja PN
Front Neurol; 2023; 14():1259958. PubMed ID: 37840939
[TBL] [Abstract][Full Text] [Related]
16. Prediction of Cardiac Arrest in the Emergency Department Based on Machine Learning and Sequential Characteristics: Model Development and Retrospective Clinical Validation Study.
Hong S; Lee S; Lee J; Cha WC; Kim K
JMIR Med Inform; 2020 Aug; 8(8):e15932. PubMed ID: 32749227
[TBL] [Abstract][Full Text] [Related]
17. Automated Machine Learning versus Expert-Designed Models in Ocular Toxoplasmosis: Detection and Lesion Localization Using Fundus Images.
Milad D; Antaki F; Bernstein A; Touma S; Duval R
Ocul Immunol Inflamm; 2024 Feb; ():1-7. PubMed ID: 38411944
[TBL] [Abstract][Full Text] [Related]
18. Quantitative Serial CT Imaging-Derived Features Improve Prediction of Malignant Cerebral Edema after Ischemic Stroke.
Foroushani HM; Hamzehloo A; Kumar A; Chen Y; Heitsch L; Slowik A; Strbian D; Lee JM; Marcus DS; Dhar R
Neurocrit Care; 2020 Dec; 33(3):785-792. PubMed ID: 32729090
[TBL] [Abstract][Full Text] [Related]
19. Outcome prediction of intracranial aneurysm treatment by flow diverters using machine learning.
Paliwal N; Jaiswal P; Tutino VM; Shallwani H; Davies JM; Siddiqui AH; Rai R; Meng H
Neurosurg Focus; 2018 Nov; 45(5):E7. PubMed ID: 30453461
[TBL] [Abstract][Full Text] [Related]
20. Predicting Grape Sugar Content under Quality Attributes Using Normalized Difference Vegetation Index Data and Automated Machine Learning.
Kasimati A; Espejo-García B; Darra N; Fountas S
Sensors (Basel); 2022 Apr; 22(9):. PubMed ID: 35590939
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
