180 related articles for article (PubMed ID: 33045678)
1. Driverless artificial intelligence framework for the identification of malignant pleural effusion.
Li Y; Tian S; Huang Y; Dong W
Transl Oncol; 2021 Jan; 14(1):100896. PubMed ID: 33045678
[TBL] [Abstract][Full Text] [Related]
2. Development and validation of a machine learning model for differential diagnosis of malignant pleural effusion using routine laboratory data.
Wei TT; Zhang JF; Cheng Z; Jiang L; Li JY; Zhou L
Ther Adv Respir Dis; 2023; 17():17534666231208632. PubMed ID: 37941347
[TBL] [Abstract][Full Text] [Related]
3. Diagnosis of malignant pleural effusion with combinations of multiple tumor markers: A comparison study of five machine learning models.
Zhang Y; Wang J; Liang B; Wu H; Chen Y
Int J Biol Markers; 2023 Jun; 38(2):139-146. PubMed ID: 36847282
[TBL] [Abstract][Full Text] [Related]
4. Identifying tuberculous pleural effusion using artificial intelligence machine learning algorithms.
Ren Z; Hu Y; Xu L
Respir Res; 2019 Oct; 20(1):220. PubMed ID: 31619240
[TBL] [Abstract][Full Text] [Related]
5. An Integrated Clinical and Computerized Tomography-Based Radiomic Feature Model to Separate Benign from Malignant Pleural Effusion.
Cai F; Cheng L; Liao X; Xie Y; Wang W; Zhang H; Lu J; Chen R; Chen C; Zhou X; Mo X; Hu G; Huang L
Respiration; 2024 Feb; ():1-11. PubMed ID: 38422997
[TBL] [Abstract][Full Text] [Related]
6. Machine learning applied to near-infrared spectra for clinical pleural effusion classification.
Chen Z; Chen K; Lou Y; Zhu J; Mao W; Song Z
Sci Rep; 2021 May; 11(1):9411. PubMed ID: 33941795
[TBL] [Abstract][Full Text] [Related]
7. Evaluation of different boosting ensemble machine learning models and novel deep learning and boosting framework for head-cut gully erosion susceptibility.
Chen W; Lei X; Chakrabortty R; Chandra Pal S; Sahana M; Janizadeh S
J Environ Manage; 2021 Apr; 284():112015. PubMed ID: 33515838
[TBL] [Abstract][Full Text] [Related]
8. Application of Artificial Intelligence for Preoperative Diagnostic and Prognostic Prediction in Epithelial Ovarian Cancer Based on Blood Biomarkers.
Kawakami E; Tabata J; Yanaihara N; Ishikawa T; Koseki K; Iida Y; Saito M; Komazaki H; Shapiro JS; Goto C; Akiyama Y; Saito R; Saito M; Takano H; Yamada K; Okamoto A
Clin Cancer Res; 2019 May; 25(10):3006-3015. PubMed ID: 30979733
[TBL] [Abstract][Full Text] [Related]
9. Prediction of Masked Hypertension and Masked Uncontrolled Hypertension Using Machine Learning.
Hung MH; Shih LC; Wang YC; Leu HB; Huang PH; Wu TC; Lin SJ; Pan WH; Chen JW; Huang CC
Front Cardiovasc Med; 2021; 8():778306. PubMed ID: 34869691
[No Abstract] [Full Text] [Related]
10. Artificial Intelligence Predictive Analytics in the Management of Outpatient MRI Appointment No-Shows.
Chong LR; Tsai KT; Lee LL; Foo SG; Chang PC
AJR Am J Roentgenol; 2020 Nov; 215(5):1155-1162. PubMed ID: 32901567
[No Abstract] [Full Text] [Related]
11. A Comparative Analysis of Novel Deep Learning and Ensemble Learning Models to Predict the Allergenicity of Food Proteins.
Wang L; Niu D; Zhao X; Wang X; Hao M; Che H
Foods; 2021 Apr; 10(4):. PubMed ID: 33918556
[TBL] [Abstract][Full Text] [Related]
12. Artificial Intelligence-Based Traditional Chinese Medicine Assistive Diagnostic System: Validation Study.
Zhang H; Ni W; Li J; Zhang J
JMIR Med Inform; 2020 Jun; 8(6):e17608. PubMed ID: 32538797
[TBL] [Abstract][Full Text] [Related]
13. An Explainable AI Approach for the Rapid Diagnosis of COVID-19 Using Ensemble Learning Algorithms.
Gong H; Wang M; Zhang H; Elahe MF; Jin M
Front Public Health; 2022; 10():874455. PubMed ID: 35801239
[TBL] [Abstract][Full Text] [Related]
14. Validation of Deep Convolutional Neural Network-based algorithm for detection of diabetic retinopathy - Artificial intelligence versus clinician for screening.
Shah P; Mishra DK; Shanmugam MP; Doshi B; Jayaraj H; Ramanjulu R
Indian J Ophthalmol; 2020 Feb; 68(2):398-405. PubMed ID: 31957737
[TBL] [Abstract][Full Text] [Related]
15. LIME-based ensemble machine for predicting performance status of patients with liver cancer.
Nguyen HV; Byeon H
Digit Health; 2023; 9():20552076231211636. PubMed ID: 38025102
[TBL] [Abstract][Full Text] [Related]
16. Predicting Glaucoma Progression to Surgery with Artificial Intelligence Survival Models.
Tao S; Ravindranath R; Wang SY
Ophthalmol Sci; 2023 Dec; 3(4):100336. PubMed ID: 37415920
[TBL] [Abstract][Full Text] [Related]
17. Diagnostic value of soluble B7-H4 and carcinoembryonic antigen in distinguishing malignant from benign pleural effusion.
Jing X; Wei F; Li J; Dai L; Wang X; Jia L; Wang H; An L; Yang Y; Zhang G; Cheng Z
Clin Respir J; 2018 Mar; 12(3):986-990. PubMed ID: 28127951
[TBL] [Abstract][Full Text] [Related]
18. Artificial Intelligence-Based Multimodal Risk Assessment Model for Surgical Site Infection (AMRAMS): Development and Validation Study.
Chen W; Lu Z; You L; Zhou L; Xu J; Chen K
JMIR Med Inform; 2020 Jun; 8(6):e18186. PubMed ID: 32538798
[TBL] [Abstract][Full Text] [Related]
19. [The value of B7-H4 and carcinoembryonic antigen in diagnosing the benign and malignant pleural effusion].
Wei F; Wei Y; Li LF; Li GL; Wang GJ
Zhonghua Zhong Liu Za Zhi; 2017 Jul; 39(7):524-527. PubMed ID: 28728299
[No Abstract] [Full Text] [Related]
20. Machine and deep learning for modelling heat-health relationships.
Boudreault J; Campagna C; Chebana F
Sci Total Environ; 2023 Sep; 892():164660. PubMed ID: 37285991
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
