Results 101 to 110 of about 283,145 (183)

Machine learning integrating MRI and clinical features predicts early recurrence of hepatocellular carcinoma after resection. [PDF]

Sci Rep
Feng L, Luo N, Ruan F, Zheng X, Pan X, Li X, Fu L, Long L.   +7 more
europepmc   +1 more source

Time-Resolved Fluorescence and Diffuse Reflectance (TRF-DR) Spectroscopy for Heterogeneous Breast Tissue Classification and Tumor Margin Assessment. [PDF]

J Biophotonics
Lad J, Dao E, Gohla G, Lovrics P, Fang Q, Farrell TJ, Farquharson MJ.   +6 more
europepmc   +1 more source

Gadoxetic Acid-enhanced MRI Radiomics Features of Tumor Margins for Predicting High-Risk Solitary Hepatocellular Carcinoma Aggressiveness and Prognosis. [PDF]

Radiol Imaging Cancer
Yu C, Wang X, Tang S, Li Y, Han S, Zhang Q, Qu J, Xu H, Zhou Y.   +8 more
europepmc   +1 more source

Detection and classification of venous thromboembolism through image test reports analysis using active learning and deep learning. [PDF]

PLoS One
Jeong E, Woo Y, Lee HJ, Kim JY.
europepmc   +1 more source

A Multimodal Ultrasound Radiomics Study for Discriminating Benign and Malignant Breast Lesions Classified as BI-RADS Category 4. [PDF]

Int J Gen Med
Li D, Chang S, Sun C, Lin F, Zhang Z, Chen Q.   +5 more
europepmc   +1 more source

Machine learning-based analysis of economic efficiency disparities and transition drivers between high- and low-carbon industries in China. [PDF]

Carbon Balance Manag
Huang Z, Zhang Q, Zheng Y, Tian E.
europepmc   +1 more source

Machine learning-based model for predicting contralateral central lymph node metastasis in papillary thyroid carcinoma with isthmus proximity. [PDF]

Front Endocrinol (Lausanne)
Wang L, Han Y, Wang C, Sun Z, Zhang H.
europepmc   +1 more source

Reducing label dependence in vibration-based drill-bit condition monitoring with masked feature pretraining. [PDF]

Sci Rep
Chandan MN, Badadhe A, Kebede AW, Majumder H.   +3 more
europepmc   +1 more source

A single MRI scan contains sufficient imaging information for accurate prediction of meningioma growth risk. [PDF]

Neuroimage Clin
Sadeghzadeh N, Correia JA, Shen J, Jun SM, Nielsen PMF, Davis B, Holdsworth SJ, Dragunow M, Faull RLM, Abbasi H.   +9 more
europepmc   +1 more source