Results 201 to 210 of about 16,703 (255)

Interpretable multi-center machine learning model driven by facial image features for non-invasive early risk assessment of lung cancer. [PDF]

Front Physiol
Shi Y, Chun Y, Zhang S, Xu X, Chen W, Jiao L, Wang L, Tu L, Xu J.   +8 more
europepmc   +1 more source

Machine learning classification of cycloplegic refractive status in children and adolescents using non-cycloplegic data across ten provincial-level administrative divisions. [PDF]

BMC Med Inform Decis Mak
Liu K, Luo H, Chen Y, E B, Kuang H, Zhang C, Guo X.   +6 more
europepmc   +1 more source

LiRPE 1.0: a modified linformer with relational positional encoding for network intrusion detection. [PDF]

Sci Rep
Biswal U, Mishra S, Mahapatra S.
europepmc   +1 more source

An NLP-Driven Framework for Automated Radiology-Pathology Concordance Assessment in Breast Biopsy. [PDF]

Diagnostics (Basel)
Esmerer E, Nazlı MA, Uzun-Per M, Değidiben MG, Söyleyici M, Tahir E, Bal M.   +6 more
europepmc   +1 more source

Energy Flow Forecasting using LightGBM

Zamanian, Zahra, Vlaminck, Noémie, Sainvitu, Caroline, Vallée, François, Dewasme, Laurent, Vande Wouwer, Alain   +5 more
openaire   +1 more source

Network traffic prediction based on PSO-LightGBM-TM

Computer Networks
Network traffic prediction is critical in wireless network management by allowing a good estimate of the traffic trend, which is also an important approach for detecting traffic anomalies in order to enhance network security. Deep-learning-based method has been widely adopted to predict network traffic matrix (TM) though with the main drawbacks in high
Feng Li 0008, Wei Nie, Kwok-Yan Lam, Li Wang 0041   +3 more
openaire   +3 more sources

Some of the next articles are maybe not open access.

Related searches:

Corporate finance risk prediction based on LightGBM

Information Sciences, 2022
Da Zhao
exaly   +2 more sources

Application of Improved LightGBM Model in Blood Glucose Prediction

Applied Sciences (Switzerland), 2020
In recent years, with increasing social pressure and irregular schedules, many people have developed unhealthy eating habits, which has resulted in an increasing number of patients with diabetes, a disease that cannot be cured under the current medical ...
Tao Wang
exaly   +2 more sources