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Machine learning

Using multi-label ensemble CNN classifiers to mitigate labelling inconsistencies in patch-level Gleason grading

Muhammad Asim Butt, Muhammad Farhat Kaleem, Muhammad Bilal, Muhammad Shehzad Hanif

Knowledge graph revision in the context of unknown knowledge

Shuangmei Wang, Fengjie Sun

Load forecasting method based on CEEMDAN and TCN-LSTM

Luo Heng, Cheng Hao, Liu Chen Nan

Deep learning-based stress detection for daily life use using single-channel EEG and GSR in a virtual reality interview paradigm

Hun-gyeom Kim, Solwoong Song, Baek Hwan Cho, Dong Pyo Jang

Comparison of model feature importance statistics to identify covariates that contribute most to model accuracy in prediction of insomnia

Alexander A. Huang, Samuel Y. Huang

A deep neural network prediction method for diabetes based on Kendall’s correlation coefficient and attention mechanism

Xiaobo Qi, Yachen Lu, [ ... ], Lifang Ren

Do all sedatives promote biological sleep electroencephalogram patterns? A machine learning framework to identify biological sleep promoting sedatives using electroencephalogram

Sowmya M. Ramaswamy, Merel H. Kuizenga, [ ... ], Michel M. R. F. Struys

DarwinGSE: Towards better image retrieval systems for intellectual property datasets

João António, Jorge Valente, [ ... ], Sandra Jardim

The analysis of the internet of things database query and optimization using deep learning network model

Xiaowen Ma

Significant effect of image contrast enhancement on weld defect detection

Wan Azani Mustafa, Haniza Yazid, [ ... ], Syahrul Junaini

Exploring the diagnostic performance of machine learning in prediction of metabolic phenotypes focusing on thyroid function

Hyeong Jun Ahn, Kyle Ishikawa, Min-Hee Kim

Striking the balance: Configurations of causation and effectuation principles for SME performance

Xiaoyu Yu, Wenjing Zhao, [ ... ], Gang Cao

Prediction of final pathology depending on preoperative myometrial invasion and grade assessment in low-risk endometrial cancer patients: A Korean Gynecologic Oncology Group ancillary study

Dong-hoon Jang, Hyun-Gyu Lee, [ ... ], Yun Hwan Kim

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