Results 1 to 10 of about 85,074 (191)

Interpretable machine learning model for shear wave estimation in a carbonate reservoir using LightGBM and SHAP: a case study in the Amu Darya right bank [PDF]

Frontiers in Earth Science, 2023
The shear wave velocity (Vs) is significant for quantitative seismic interpretation. Although numerous studies have proved the effectiveness of the machine learning method in estimating the Vs using well-logging parameters, the real-world application is ...
Tianze Zhang, Hui Chai, Hongjun Wang, Tongcui Guo, Liangjie Zhang, Wenqi Zhang   +5 more
doaj   +2 more sources

Comparative Analysis of Random Forest and XGBoost Models for Cervical Cancer Risk Prediction using SHAP-based Explainable AI

Journal of Applied Informatics and Computing
Cervical cancer remains one of the leading causes of cancer-related deaths among women, particularly in developing countries such as Indonesia. This study aims to develop an accurate and interpretable predictive model for cervical cancer risk using ...
Muhammad Agung Reza Yudha, Majid Rahardi
doaj   +3 more sources

Combining conventional ultrasound and ultrasound elastography to predict HER2 status in patients with breast cancer

Frontiers in Physiology, 2023
Introduction: Identifying the HER2 status of breast cancer patients is important for treatment options. Previous studies have shown that ultrasound features are closely related to the subtype of breast cancer.Methods: In this study, we used features of ...
Xiaoying Zhuo, Xiaoying Zhuo, Ji Lv, Ji Lv, Binjie Chen, Jia Liu, Yujie Luo, Jie Liu, Xiaowei Xie, Jiao Lu, Ningjun Zhao, Ningjun Zhao   +11 more
doaj   +1 more source

A Model-agnostic XAI Approach for Developing Low-cost IoT Intrusion Detection Dataset

Journal of Information Security and Cybercrimes Research, 2023
This study tackles the significant challenge of generating low-cost intrusion detection datasets for Internet of Things (IoT) camera devices, particularly for financially limited organizations.
Enoch Opanin Gyamfi, Zhiguang Qin, Daniel Adu-Gyamfi, Juliana Mantebea Danso, Judith Ayekai Browne, Dominic Kwasi Adom, Francis Effirim Botchey, Nelson Opoku-Mensah   +7 more
doaj   +1 more source

On the Performance of Machine Learning Based Flight Delay Prediction – Investigating the Impact of Short-Term Features

Promet (Zagreb), 2022
People and companies today are connected around the world, which has led to a growing importance of the aviation industry. As flight delays are a big challenge in aviation, machine learning algorithms can be used to forecast those.
Delia Schösser, Jörn Schönberger
doaj   +1 more source

Machine learning models for predicting the risk factor of carotid plaque in cardiovascular disease

Frontiers in Cardiovascular Medicine, 2023
IntroductionCardiovascular disease (CVD) is a group of diseases involving the heart or blood vessels and represents a leading cause of death and disability worldwide.
Chengling Bin, Qin Li, Jing Tang, Chaorong Dai, Ting Jiang, Xiufang Xie, Min Qiu, Lumiao Chen, Shaorong Yang   +8 more
doaj   +1 more source

Predicting gene expression in the human malaria parasite Plasmodium falciparum using histone modification, nucleosome positioning, and 3D localization features. [PDF]

, 2019
Empirical evidence suggests that the malaria parasite Plasmodium falciparum employs a broad range of mechanisms to regulate gene transcription throughout the organism's complex life cycle.
Cook, Kate, Le Roch, Karine G, Lu, Yang Y, Noble, William Stafford, Read, David F   +4 more
core   +2 more sources

A novel approach based on CatBoost and explainable artificial intelligence for diagnosis of COVID-19 cases using patients' symptoms [PDF]

مجله مدل سازی در مهندسی, 2023
The COVID-19 virus, which was discovered in December 2019 in the city of Wuhan, China and quickly spread throughout the world, continues to be an important threat to the health of the world.
Samaneh Emami, Ali SeyyedMomeni, Hamid Nasiri   +2 more
doaj   +1 more source

An interpretable machine learning model for predicting cavity water depth and cavity length based on XGBoost–SHAP

Journal of Hydroinformatics, 2023
In contrast to the traditional black box machine learning model, the white box model can achieve higher prediction accuracy and accurately evaluate and explain the prediction results.
Tiexiang Mo, Shanshan Li, Guodong Li
doaj   +1 more source

Routine characterization and interpretation of complex alkali feldspar intergrowths [PDF]

, 2015
Almost all alkali feldspar crystals contain a rich inventory of exsolution, twin, and domain microtextures that form subsequent to crystal growth and provide a record of the thermal history of the crystal and often of its involvement in replacement ...
Fitz Gerald, John D., Lee, Martin R., Parsons, Ian   +2 more
core   +1 more source