Developing an XGBoost model to predict blast-induced peak particle velocity in an open-pit mine: a case study
Sign Up to like & getrecommendations! Published in 2019 at "Acta Geophysica"
DOI: 10.1007/s11600-019-00268-4
Abstract: Ground vibration is one of the most undesirable effects induced by blasting operations in open-pit mines, and it can cause damage to surrounding structures. Therefore, predicting ground vibration is important to reduce the environmental effects… read more here.
Keywords: pit; open pit; peak particle; xgboost model ... See more keywords
Heavy metal contamination prediction using ensemble model: Case study of Bay sedimentation, Australia.
Sign Up to like & getrecommendations! Published in 2020 at "Journal of hazardous materials"
DOI: 10.1016/j.jhazmat.2020.123492
Abstract: Lead (Pb) is a primary toxic heavy metal (HM) which present throughout the entire ecosystem. Some commonly observed challenges in HM (Pb) prediction using artificial intelligence (AI) models include overfitting, normalization, validation against classical AI… read more here.
Keywords: prediction using; study; model; heavy metal ... See more keywords
Predictive model and risk analysis for diabetic retinopathy using machine learning: a retrospective cohort study in China
Sign Up to like & getrecommendations! Published in 2021 at "BMJ Open"
DOI: 10.1136/bmjopen-2021-050989
Abstract: Objective Aiming to investigate diabetic retinopathy (DR) risk factors and predictive models by machine learning using a large sample dataset. Design Retrospective study based on a large sample and a high dimensional database. Setting A… read more here.
Keywords: risk; machine learning; diabetic retinopathy; model ... See more keywords
An Application of a Three-Stage XGBoost-Based Model to Sales Forecasting of a Cross-Border E-Commerce Enterprise
Sign Up to like & getrecommendations! Published in 2019 at "Mathematical Problems in Engineering"
DOI: 10.1155/2019/8503252
Abstract: Sales forecasting is even more vital for supply chain management in e-commerce with a huge amount of transaction data generated every minute. In order to enhance the logistics service experience of customers and optimize inventory… read more here.
Keywords: border commerce; commerce; sales forecasting; model ... See more keywords
Hybrid Inception v3 XGBoost Model for Acute Lymphoblastic Leukemia Classification
Sign Up to like & getrecommendations! Published in 2021 at "Computational and Mathematical Methods in Medicine"
DOI: 10.1155/2021/2577375
Abstract: Acute lymphoblastic leukemia (ALL) is the most common type of pediatric malignancy which accounts for 25% of all pediatric cancers. It is a life-threatening disease which if left untreated can cause death within a few… read more here.
Keywords: classification; lymphoblastic leukemia; inception; model ... See more keywords
IRESpy: an XGBoost model for prediction of internal ribosome entry sites
Sign Up to like & getrecommendations! Published in 2019 at "BMC Bioinformatics"
DOI: 10.1186/s12859-019-2999-7
Abstract: BackgroundInternal ribosome entry sites (IRES) are segments of mRNA found in untranslated regions that can recruit the ribosome and initiate translation independently of the 5′ cap-dependent translation initiation mechanism. IRES usually function when 5′ cap-dependent… read more here.
Keywords: ribosome entry; entry sites; model; xgboost model ... See more keywords
Predicting Mortality in Intensive Care Unit Patients With Heart Failure Using an Interpretable Machine Learning Model: Retrospective Cohort Study
Sign Up to like & getrecommendations! Published in 2022 at "Journal of Medical Internet Research"
DOI: 10.2196/38082
Abstract: Background Heart failure (HF) is a common disease and a major public health problem. HF mortality prediction is critical for developing individualized prevention and treatment plans. However, due to their lack of interpretability, most HF… read more here.
Keywords: xgboost model; machine learning; mortality; model ... See more keywords
Ultrasound-based radiomics XGBoost model to assess the risk of central cervical lymph node metastasis in patients with papillary thyroid carcinoma: Individual application of SHAP
Sign Up to like & getrecommendations! Published in 2022 at "Frontiers in Oncology"
DOI: 10.3389/fonc.2022.897596
Abstract: Objectives A radiomics-based explainable eXtreme Gradient Boosting (XGBoost) model was developed to predict central cervical lymph node metastasis (CCLNM) in patients with papillary thyroid carcinoma (PTC), including positive and negative effects. Methods A total of… read more here.
Keywords: xgboost model; lymph node; shap; central cervical ... See more keywords