Results 71 to 80 of about 10,309 (278)

Machine Learning‐Assisted Prediction and Analysis of Viscosity and Fusion Characteristics for Coal and Biomass Ash

Materials Genome Engineering Advances, EarlyView.
This study develops a machine learning framework for predicting the flow temperature and viscosity of coal and biomass ash with CatBoost and LightGBM as the optimal models. Feature analysis revealed composition‐property mechanisms, and symbolic regression was further applied to derive empirical formulas for rapid and accurate prediction.
Gangcheng Wang, Muhammad Faizan, Yuanliang Li, Kun Zhou, Kaikai Li, Qi Zhang, Shulin Luo, Guixuan Wu   +7 more
wiley   +1 more source

Evaluation of multiple machine learning models predicting the results of hybrid imaging in primary hyperparathyroidism

Nuclear Medicine Review
BACKGROUND: Primary hyperparathyroidism (PHP) diagnosis is based on abnormalities in biochemical blood tests. Preoperative localization of the affected gland with imaging may increase the effectiveness of the surgical treatment.
Anna Drynda, Jacek Podlewski, Karolina Kucharczyk, Grzegorz Sokołowski, Anna Sowa-Staszczak, Alicja Hubalewska-Dydejczyk, Małgorzata Trofimiuk-Müldner   +6 more
doaj   +1 more source

Non‐Invasive Triage of Bladder Outlet Obstruction and Detrusor Underactivity in Men With Lower Urinary Tract Symptoms: A Narrative Review and Conceptual Framework for Depth‐Aware Multimodal Transcutaneous Testing

Neurourology and Urodynamics, EarlyView.
ABSTRACT Introduction Differentiating bladder outlet obstruction (BOO) from detrusor underactivity (DU) remains a major unmet need in the management of lower urinary tract symptoms in men. Although pressure–flow urodynamics provide a definitive physiological classification, their invasiveness limits their widespread use.
Sehwan Kim, Bryan K. Kim, John T. Stoffel, Aram Kim   +3 more
wiley   +1 more source

Performances of several machine learning algorithms and of logistic regression to predict Fasciola hepática in cattle [PDF]

Pesquisa Agropecuária Brasileira
The objective of this work was to compare the performances of logistic regression and machine learning algorithms to predict infection caused by Fasciola hepatica in cattle. A dataset on 30,151 bovines from Uruguay was used.
Malik Ergin, Özgür Koçkan
doaj   +1 more source

Food plant diversity in a rapidly changing world

PLANTS, PEOPLE, PLANET, EarlyView.
Diversity in food plants is essential to human and planetary health. On farms, in diets, and in many other areas of food systems, this diversity has undergone enormous change globally, including significant decline. We describe major trends in how food plant diversity has been changing, note the responses from conservation communities, highlight gaps ...
Colin K. Khoury, Hannes Dempewolf, Alejandro Argumedo, Stef de Haan, Mauricio Diazgranados, Alex C. McAlvay, Alvaro Toledo, Maarten van Zonneveld, Peter Wenzl   +8 more
wiley   +1 more source

Klasifikasi Karakteristik Faktor Risiko Pneumonia pada Balita dengan Menggunakan Classification and Regression Trees (CART) Studi Kasus RSUD dr. Tengku Mansyur Kota Tanjungbalai

, 2021
Pneumonia merupakan salah satu penyebab kematian tertinggi pada anak di dunia. Badan Kesehatan Dunia (World Health Organization (WHO)) memperkirakan bahwa pneumonia menjadi pemicu 16% kematian pada anak yang berusia dibawah 5 tahun di seluruh dunia ...
Matondang, Elvira Yolanda
core   +1 more source

Comparative Analysis of CART and Random Forest Classifiers for LULC Mapping: A Case Study of Brahmani-Baitarani River Basin, India [PDF]

Nature Environment and Pollution Technology
Land Use and Land Cover (LULC) classification is essential for monitoring environmental changes, managing resources, and planning sustainable development. However, accurate classification remains challenging because of the diversity of landscapes and the
Sonali Kadam, Sangram Patil, Kavita Sawant, Sae Jamdade, Apurva Gadilkar, Chahal Ohri, Namrata Rathi and Jotiram Gujar
doaj   +1 more source

evtree: Evolutionary Learning of Globally Optimal Classification and Regression Trees in R [PDF]

Commonly used classification and regression tree methods like the CART algorithm are recursive partitioning methods that build the model in a forward stepwise search.
Karl-Peter Pfeiffer, Thomas Grubinger, Achim Zeileis   +2 more
core  

Development and deployment of a risk assessment index as a decision‐support tool for managing whitefly‐transmitted viruses affecting squash

Pest Management Science, EarlyView.
A data‐driven framework identified planting date and row cover as dominant drivers of whitefly‐transmitted virus complex (WTVC) risk in squash. Integration into the SquashRx mobile application enables real‐time risk assessment and supports improved decision‐making for integrated pest management.
Clarence B Codod, Anoop A Malik, Alton N Sparks Jr., Andre Luiz Biscaia Ribeiro da Silva, Paul M Severns, Joara Candian, Rajagopalbabu Srinivasan, Ty Torrance, Robert C Kemerait Jr., Bhabesh Dutta   +9 more
wiley   +1 more source

Meta-XGBoost for Hyperspectral Image Classification Using Extended MSER-Guided Morphological Profiles

Remote Sensing, 2020
To investigate the performance of extreme gradient boosting (XGBoost) in remote sensing image classification tasks, XGBoost was first introduced and comparatively investigated for the spectral-spatial classification of hyperspectral imagery using the ...
Alim Samat, Erzhu Li, Wei Wang, Sicong Liu, Cong Lin, Jilili Abuduwaili   +5 more
doaj   +1 more source