Results 71 to 80 of about 7,493 (200)

Dopamine Transporter Imaging‐Based Radiomics for Predicting 4‐Year Motor Progression (Unified Parkinson's Disease Rating Scale Part III) in Parkinson's Disease

iRADIOLOGY, EarlyView.
Magnetic resonance imaging (MRI)‐guided dopamine transporter (DAT) radiomics combined with machine learning showed promising performance for predicting 4‐year motor progression in Parkinson's disease. Ensemble voting fusion markedly improved discrimination compared with individual base models, with stable predictive features mainly derived from ...
Xiaoxuan Fan, Yanghan Chen, Junfeng Lin, Zenwen Han, Jianqiang Ye, Lili Lin, Hong Zhang, Ang Li, Han Jiang   +8 more
wiley   +1 more source

Machine learning ensemble models for predicting the antibacterial efficacy of gold nanoparticles

Materials Research Express
Antimicrobial resistance (AMR) has been increasing rapidly, emerging as a major global health challenge. Gold nanoparticles (AuNPs) are promising antibacterial agents due to their biocompatibility, low toxicity, and ease of functionalization.
Priya Mary, A Mujeeb
doaj   +1 more source

Analysis of SMOTE and Random Search on Machine Learning Algorithms for Stroke Disease Diagnosis

Journal of Applied Informatics and Computing
Stroke is a critical medical condition in which false negative predictions may lead to delayed treatment and increased mortality. Therefore, predictive models in the medical domain should prioritize sensitivity (recall) in addition to overall accuracy ...
Ubaid Khoir Julio Dn, Majid Rahardi
doaj   +1 more source

Intelligent design of artificial biocatalyst for biomedical diseases

Journal of Intelligent Medicine, EarlyView.
This review summarizes recent advances in the intelligent design of artificial biocatalysts for biomedical diseases. By leveraging tailored design strategies, including environment‐responsive engineering and rational/artificial intelligence‐aided optimization, these biocatalysts enable precise modulation of pathological microenvironments and targeted ...
Lijie Zhang, Nan Song, Huanhuan Qiao, Si Sun   +3 more
wiley   +1 more source

Prediction of Lung Cancer Based on Catboost

Highlights in Science, Engineering and Technology
This research aims to provide guidance for achieving precision medicine by accurately predicting the incidence of lung cancer. This paper used random forest screening to identify several variables that make significant influences on the lung cancer, and used Smote oversampling to address the issue of data imbalance. Finally, this paper used Catboost to
Leqi Ma, Yimeng Lu, Yiduo Liu
openaire   +1 more source

FORECASTING OVERALL EQUIPMENT EFFICIENCY IN ELECTRONIC INDUSTRY USING INDUSTRIAL INTERNET OF THINGS AND MACHINE LEARNING METHODS

Измерение, мониторинг, управление, контроль
Background. The article considers modern methods for forecasting the overall efficiency of equipment, allowingto identify productivity reserves and manage production losses at industrial enterprises in the contextof digitalization and the implementation ...
Vitaly R. Aleksandrov, Aleksey A. Shchetkin, Aleksandr S. Bevz, Olga A. Zemskova, Sergey S. Sakhnenko   +4 more
doaj   +1 more source

Molecular descriptor driven QSPR modeling of Papp, TEER and Efflux Ratio from Caco‐2 cells using machine learning for various phytochemicals

Journal of the Science of Food and Agriculture, EarlyView.
Abstract BACKGROUND The present study aimed to develop and validate quantitative structure–property relationship (QSPR) models for predicting permeability related bioavailability indicators including apparent permeability (Papp), trans‐epithelial electrical resistance (TEER) and efflux ratio (ER) based on molecular descriptors (n = 5003) of 83 ...
Jin‐Woo Kim, Rixing Cong, Jin‐Soo Park, Keunwan Park, Kyungsu Kang, Soon‐Mi Shim   +5 more
wiley   +1 more source

Peningkatan Akurasi Prediksi Curah Hujan menggunakan Gradient Boosting dan CatBoost dengan Pendekatan Voting Classifier

Edumatic
Accurate rainfall prediction is essential for agriculture, disaster mitigation, and water resource management, especially in the face of climate change impacts. This research aims to improve the accuracy of rainfall prediction using gradient boosting and
Dina Fudhlatina, Fikri Budiman
doaj   +1 more source

Protective Effects of Riociguat Against Contrast‐Induced Nephropathy: An Experimental and Machine Learning‐Based Study in Rats

The Kaohsiung Journal of Medical Sciences, EarlyView.
ABSTRACT Contrast‐induced nephropathy (CIN) is an important cause of acute kidney injury following exposure to iodinated contrast media, and effective preventive strategies remain limited. This study investigated the renoprotective effects of riociguat, a soluble guanylate cyclase stimulator, in an experimental rat model of CIN and explored machine ...
Mustafa Begenc Tascanov, Kenan Toprak, Sibel Turedi, İsmail Koyuncu, Zulkif Tanrıverdi, Necip Fazıl Dedeoglu, Halil Fedai, Asuman Bicer, İbrahim Halil Altıparmak, Recep Demirbag, Gencay Sarıısık   +10 more
wiley   +1 more source

Earthquake Time Prediction using CatBoost and SVR

International Journal of Innovative Technology and Exploring Engineering, 2019
Seismic tremors everywhere throughout the globe have been a noteworthy reason for decimation and death toll and property. The following context expects to recognize earthquakes at a beginning time utilizing AI. This will help individuals and salvage groups to make their errand simpler.
Sahaya Sakila*, Sanyam Garg, Tanay Yeole, Hrithik Yadav   +3 more
openaire   +1 more source