Results 101 to 110 of about 32,654 (268)

LightGBM: A Leading Force in Breast Cancer Diagnosis Through Machine Learning and Image Processing

IEEE Access
The early diagnosis of breast cancer (BC), a prominent global cause of mortality, necessitates the development of innovative diagnostic strategies.
Bassam M. Kanber, Ahmad AL Smadi, Naglaa F. Noaman, Bo Liu, Shuiping Gou, M. Alsmadi   +5 more
semanticscholar   +1 more source

Heterogeneous Multilayer Nanopores via Chemically Tuned Dielectric Breakdown for Single‐Molecule Sensing

Small, EarlyView.
A scalable fabrication method based on chemically tuned controlled dielectric breakdown (CT‐CDB) enables heterogeneous multilayer nanopores integrating SiNx with 2D materials such as hBN, MoS2, and graphene. The resulting nanopores exhibit distinct electrokinetic behaviors and low noise, allowing structure‐dependent single‐protein sensing.
Chaoming Gu, Kamruzzaman Joty, Navod Thyashan, Ivan Vlassiouk, Liam Collins, Xingye Zhang, Christopher T. Nelson, Nathan Taton, Sangyoup Lee, Min Jun Kim   +9 more
wiley   +1 more source

AI‐Powered Anomaly Detection for Secure Internet of Things (IoT): Optimising XGBoost and Deep Learning With Bayesian Optimisation

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Intelligent and adaptive defence systems that can quickly thwart changing cyberthreats are becoming more and more necessary in the dynamic and data‐intensive Internet of things (IoT) environment. Using the NSL‐KDD benchmark dataset, this paper presents an improved anomaly detection system that combines an optimised sequential neural network ...
Seong‐O Shim, Lal Hussain, Mohammed A. Alqarni, Faisal S. Alsubaei, Rasha Jamal Atwah   +4 more
wiley   +1 more source

A Machine Learning Method for Maximum Temperature Bias Correction in Complex Terrain

Gaoyuan qixiang
To enhance the prediction accuracy of the 2-meter maximum temperature in complex terrain areas， this study developed a gradient modeling approach based on the LightGBM （Light Gradient Boosting Machine， LGB） algorithm， applied to the Sichuan Basin and its
Qiuxue ZHOU, Liangmin FENG, Chaoping CHEN, Di HU   +3 more
doaj   +1 more source

LightGBM-Based Human Action Recognition Using Sensors

Sensors
In recent years, research on human activity recognition (HAR) on smartphones has received extensive attention due to its portability. However, the discrimination issues between similar activities such as leaning forward and walking forward, as well as going up and down stairs, are hard to deal with.
Yinuo Liu, Ziwei Chen
openaire   +2 more sources

A Unified Machine Learning Model for Relapse Prediction in Clinical Stage I Testicular Cancer

Andrology, EarlyView.
ABSTRACT Background Approximately one‐fourth of patients with clinical stage I testicular cancer relapse. For decades, risk stratification has been based on different tumor characteristics for seminomas and non‐seminomas. Previous studies primarily used Cox proportional‐hazards models and included only a limited number of variables.
Thomas Wagner, Ramtin Zargari Marandi, Jakob Lauritsen, Daniel Dawson Murray, Mikkel Bandak, Birgitte Grønkær Toft, Dan Berney, Gedske Daugaard   +7 more
wiley   +1 more source

Enhancing Fraud Detection in Financial Transactions using LightGBM and Random Forest

Journal of Informatics and Web Engineering
In recent years, the frequency and complexity of financial fraud have been rising and have become an urgent challenge for the global financial system. Traditional rule-based detection methods struggle to cope with new types of fraud, especially in terms ...
Wan-Ping Khor, Kah-Ong Michael Goh, Check-Yee Law, Connie Tee, Yong-Wee Sek, Riasat Khan   +5 more
doaj   +1 more source

Classifying Beta-Secretase 1 Inhibitor Activity for Alzheimer’s Drug Discovery with LightGBM

Journal of Computing Theories and Applications
This study explores the utilization of LightGBM, a gradient-boosting framework, to classify the inhibitory activity of beta-secretase 1 inhibitors, addressing the challenges of Alzheimer's disease drug discovery.
T. R. Noviandy, Khairun Nisa, Ghalieb Mutig Idroes, Irsan Hardi, N. R. Sasmita   +4 more
semanticscholar   +1 more source

Machine Learning for Predicting Colorectal Cancer‐Specific Mortality: The Role of Socioeconomic Inequalities in Public Policy

ANZ Journal of Surgery, EarlyView.
ABSTRACT Background Colorectal cancer remains a leading cause of mortality worldwide. We investigated whether adding socioeconomic information to machine learning models can improve the prediction of colorectal cancer‐specific mortality. Methods Using data from the Fundação Oncocentro de São Paulo (FOSP), we analyzed individuals diagnosed with ...
Felipe Mendes Delpino, Rocco Friebel, Francisco Tustumi, Marina Martins Siqueira, Gabriely Rangel Pereira, Marcelo Passos Teivelis, Lucas Hernandes Correa, Nelson Wolosker   +7 more
wiley   +1 more source

Unveiling financial well-being: Insights from retired people in Third Age group in Poland, Spain and Denmark

Economics and Business Review
The study investigates the financial well-being of older people in Poland, Spain and Denmark, with a particular focus on their ability to make ends meet.
Jajko-Siwek Alicja
doaj   +1 more source