Results 51 to 60 of about 22,279 (217)

Further Detail Concerning the Deep Learning Model for Mortality After Total Gastrectomy

Annals of Gastroenterological Surgery, EarlyView.
Kentaro Goto, Haruku Fujita, Ryohei Onishi, Nobuaki Hoshino, Koya Hida   +4 more
wiley   +1 more source

Deep learning–driven chromatic X‐ray imaging based on multicolor halide scintillation film stacks for quantitative densitometry

Information &Functional Materials, EarlyView.
The vapor‐deposited stacking strategy for multicolor halide scintillation films has been developed for chromatic X‐ray imaging, while enabling the systematic curation of a materials genome database. The effectiveness has been demonstrated through segmentation of complex circuit boards and 3D reconstruction of material density distributions.
Hao Wang, Shuai Zhang, Zhiguo Xia
wiley   +1 more source

A Hybrid Approach to Music Recommendations Based on Audio Similarity Using Autoencoder and LightGBM

Journal of Applied Informatics and Computing
Music recommendation systems help users navigate large music collections by suggesting songs aligned with their preferences. However, conventional methods often overlook the depth of audio content, limiting personalization and accuracy.
Winda Ardelia Aristawidya, Majid Rahardi
doaj   +1 more source

Enhanced Botnet Detection and Neutralization through Machine Learning: A Synergistic Analysis of Host Activity, Network Patterns with Explainable Insights [PDF]

Computer Science Journal of Moldova
Botnets continue to be one of the biggest cybersecurity risks since they provide a platform for a number of unlawful operations. The growing sophistication and stealth of contemporary botnet networks, which frequently elude conventional detection tools ...
B. Gomathy, S. V. Riyaayini, K. R. Krishnaprabha, T. Ritanya, A. Kaviyavalli   +4 more
doaj   +1 more source

An Evaluation of Classification and Outlier Detection Algorithms [PDF]

, 2018
This paper evaluates algorithms for classification and outlier detection accuracies in temporal data. We focus on algorithms that train and classify rapidly and can be used for systems that need to incorporate new data regularly.
Austin, Jim, Hodge, Victoria J.
core   +1 more source

Machine learning versus traditional formulas for fetal weight estimation: An international multicenter study evaluating prediction accuracy across birth weight percentiles

International Journal of Gynecology &Obstetrics, EarlyView.
Abstract Objective To assess whether machine learning (ML) offers improved birth weight prediction accuracy, since despite numerous models, the Hadlock formula remains the clinical standard. Methods A multicenter retrospective study analyzed data from 9674 singleton pregnancies with estimated fetal weight (EFW) within 7 days of delivery.
Omer Dor, Eran Ashwal, May Cohen, Ori Rottenstreich, Yariv Yogev, Noam Shomron, Misgav Rottenstreich   +6 more
wiley   +1 more source

Construction and Validation of a Preoperative Surgical Difficulty Prediction and Risk Stratification System for Posterior Spinal Deformity Correction Surgery Based on Machine Learning ‐ Multicenter Cohort Study

iMetaMed, EarlyView.
A web calculator, trained on multicenter data with seven Boruta‐selected preoperative features, predicts prolonged operative time for posterior spinal deformity correction to enable individualized planning and optimized operating‐room resources. ABSTRACT Operative duration reflects surgical complexity and is valuable for perioperative planning.
Chan Xu, Jialiang Zheng, Chengliang Yin, Runmin Li, Xubin Quan, Binghao Chen, Zhaohui Hu, Tongqing Luo, Hao Jiang, Xuewen Hou, Qizhong Xu, Weiheng He, Liang Chen, Anfa Chen, Xin Zhou, Wei Huang, Sen Gao, Jiali Yu, Zhi‐Ri Tang, Yusi Zhang, Kai Wang, Shi‐Nan Wu, Wencai Liu, Xiangdong Xi, Haizhen Ding, Qiang Liu, Haopeng Luan, Wenle Li   +27 more
wiley   +1 more source

An Innovative Approach for Forecasting Hydroelectricity Generation by Benchmarking Tree-Based Machine Learning Models

Applied Sciences
Hydroelectricity, one of the oldest and most potent forms of renewable energy, not only provides low-cost electricity for the grid but also preserves nature through flood control and irrigation support.
Bektaş Aykut Atalay, Kasım Zor
doaj   +1 more source

Decoding temporal miRNA signatures of semen under in vitro exposure for forensic time since deposition estimation using machine learning‐driven modeling

Interdisciplinary Medicine, EarlyView.
This study develops a novel miRNA‐based framework for estimating the time since deposition of semen stains, combining small RNA sequencing with machine learning. Time‐dependent miRNA modules were identified using Mfuzz clustering and WGCNA, followed by a multi‐stage feature selection pipeline that reduced 261 candidate miRNAs to a minimal 7‐miRNA panel.
Meiming Cai, Qiong Lan, Tong Xie, Qinglin Liu, Ming Zhao, Xiaolian Wu, Xin Shi, Ruonan Shen, Yiman Wu, Chen Mao, Bin Cong, Bofeng Zhu   +11 more
wiley   +1 more source

PREDICTION INTERVALS IN MACHINE LEARNING: RESIDUAL BOOTSTRAP AND QUANTILE REGRESSION FOR CASH FLOW ANALYSIS

Barekeng
Time series forecasting often faces challenges in producing reliable predictions due to inherent uncertainty in dynamic systems. While point predictions are commonly used, they may not adequately capture this uncertainty, especially in financial systems ...
Wa Ode Rahmalia Safitri, Farit Mochamad Afendi, Budi Susetyo   +2 more
doaj   +1 more source