Results 111 to 120 of about 60,977 (298)

Bridging Theory and Prediction: A Hybrid SEM and Machine Learning Approach to Optimize Lean Construction for Megaproject Sustainability in China

Corporate Social Responsibility and Environmental Management, EarlyView.
ABSTRACT Construction megaprojects, large‐scale, complex, and capital‐intensive, are particularly prone to inefficiencies, cost overruns, delays, and environmental degradation due to fragmented workflows, stakeholder misalignment, and resource intensity.
Abdelazim Ibrahim, Tarek Zayed, Zoubeir Lafhaj, Ahmed Maged, Ahmed Farouk Kineber, Jingchao Yang   +5 more
wiley   +1 more source

Edited Naive Bayes

, 2008
Naive Bayes is a well-known and studied algorithm both in statistics and machine learning. Bayesian learning algorithms represent each concept with a single probabilistic summary.
E. Lazkano, J. M. Martínez-otzeta, A. Astigarraga, Martnez-Otzeta Sierra Lazkano, B. Sierra, M. Ardaiz   +5 more
core  

Machine Learning–Enhanced Fluorescence Cryptography with NADH‐Responsive Polymer Dots

ENERGY &ENVIRONMENTAL MATERIALS, EarlyView.
This study presents a smart anticounterfeiting system using semiconducting polymer dots (Pdots) that exhibit tunable fluorescence responses to NADH. By integrating these dynamic optical signals with machine learning–based decoding, the work establishes a secure and intelligent encryption platform, showing a novel strategy that links chemical sensing ...
Zhengkun Zhan, Mingyue Gong, Zirui Zeng, Hangyu Liu, Xiaoliang Li, Zhuxin Dong, Xiaoju Men, Haobin Chen   +7 more
wiley   +1 more source

Adaptive secure malware efficient machine learning algorithm for healthcare data

CAAI Transactions on Intelligence Technology, EarlyView., 2023
Abstract Malware software now encrypts the data of Internet of Things (IoT) enabled fog nodes, preventing the victim from accessing it unless they pay a ransom to the attacker. The ransom injunction is constantly accompanied by a deadline. These days, ransomware attacks are too common on IoT healthcare devices.
Mazin Abed Mohammed, Abdullah Lakhan, Dilovan Asaad Zebari, Karrar Hameed Abdulkareem, Jan Nedoma, Radek Martinek, Usman Tariq, Majed Alhaisoni, Prayag Tiwari   +8 more
wiley   +1 more source

Hierarchical mixtures of naive Bayes classifiers [PDF]

, 2002
Naive Bayes classifiers tend to perform very well on a large number of problem domains, although their representation power is quite limited compared to more sophisticated machine learning algorithms.
Intelligente Systemen, Wiering, M.A., Dep Informatica   +2 more
core  

Exercise limitations in amyloid cardiomyopathy assessed by cardiopulmonary exercise testing—A multicentre study

ESC Heart Failure, Volume 12, Issue 2, Page 1326-1335, April 2025.
Abstract Aims Amyloid cardiomyopathy is caused by the deposition of light chain (AL) or transthyretin amyloid (ATTR) fibrils, that leads to a restrictive cardiomyopathy, often resulting in heart failure (HF) with preserved or reduced ejection fraction.
Robin Willixhofer, Mauro Contini, Michele Emdin, Damiano Magrì, Alice Bonomi, Elisabetta Salvioni, Fabrizio Celeste, Alberico Del Torto, Claudio Passino, Christophe D.J. Capelle, Chiara Arzilli, Emiliano Fiori, Nicolò Capra, Christina Kronberger, Nikita Ermolaev, Andreas Kammerlander, Beatrice Musumeci, Giuseppe Vergaro, Vincenzo Castiglione, René Rettl, Giacomo Tini, Andrea Baggiano, Iacopo Fabiani, Susanna Sciomer, Roza Badr Eslam, Piergiuseppe Agostoni   +25 more
wiley   +1 more source

Clustered Naive Bayes [PDF]

, 2006
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2006.Includes bibliographical references (leaves 71-73).Humans effortlessly use experience from related tasks to improve their performance at ...
Roy, Daniel Murphy
core  

Artificial intelligence for adaptive neuromodulation in drug‐resistant epilepsy

Epilepsia, EarlyView.
Abstract Drug‐resistant epilepsy (DRE) affects nearly one third of people with epilepsy and is associated with substantial cognitive, psychiatric, and mortality burdens. For patients who are not candidates for resection or laser interstitial thermal therapy, neuromodulation therapies such as vagus nerve stimulation, deep brain stimulation, and ...
Amir Hossein Daraie, Arianna Damiani, Mahsa Khoshkhou, Luis A. Sanchez, Rachel J. Smith, Shruti H. Agashe, Jorge A. Gonzalez‐Martinez, Jennifer Hopp, Adam S. Charles, Sridevi V. Sarma, Joon‐Yi Kang   +10 more
wiley   +1 more source

AI‐based localization of the epileptogenic zone using intracranial EEG

Epilepsia Open, EarlyView.
Abstract Artificial intelligence (AI) is rapidly transforming our lives. Machine learning (ML) enables computers to learn from data and make decisions without explicit instructions. Deep learning (DL), a subset of ML, uses multiple layers of neural networks to recognize complex patterns in large datasets through end‐to‐end learning.
Atsuro Daida, Yipeng Zhang, Sotaro Kanai, Richard Staba, Vwani Roychowdhury, Hiroki Nariai   +5 more
wiley   +1 more source

Artificial intelligence in preclinical epilepsy research: Current state, potential, and challenges

Epilepsia Open, EarlyView.
Abstract Preclinical translational epilepsy research uses animal models to better understand the mechanisms underlying epilepsy and its comorbidities, as well as to analyze and develop potential treatments that may mitigate this neurological disorder and its associated conditions. Artificial intelligence (AI) has emerged as a transformative tool across
Jesús Servando Medel‐Matus, Cesar Santana‐Gomez, Ruby G. Escalante, Dominique Duncan, Pedro F. Viana, Giulia Sofia Cereda, Naoto Kuroda, Aristea S. Galanopoulou   +7 more
wiley   +1 more source