Results 71 to 80 of about 524,166 (313)

Adversarial attacks against supervised machine learning based network intrusion detection systems

PLoS ONE, 2022
Adversarial machine learning is a recent area of study that explores both adversarial attack strategy and detection systems of adversarial attacks, which are inputs specially crafted to outwit the classification of detection systems or disrupt the ...
Ebtihaj Alshahrani, Daniyal Alghazzawi, Reem Alotaibi, Osama Rabie   +3 more
doaj   +2 more sources

Determining the Need for Computed Tomography Scan Following Blunt Chest Trauma through Machine Learning Approaches

Archives of Academic Emergency Medicine, 2021
Introduction: The use of computed tomography (CT) scan is essential for making diagnoses for trauma patients in emergency medicine. Numerous studies have been conducted on guiding medical examinations in light of advances in machine learning, leading to ...
Mohsen Shahverdy, Hamed Malek
doaj   +1 more source

Learning Multiple Tasks with Boosted Decision Trees [PDF]

, 2012
We address the problem of multi-task learning with no label correspondence among tasks. Learning multiple related tasks simultane- ously, by exploiting their shared knowledge can improve the predictive performance on every task. We develop the multi-task Adaboost en- vironment with Multi-Task Decision Trees as weak classifiers.
Faddoul, Jean Baptiste, Chidlovskii, Boris, Gilleron, Rémi, Torre, Fabien   +3 more
openaire   +4 more sources

Investigating Tree Family Machine Learning Techniques for a Predictive System to Unveil Software Defects

Complexity, 2020
Software defects prediction at the initial period of the software development life cycle remains a critical and important assignment. Defect prediction and correctness leads to the assurance of the quality of software systems and has remained integral to
Rashid Naseem, Bilal Khan, Arshad Ahmad, Ahmad Almogren, Saima Jabeen, Bashir Hayat, Muhammad Arif Shah   +6 more
doaj   +1 more source

Decision Tree-Based Ensemble Model for Predicting National Greenhouse Gas Emissions in Saudi Arabia

Applied Sciences, 2023
Greenhouse gas (GHG) emissions must be precisely estimated in order to predict climate change and achieve environmental sustainability in a country.
Muhammad Muhitur Rahman, Md Shafiullah, Md Shafiul Alam, Mohammad Shahedur Rahman, Mohammed Ahmed Alsanad, Mohammed Monirul Islam, Md Kamrul Islam, Syed Masiur Rahman   +7 more
doaj   +1 more source

Clinical applications of next‐generation sequencing‐based ctDNA analyses in breast cancer: defining treatment targets and dynamic changes during disease progression

Molecular Oncology, EarlyView.
Circulating tumor DNA (ctDNA) offers a possibility for different applications in early and late stage breast cancer management. In early breast cancer tumor informed approaches are increasingly used for detecting molecular residual disease (MRD) and early recurrence. In advanced stage, ctDNA provides a possibility for monitoring disease progression and
Eva Valentina Klocker, Samantha Hasenleithner, Rupert Bartsch, Simon P. Gampenrieder, Daniel Egle, Christian F. Singer, Gabriel Rinnerthaler, Michael Hubalek, Katja Schmitz, Zsuzsanna Bago‐Horvath, Andreas Petzer, Sonja Heibl, Ellen Heitzer, Marija Balic, Michael Gnant   +14 more
wiley   +1 more source

Addressing persistent challenges in digital image analysis of cancer tissue: resources developed from a hackathon

Molecular Oncology, EarlyView.
Large multidimensional digital images of cancer tissue are becoming prolific, but many challenges exist to automatically extract relevant information from them using computational tools. We describe publicly available resources that have been developed jointly by expert and non‐expert computational biologists working together during a virtual hackathon
Sandhya Prabhakaran, Clarence Yapp, Gregory J. Baker, Johanna Beyer, Young Hwan Chang, Allison L. Creason, Robert Krueger, Jeremy Muhlich, Nathan Heath Patterson, Kevin Sidak, Damir Sudar, Adam J. Taylor, Luke Ternes, Jakob Troidl, Xie Yubin, Artem Sokolov, Darren R. Tyson   +16 more
wiley   +1 more source

Quantitative Comparison of Tree Ensemble Learning Methods for Perfume Identification Using a Portable Electronic Nose

Applied Sciences, 2022
Perfume identification (PI) based on an electronic nose (EN) can be used for exposing counterfeit perfumes more time-efficiently and cost-effectively than using gas chromatography and mass spectrometry instruments.
Mengli Cao, Xingwei Ling
doaj   +1 more source

Bayesian Decision Trees via Tractable Priors and Probabilistic Context-Free Grammars [PDF]

arXiv, 2023
Decision Trees are some of the most popular machine learning models today due to their out-of-the-box performance and interpretability. Often, Decision Trees models are constructed greedily in a top-down fashion via heuristic search criteria, such as Gini impurity or entropy. However, trees constructed in this manner are sensitive to minor fluctuations
arxiv  

A review of artificial intelligence in brachytherapy

Journal of Applied Clinical Medical Physics, EarlyView.
Abstract Artificial intelligence (AI) has the potential to revolutionize brachytherapy's clinical workflow. This review comprehensively examines the application of AI, focusing on machine learning and deep learning, in various aspects of brachytherapy.
Jingchu Chen, Richard L. J. Qiu, Tonghe Wang, Shadab Momin, Xiaofeng Yang   +4 more
wiley   +1 more source