Unravelling single-cell DNA replication timing dynamics using machine learning reveals heterogeneity in cancer progression by Joseph M. Josephides, Chun-Long Chen

“…Here, we develop MnM, an efficient machine learning-based tool that allows disentangling scRT profiles from heterogenous samples. …”
Get full text

Machine Learning-Integrated Usability Evaluation and Monitoring of Human Activities for Individuals With Special Needs During Hajj and Umrah by Ghadah Naif Alwakid

Subjects: “…Machine learning…”
Get full text

Beyond high hopes: A scoping review of the 2019-2021 scientific discourse on machine learning in medical imaging. by Vasileios Nittas, Paola Daniore, Constantin Landers, Felix Gille, Julia Amann, Shannon Hubbs, Milo Alan Puhan, Effy Vayena, Alessandro Blasimme

“…Machine learning has become a key driver of the digital health revolution. …”
Get full text

Empowering Security Operation Center With Artificial Intelligence and Machine Learning—A Systematic Literature Review by Mohamad Khayat, Ezedin Barka, Mohamed Adel Serhani, Farag Sallabi, Khaled Shuaib, Heba M. Khater

Subjects: Get full text

A Quantum-Based Machine Learning Approach for Autism Detection Using Common Spatial Patterns of EEG Signals by S. Saranya, R. Menaka

“…Electroencephalography (EEG) has emerged as a non-invasive tool to capture brain activity and facilitate the early detection of ASD using machine learning techniques. However, attaining high accuracy with minimal EEG channels remains a challenge. …”
Get full text

Dynamics of Cropland Non-Agriculturalization in Shaanxi Province of China and Its Attribution Using a Machine Learning Approach by Huiting Yan, Hao Chen, Fei Wang, Linjing Qiu

Subjects: Get full text

An extensive bibliometric analysis of pavement deterioration detection using sensors and machine learning: Trends, innovations, and future directions by Mehmet Rizelioğlu

Subjects: Get full text

Integrated energy trading algorithm for source-grid-load-storage energy system based on distributed machine learning by Zhiwei Cui, Changming Mo, Qideng Luo, Chunli Zhou

“…However, the current static network isomorphism algorithm for distributed machine learning cannot meet the energy exchange needs of the integrated energy system. …”
Get full text

The value of multiparametric MRI radiomics and machine learning in predicting preoperative Ki-67 expression level in breast cancer by Yan Lu, Long Jin, Ning Ding, Mengjuan Li, Shengnan Yin, Yiding Ji

Subjects: Get full text

Fault diagnosis of a CNC hobbing cutter through machine learning using three axis vibration data by Nagesh Tambake, Bhagyesh Deshmukh, Sujit Pardeshi, Sachin Salunkhe, Robert Cep, Emad Abouel Nasr

Subjects: Get full text

Following intravenous thrombolysis, the outcome of diabetes mellitus associated with acute ischemic stroke was predicted via machine learning by Xiaoqing Liu, Miaoran Wang, Rui Wen, Haoyue Zhu, Ying Xiao, Qian He, Yangdi Shi, Zhe Hong, Bing Xu

“…An 80/20 train-test split was implemented for model development and validation, employing various machine learning classifiers, including artificial neural networks (ANN), random forest (RF), XGBoost (XGB), and LASSO regression. …”
Get full text

Nanotechnology and LSTM machine learning algorithms in advanced fuel spray dynamics in CI engines with different bowl geometries by Harish Venu, Manzoore Elahi M. Soudagar, Tiong Sieh Kiong, N. M. Razali, Hua-Rong Wei, Armin Rajabi, V. Dhana Raju, T. M. Yunus Khan, Naif Almakayeel, Erdem Cuce, Huseyin Seker

“…Abstract This study explores the integration of nanotechnology and Long Short-Term Memory (LSTM) machine learning algorithms to enhance the understanding and optimization of fuel spray dynamics in compression ignition (CI) engines with varying bowl geometries. …”
Get full text

Machine learning techniques for IoT security: Current research and future vision with generative AI and large language models by Fatima Alwahedi, Alyazia Aldhaheri, Mohamed Amine Ferrag, Ammar Battah, Norbert Tihanyi

Subjects: Get full text

Interpretable machine learning for stability and electronic structure prediction of Janus III–VI van der Waals heterostructures by Yudong Shi, Yinggan Zhang, Jiansen Wen, Zhou Cui, Jianhui Chen, Xiaochun Huang, Cuilian Wen, Baisheng Sa, Zhimei Sun

Subjects: Get full text

Comparative analysis of the human microbiome from four different regions of China and machine learning-based geographical inference by Yinlei Lei, Min Li, Han Zhang, Yu Deng, Xinyu Dong, Pengyu Chen, Ye Li, Suhua Zhang, Chengtao Li, Shouyu Wang, Ruiyang Tao

Subjects: Get full text

Application of the Machine Learning Methods to Assess the Impact of physico-chemical characteristics of water on Feed Consumption in Fish Farms by Hava Şimşek, Mükerrem Oral, Mesut Yılmaz, Mustafa Çakır, Nedim Özdemir, Okan Oral

“…Machine learning (ML) methods, which are one of the subfields of artificial intelligence (AI) and have gained popularity in applications in recent years, play an important role in solving many challenges in aquaculture. …”
Get full text

Species identification for Indian seafood markets: A machine learning approach with a fish datasetMendeley Data by Priyanka Paygude, Namita Shinde, Amol Dhumane, Geeta S. Navale, Prashant Chavan, Atul Kathole, Vijaykumar Bidve

Subjects: Get full text

Artificial intelligence and machine learning techniques for power quality event classification: a focused review and future insights by Indu Sekhar Samanta, Sarthak Mohanty, Shubhranshu Mohan Parida, Pravat Kumar Rout, Subhasis Panda, Mohit Bajaj, Vojtech Blazek, Lukas Prokop, Stanislav Misak

Subjects: Get full text

Development and application of machine learning models in US consumer price index forecasting: Analysis of a hybrid approach by Yunus Emre Gur

Subjects: Get full text

Dynamic Behavior Analysis of Touchdown Process in Active Magnetic Bearing System Based on a Machine Learning Method by Zhe Sun, Xunshi Yan, Jingjing Zhao, Xiao Kang, Guojun Yang, Zhengang Shi

“…In this model, some specific mechanical parameters are regarded as functions of deformation of auxiliary bearing and velocity of rotor firstly; furthermore, a machine learning method is utilized to model these function relationships. …”
Get full text