Detection and prediction of real-world severe asthma phenotypes by application of machine learning to electronic health records by Mehmet Furkan Bağcı, MSc, Toan Do, MD, Samantha R. Spierling Bagsic, PhD, Rahul F. Gomez, MD, Judy H. Jun, MD, Anna L. Ritko, MA, MPhil, Sally E. Wenzel, MD, Truong Nguyen, PhD, Yusuf Öztürk, PhD, Brian D. Modena, MD, MSc

“…Results: Three principal components (PCs) emerged, reflecting lung function (PC1), blood inflammatory markers (PC2), and systemic corticosteroid receipt (PC3). …”
Get full text

Machine Learning Aided Resilient Spectrum Surveillance for Cognitive Tactical Wireless Networks: Design and Proof-of-Concept by Eli Garlick, Nourhan Hesham, MD. Zoheb Hassan, Imtiaz Ahmed, Anas Chaaban, MD. Jahangir Hossain

“…To address these issues, this paper proposes an automated interference detection framework, entitled <inline-formula> <tex-math notation="LaTeX">$\textsf {MARSS}$ </tex-math></inline-formula> (Machine Learning Aided Resilient Spectrum Surveillance). <inline-formula> <tex-math notation="LaTeX">$\textsf {MARSS}$ </tex-math></inline-formula> is a fully unsupervised method, which first extracts the low-dimensional representative features from spectrograms by suppressing noise and background information and employing convolutional neural network (CNN) with novel loss function, and subsequently, distinguishes signals with and without interference by applying an isolation forest model on the extracted features. …”
Get full text

In vitro machine learning-based CAR T immunological synapse quality measurements correlate with patient clinical outcomes. by Alireza Naghizadeh, Wei-Chung Tsao, Jong Hyun Cho, Hongye Xu, Mohab Mohamed, Dali Li, Wei Xiong, Dimitri Metaxas, Carlos A Ramos, Dongfang Liu

“…The human immune system consists of a highly intelligent network of billions of independent, self-organized cells that interact with each other. Machine learning (ML) is an artificial intelligence (AI) tool that automatically processes huge amounts of image data. …”
Get full text

Cell-free plasma telomere length correlated with the risk of cardiovascular events using machine learning classifiers by Mengjun Dai, Kangbo Li, Mesud Sacirovic, Claudia Zemmrich, Oliver Ritter, Peter Bramlage, Anja Bondke Persson, Eva Buschmann, Ivo Buschmann, Philipp Hillmeister

“…Data from 518 participants were collected, including clinical and laboratory data. cf-TL was measured in plasma samples and machine learning (ML) classification models were developed to differentiate between CAD, HF and control conditions. …”
Get full text

A deep learning-orchestrated garlic routing architecture for secure telesurgery operations in healthcare 4.0 by Kavit Shah, Nilesh Kumar Jadav, Rajesh Gupta, Sucheta Gupta, Sudeep Tanwar, Joel J.P.C. Rodrigues, Fayez Alqahtani, Amr Tolba

Get full text

A Critical History of Autonomous Language Learning: Exposing the Institutional and Structural Resistance Against Methodological Innovation in Language Education by Santiago Betancor-Falcon

“…Based on this review I further argue that scarcity and the system’s rational functionality are the root problem as well as the foundation of traditional language teaching. …”
Get full text

Prediction of knee joint pain in Tai Chi practitioners: a cross-sectional machine learning approach by Yang Chen, Xiaojie Su, Fei Yao, Yushan Liu, Hua Xing, Yubin Ju, Zhiran Kang, Wuquan Sun, Lijun Yao, Li Gong

“…Six machine learning algorithms were selected and trained by our dataset. …”
Get full text

Enhancing Early Detection of Diabetic Retinopathy Through the Integration of Deep Learning Models and Explainable Artificial Intelligence by Kazi Ahnaf Alavee, Mehedi Hasan, Abu Hasnayen Zillanee, Moin Mostakim, Jia Uddin, Eduardo Silva Alvarado, Isabel de la Torre Diez, Imran Ashraf, Md Abdus Samad

“…Such a disease can exists in human eye that can affect one or both eyes is diabetic retinopathy (DR) which can impair function, vision, and eventually result in permanent blindness. …”
Get full text

Robust Video List Decoding in Error-Prone Transmission Systems Using a Deep Learning Approach by Yujing Zhang, Stephane Coulombe, Francois-Xavier Coudoux, Alexis Guichemerre, Patrick Corlay

“…This paper introduces a novel deep-learning assisted video list decoding method for error-prone video transmission systems. …”
Get full text

Predicting biogas production in real scale anaerobic digester under dynamic conditions with machine learning approach by M. Erdem Isenkul, Sevgi Güneş-Durak, Yasemin Poyraz Kocak, İnci Pir, Mertol Tüfekci, Güler Türkoğlu Demirkol, Selçuk Sevgen, Aslı Seyhan Çığgın, Neşe Tüfekci

“…Among these, Support Vector Regression (SVR) with a Radial Basis Function (RBF) kernel has been used to predict biogas yield based on diverse operating parameters. …”
Get full text

A designed predictive modelling strategy based on data decomposition and machine learning to forecast solar radiation by Mumtaz Ali, Ramendra Prasad, Salman Alamery, Aitazaz Ahsan Farooque

Get full text

Unsupervised machine learning to identify subphenotypes among cardiac intensive care unit patients with heart failure by Jacob C. Jentzer, Yogesh N.V. Reddy, Sabri Soussi, Ruben Crespo‐Diaz, Parag C. Patel, Patrick R. Lawler, Alexandre Mebazaa, Shannon M. Dunlay

“…We aimed to leverage unsupervised machine learning to identify previously unknown HF phenotypes in a large and diverse cohort of patients with HF admitted to the CICU. …”
Get full text

Towards interpretable drug interaction prediction via dual-stage attention and Bayesian calibration with active learning by Rongpei Li, Yufang Zhang, Heqi Sun, Shenggeng Lin, Guihua Jia, Yitian Fang, Chen Zhang, Xiaotong Song, Jianwei Zhao, Lyubin Hu, Yajing Yuan, Xueying Mao, Jiayi Li, Aman Kaushik, Dandan An, Dongqing Wei

“…While recent computational methods focus on improving prediction accuracy, they suffer from high false-positive rates (>45%) and often function as black-box models without biological interpretability. …”
Get full text

Développement des fonctions exécutives chez des ados du secondaire 1 au Tessin : impact des états de concentration et d’hyper-concentration sur le stress induit par le processus d’... by Omar Pagnamenta

Subjects: Get full text

Nonsuicidal self-injury prediction with pain-processing neural circuits using interpretable graph neural network by Sichu Wu, Yuan Xue, Yaming Hang, Ya Xie, Pei Zhang, Minlu Liang, Yuan Zhong, Chun Wang

Subjects: Get full text

PECULIARITIES OF EMPLOYING DISABLED PEOPLE IN ISRAEL by Galina Kozlovskaya, Natalia Borozinets

Subjects: Get full text

Pengaruh Lingkungan Belajar Terhadap Hasil Belajar Mahasiswa Dalam Matakuliah Akuntansi Pemerintah by Husni Mubarak, Karina Krisnanda

“…One of the functions of face-to-face lectures in class is as a transfer of knowledge from lecturer to students. …”
Get full text

Approaches used to prevent and reduce the use of restrictive practices on adults with learning disabilities: a realist review by Joy Duxbury, Alina Haines-Delmont, John Baker, Peter Baker, Gary Bourlet, Elaine Craig, James Ridley, Rachel Whyte, Beth Morrison, Michaela Thomson, Anthony Tsang, Tella Lantta

“…Background There is some evidence to support approaches to reduce restrictive practices in settings for people with a learning disability who may also have a diagnosis of autism or mental health problems. …”
Get full text

Machine learning and DFT database for C-H dissociation on single-atom alloy surfaces in methane decomposition by Huan Wang, Jikai Sun, Youyong Li, Weiqiao Deng

“…This study introduces a comprehensive database of C-H dissociation energy barriers on SAA surfaces, generated through machine learning (ML) and density functional theory (DFT). …”
Get full text

Practical and Accurate Evaluation of Numerical Aperture and Beam Quality Factor in Photonic Crystal Fibers by Mechanical Learning by Mengda Wei, Meisong Liao, Liang Chen, Yinpeng Liu, Wen Hu, Lidong Wang, Dongyu He, Tianxing Wang, Shizi Yu, Weiqing Gao

Get full text