Dynamic Task Planning for Multi-Arm Harvesting Robots Under Multiple Constraints Using Deep Reinforcement Learning by Feng Xie, Zhengwei Guo, Tao Li, Qingchun Feng, Chunjiang Zhao

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FundusNet: A Deep-Learning Approach for Fast Diagnosis of Neurodegenerative and Eye Diseases Using Fundus Images by Wenxing Hu, Kejie Li, Jake Gagnon, Ye Wang, Talia Raney, Jeron Chen, Yirui Chen, Yoko Okunuki, Will Chen, Baohong Zhang

“…In this study, we present FundusNet, a deep-learning model trained on fundus images, for rapid and cost-effective diagnosis of neurodegenerative diseases. …”
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Prediction of Systemic Risk Contagion Based on a Dynamic Complex Network Model Using Machine Learning Algorithm by Jiannan Yu, Jinlou Zhao

“…We also use machine learning techniques to identify the synthetic features of the network. …”
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Fluorescence Lifetime Endoscopy with a Nanosecond Time-Gated CAPS Camera with IRF-Free Deep Learning Method by Pooria Iranian, Thomas Lapauw, Thomas Van den Dries, Sevada Sahakian, Joris Wuts, Valéry Ann Jacobs, Jef Vandemeulebroucke, Maarten Kuijk, Hans Ingelberts

“…In this work, the capabilities of an endoscopic lifetime imaging system are demonstrated using a rigid endoscope involving various phantoms and an IRF-free deep learning-based method with only 6-time points. The results show that this application’s fluorescence lifetime image has better lifetime uniformity and precision with 6-time points than the conventional methods.…”
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Residents as learning facilitators inside and outside of interprofessional education: a faculty development program in postgraduate pediatric training by Philipp A. Müller, Christine Straub, Christine Straub, Andrea Heinzmann, Thorsten Langer, Sebastian F. N. Bode, Jan Griewatz, Christian Kimmig, Sebastian Friedrich

“…IntroductionChanging learning environments in health professions are an important challenge of interprofessional education (IPE). …”
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Experiences of Science Teachers during the Pandemic-Based Distance Learning Process and Their Recommendations about the Post-Pandemic Process by Serpil Deli, Ozlem Koray, Emine Kahraman

“…The study findings revealed that science teachers experienced problems in learning-teaching processes, assessment-evaluation, technical and structural situations due to the sudden transition to distance learning in the first period of the pandemic. …”
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Developing a Machine Learning–Based Automated Patient Engagement Estimator for Telehealth: Algorithm Development and Validation Study by Pooja Guhan, Naman Awasthi, Kathryn McDonald, Kristin Bussell, Gloria Reeves, Dinesh Manocha, Aniket Bera

“…ObjectiveThis study aimed to examine the ability of machine learning models to estimate patient engagement levels during a tele–mental health session and understand whether the machine learning approach could support therapeutic engagement between the client and psychotherapist. …”
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Utilizing bioinformatics and machine learning to identify CXCR4 gene-related therapeutic targets in diabetic foot ulcers by Hengyan Zhang, Ye Zhou, Heguo Yan, Changxing Huang, Licong Yang, Yangwen Liu

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Uncovering the complex relationships among distributed leadership, departmental teacher leadership, and professional learning community in Chinese schools by Xin Zheng, Chenxi Jiang, Chenlu Liu

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A Review of Key Factors Influencing Mind Wandering in Online Learning and the Role of Visual Design and Technological Interventions by Hao Xu, Masitah Ghazali, Nur Zuraifah Syazrah Othman

Subjects: “…Online learning…”
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Comparison of time-to-event machine learning models in predicting biliary complication and mortality rate in liver transplant patients by Aref Andishgar, Sina Bazmi, Kamran B. Lankarani, Seyed Alireza Taghavi, Mohammad Hadi Imanieh, Gholamreza Sivandzadeh, Samira Saeian, Nazanin Dadashpour, Alireza Shamsaeefar, Mahdi Ravankhah, Hamed Nikoupour Deylami, Reza Tabrizi, Mohammad Hossein Imanieh

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A machine learning driven computationally efficient horse shoe shaped antenna design for internet of medical things. by Umhara Rasool Khan, Javaid A Sheikh, Aqib Junaid, Shazia Ashraf, Altaf A Balkhi

“…In this article, regression-based Machine learning (ML) techniques are used to facilitate the design of Horse shoe shaped patch antenna to predict the frequency of operation, radiation efficiency and Specific Absorption Rate (SAR) values to accelerate its design process for on-body applications. …”
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A Machine Learning Approach to Optimize, Model, and Predict the Machining Factors in Dry Drilling of Nimonic C263 by S. Lakshmana Kumar, V. Jacintha, A. Mahendran, R. M. Bommi, M. Nagaraj, Umamahesawari Kandasamy

“…In this present paper, the machine learning approach is used to optimize, model, and predict the factors during drilling Nimonic C263 under dry mode. …”
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A Smart Machine Learning Model for the Detection of Brain Hemorrhage Diagnosis Based Internet of Things in Smart Cities by Hang Chen, Sulaiman Khan, Bo Kou, Shah Nazir, Wei Liu, Anwar Hussain

“…To reduce the death rates and propose accurate treatment, this paper presents a smart IoT-based application using machine learning algorithms for the human brain hemorrhage diagnosis. …”
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Groundwater Storage Estimation in the Saskatchewan River Basin Using GRACE/GRACE-FO Gravimetric Data and Machine Learning by Mohamed Hamdi, Anas El Alem, Kalifa Goita

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Personalized prediction of anticancer potential of non-oncology drugs through learning from genome derived molecular pathways by Xiaobao Dong, Huanhuan Liu, Ting Tong, Liuxing Wu, Jianhua Wang, Tianyi You, Yongjian Wei, Xianfu Yi, Hongxi Yang, Jie Hu, Haitao Wang, Xiaoyan Wang, Mulin Jun Li

“…Herein we present CHANCE, a supervised machine learning model designed to predict the anticancer activities of non-oncology drugs for specific patients by simultaneously considering personalized coding and non-coding mutations. …”
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Neural network for step anomaly detection in head motion during fMRI using meta-learning adaptation by N.S. Davydov, V.V. Evdokimova, P.G. Serafimovich, V.I. Protsenko, A.G. Khramov, A.V. Nikonorov

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Recognition of Qualifications Obtained as a Result of Non-Formal and Informal Learning: Foreign Experience and Prospects for Russian Practice by A. I. Satdykov, B. A. Sazonov

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Evaluation of a Smoking Cessation Program for HIV Infected Individuals in an Urban HIV Clinic: Challenges and Lessons Learned by Debra Chew, Michael B. Steinberg, Polly Thomas, Shobha Swaminathan, Sally L. Hodder

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A machine learning model using the snapshot ensemble approach for soil respiration prediction in an experimental Oak Forest by S.N. Ferdous, J.P. Ahire, R. Bergman, L. Xin, E. Blanc-Betes, Z. Zhang, J. Wang

“…To mitigate this requirement for high computational power for the assimilation of high-throughput data to identify patterns and trends in soil respiration and guide in deploying effective strategies to reduce Greenhouse gas (GHG) emission, the application of machine-learning (ML) models can help reduce the requirement of intensive computational capacity and improve the accuracy of predictions. …”
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