Realizing the promise of machine learning in precision oncology: expert perspectives on opportunities and challenges by Vasileios Nittas, Kelly E. Ormond, Effy Vayena, Alessandro Blasimme

“…ML will continue to advance cancer research and provide opportunities for patient-centric, personalized, and efficient precision oncology. Yet, the field must move beyond hype and toward concrete efforts to overcome key obstacles, such as ensuring access to molecular data, establishing clinical utility, developing guidelines and regulations, and meaningfully addressing ethical challenges.…”
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Penerapan Teori Meaningful Learning Pada Pengembangan Media Pembelajaran Kit-Build Concept Map Berbasis Knowledge Reconstruction Dengan Sistem Evaluasi dan Feedback Otomatis by Aryo Pinandito, Agi Putra Kharisma, Muhammad Aminul Akbar

“…Abstract This research proposes the application of knowledge reconstruction theory and Ausubel's meaningful learning theory within a learning framework that utilizes the Kit-Build concept map. Under the proposed learning framework, students identify knowledge sources to be organized by linking their prior knowledge and experiences, and integrating the newly organized knowledge into their cognitive understanding using the Kit-Build concept map. …”
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Classification of Red Foxes: Logistic Regression and SVM with VGG-16, VGG-19, and Inception V3 by Brian Sabayu, Imam Yuadi

“…This study conducts an evaluation of three deep learning architectures: Inception V3, VGG-16, and VGG-19, utilizing images of red foxes. The research employs Silhouette Graphs, Multidimensional Scaling (MDS), and t-Distributed Stochastic Neighbor Embedding (t-SNE) to assess clustering and classification efficiency. …”
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Deep Learning Based 3D Visualization Health Condition Monitoring Method for Anchor Digging Machines by YANG Xueqi, GAO Xinqin, ZHENG Haiyang, YANG Jun

“…The model possessed the structure of dual time-length encoding, which meant that the features of long-time sequences were retained and allowed efficient processing of tightly connected short-time series data. …”
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Estimation of long-term gridded cloud radiative kernel and radiative effects based on cloud fraction by X. Liu, T. He, Q. Wang, X. Xiao, Y. Ma, Y. Wang, S. Luo, L. Du, Z. Wu, Z. Wu

“…This paper introduces a novel approach that enhances the accuracy of CRE estimation by constructing computationally efficient, long-term gridded surface cloud fraction radiative kernels (GCF-CRKs) and integrating refined DSSR estimates and a high-precision cloud fraction (CF). …”
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Reinforcement of smart campus grid infrastructure for sustainable energy management in buildings across horizon 2030 by Mahnoor Abbasi, Syed Ali Abbas Kazmi, Muhammad Zubair Iftikhar, Mustafa Anwar, Muhammad Hassan, Thamer A.H. Alghamdi, Mohammed Alenezi

“…Electricity consumption expenses take a significant amount of an educational institution's budget. A major part of utility production in Pakistan depends on non-renewable sources of energy, which have a bad impact on the environment, while their production cost is very high. …”
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Unveiling the shadows: obstacles, consequences, and challenges of information opacity in healthcare systems by Majid Alizadeh, Nazila Azizi, Samireh Mahdavi, Fouad Baghlani

“…A comprehensive search was conducted across major databases such as PubMed, Scopus, and Google Scholar, utilizing relevant keywords. Selection criteria focused on the relevance, quality, and timeliness of the sources, leading to a critical analysis of the extracted data through thematic synthesis. …”
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Designing a new tomato leaf disease classification framework using ran-based adaptive fuzzy c-means with heuristic algorithm model by Kanti Rongali Divya, Rao Gottapu Sasibhushana, Aruna Singam

“…Therefore, the investigated system shows a more efficient TLD prediction rate compared to traditional techniques in the experimental investigation. …”
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A reliable and privacy-preserved federated learning framework for real-time smoking prediction in healthcare by Siddhesh Fuladi, D. Ruby, N. Manikandan, Animesh Verma, M. K. Nallakaruppan, Shitharth Selvarajan, Shitharth Selvarajan, Shitharth Selvarajan, Preeti Meena, V. P. Meena, Ibrahim A. Hameed

“…This research also discusses the benefits of federated learning, including efficient time management, parallel processing, secure model updates, and enhanced data privacy, while addressing limitations such as computational overhead. …”
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Advancements in energy harvesting techniques for sustainable IoT devices by Ahsan Ali, Hamna Shaukat, Hassan Elahi, Shaista Taimur, Muhammad Qasim Manan, Wael A. Altabey, Sallam A. Kouritem, Mohammad Noori

“…The replacement and maintenance process is costly; thus, smart energy management is essential for IoT devices to be energy-efficient. Therefore, energy harvesting is a promising method to supply such low-powered IoT devices by utilizing various energy resources. …”
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A scoping review of artificial intelligence applications in clinical trial risk assessment by Douglas Teodoro, Nona Naderi, Anthony Yazdani, Boya Zhang, Alban Bornet

“…AI techniques, including traditional machine learning, deep learning (e.g., graph neural networks, transformers), and causal machine learning, are used for tasks like adverse drug event prediction, treatment effect estimation, and phase transition prediction. These methods utilize diverse data sources, from molecular structures and clinical trial protocols to patient data and scientific publications. …”
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Improving Integrated Energy Systems With Improved Particle Swarm Optimization: Co-Optimizing Renewables, Electric Vehicles, Gas Systems, and Demand Management by Vahid Khademi, Soodabeh Soleymani, Reza Sharifi, Babak Mozafari

“…This research focuses on optimizing integrated energy systems to enhance both energy efficiency and profitability. Due to the uncertainty in renewable energy output and fluctuating electricity prices, a scenario-based model is utilized. …”
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Simulation of Heat Pump with Heat Storage and PV System—Increase in Self-Consumption in a Polish Household by Jakub Szymiczek, Krzysztof Szczotka, Piotr Michalak

“…The results prove that a buffer tank with the right heat production control system can efficiently increase the auto consumption of self-produced PV electric energy, leading to a reduction in environmental effects and higher economic profitability.…”
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Deep Ultraviolet Dual Comb from a Thin-Disk Laser by Quanming Li, Hanze Bai, Xiaodan Teng, Hongshan Chen, Haijing Mai, Zhitao Zhang, Jinwei Zhang, Hongwen Xuan

“…To extend the dual comb to DUV region, we generated the second and fourth harmonics using LBO and BBO crystals, respectively, with conversion efficiencies exceeding 40% and 10% for both comb beams. …”
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Microwave-Assisted Valorization of Tomato Pomace for Pectin Recovery: Improving Yields and Environmental Footprint by Nikolina Golub, Emerik Galić, Kristina Radić, Nada Smigic, Ilija Djekić, Sandra Pedisić, Dubravka Vitali Čepo

“…Rising industrial demands emphasize the need for exploring other non-traditional sources for obtaining pectin. As efforts to enhance circular economy practices and reduce reliance on primary resources intensify; the focus has shifted towards utilizing various types of agricultural and food industry waste; including tomato pomace waste (TPW). …”
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Cloud-Based Internet-of-Things System for Long-Term Bridge Bearing Monitoring Using Computer Vision by Gunhee Kim, Junsik Shin, Jongbin Won, Jongwoong Park

“…The system features an event-driven power mechanism to minimize energy consumption and utilizes vision-based displacement measurement techniques, providing both portability and efficiency. …”
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GC-MT: A Novel Vessel Trajectory Sequence Prediction Method for Marine Regions by Haixiong Ye, Wei Wang, Xiliang Zhang

“…To ensure the safety of maritime traffic and enhance the efficiency of navigation information, vessel trajectory prediction is crucial for Automatic Identification Systems (AIS). …”
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Enhanced Occupational Safety in Agricultural Machinery Factories: Artificial Intelligence-Driven Helmet Detection Using Transfer Learning and Majority Voting by Simge Özüağ, Ömer Ertuğrul

“…A transfer learning approach was employed, utilizing nine pre-trained neural networks for the extraction of deep features. …”
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Deep Water Subsea Energy Storage, Lessons Learned from the Offshore Oil and Gas Industry by Rasmus Juhlin, Alexander H. Slocum, Mohsen Assadi

“…While previous publications address thermodynamic efficiency limits, there is a notable lack of research on turbine selection, design, and cost estimation based on best practices. …”
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Stochastic carbon footprint tracing for power systems with uncertainty by Jiashuo Hu, Mengge Shi, Xiao‐ping Zhang, Youwei Jia

“…Abstract The increasing penetration of distributed energy resources (DERs) and renewable energy sources (RESs) requires more granular analysis for accurate carbon footprint tracing. …”
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