Towards Reliable ECG Analysis: Addressing Validation Gaps in the Electrocardiographic R-Peak Detection by Syed Talha Abid Ali, Sebin Kim, Young-Joon Kim

“…To validate R-peak detectors, comparing the predicted results with reference annotations is crucial. …”
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The interpretable machine learning model for depression associated with heavy metals via EMR mining method by Site Xu, Mu Sun

“…The optimal model was selected after parameter tuning with a Genetic Algorithm (GA). To enhance the interpretability of the model’s predictions, we applied SHapley Additive exPlanation (SHAP) and Local Interpretable Model-Agnostic Explanations (LIME) algorithms. …”
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Target identification of natural products in cancer with chemical proteomics and artificial intelligence approaches by Guohua Li, Qian Shi, Qibiao Wu, Xinbing Sui

“…Recent advances in artificial intelligence (AI) have further enhanced the field by improving target prediction and streamlining data analysis. AI-driven models, especially machine learning algorithms, have proven effective in processing complex proteomic data and predicting potential NP-protein interactions. …”
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Employing Streaming Machine Learning for Modeling Workload Patterns in Multi-Tiered Data Storage Systems by Edson Ramiro Lucas Filho, George Savva, Lun Yang, Kebo Fu, Jianqiang Shen, Herodotos Herodotou

“…Recently, different Machine-Learning (ML) algorithms have been used to model access patterns from complex workloads. …”
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Human-in-the-loop control strategy for IoT-based smart thermostats with Deep Reinforcement Learning by Payam Fatehi Karjou, Fabian Stupperich, Phillip Stoffel, Drk Müller

“…They use sensors and algorithms to learn user behavior and optimize heating schedules accordingly. …”
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Allocation of Oral Cholera Vaccines in Africa by Elisa M. Maffioli, Yutong Lu

“…Using machine learning algorithms, we assess the relative importance of socio-demographic, governance, and weather variables in predicting cholera outbreaks. …”
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Using Digital Intelligence in Promoting Mechanism for Medical Care Insurance for Rare Diseases: Concepts and Applications by YANG Xinyu, ZHANG Yuzheng, WANG Shengfeng, GUO Wudong

“…By using Chinese keywords of " rare disease" " medical insurance"" artificial intelligence"" prediction model"" machine learning"" big data"" algorithm" and their English equivalents, we searched the databases of PubMed, Embase, Web of Science, CNKI, Wanfang, and VIP, collected relevant literature, and decided the criteria of inclusion and exclusion. …”
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Identification of mitophagy and ferroptosis-related hub genes associated with intracerebral haemorrhage through bioinformatics analysis by Yan Wang, Rufeng Wang, Jianzhong Zhu, Ling Chen

“…Hub genes were selected via STRING, MCODE, and MCC algorithms in Cytoscape. miRNAs targeting hubs were predicted using miRWalk 3.0, forming a miRNA-hub gene network. …”
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Raising awareness of potential biases in medical machine learning: Experience from a Datathon. by Harry Hochheiser, Jesse Klug, Thomas Mathie, Tom J Pollard, Jesse D Raffa, Stephanie L Ballard, Evamarie A Conrad, Smitha Edakalavan, Allan Joseph, Nader Alnomasy, Sarah Nutman, Veronika Hill, Sumit Kapoor, Eddie Pérez Claudio, Olga V Kravchenko, Ruoting Li, Mehdi Nourelahi, Jenny Diaz, W Michael Taylor, Sydney R Rooney, Maeve Woeltje, Leo Anthony Celi, Christopher M Horvat

“…<h4>Objective</h4>To challenge clinicians and informaticians to learn about potential sources of bias in medical machine learning models through investigation of data and predictions from an open-source severity of illness score.…”
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Advancing Hydrogel-Based 3D Cell Culture Systems: Histological Image Analysis and AI-Driven Filament Characterization by Lucio Assis Araujo Neto, Alessandra Maia Freire, Luciano Paulino Silva

“…<b>Background:</b> Machine learning is used to analyze images by training algorithms on data to recognize patterns and identify objects, with applications in various fields, such as medicine, security, and automation. …”
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Structural Magnetic Resonance Imaging Brain Age Investigation in Athletes with Persistent Postconcussion Syndrome by Samuel Guay, Camille Charlebois-Plante, Sophie-Andrée Vinet, Marie-Eve Bourassa, Louis De Beaumont

“…Brain age prediction algorithms using structural magnetic resonance imaging (MRI) estimate the biological age of the brain by comparing it to a normal aging trajectory, allowing for the identification of deviations that may indicate slower or accelerated biological aging. …”
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The Role of Intelligent Transport Systems and Smart Technologies in Urban Traffic Management in Polish Smart Cities by Ewa Puzio, Wojciech Drożdż, Maciej Kolon

“…The study uses a mixed-method approach, including the analysis of crowdsourced mobility data (from GPS, smartphones, and municipal reports), GIS tools for mapping congestion, big data analytics, and machine learning algorithms, to evaluate trends and predict traffic scenarios. …”
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Workload Forecasting Methods in Cloud Environments: An Overview by Samah Aziz, Manar Kashmoola

“…In this study, we discuss some methods of predicting workload in cloud environments. This study presents an overview of workload prediction techniques in cloud systems, with a special emphasis on long short-term memory (LSTM) networks. …”
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Thermoluminescence Properties of Plagioclase Mineral and Modelling of TL Glow Curves with Artificial Neural Networks by Mehmet Yüksel, Emre Ünsal

“…In addition, an artificial neural network (ANN) model was developed to predict TL glow curves using three optimization algorithms, including Levenberg–Marquardt (LM), Bayesian Regularization (BR), and Scaled Conjugate Gradient (SCG). …”
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determination of dust using remote sensing techniques and numerical simulation by Razieh Pilehvaran, Zahra Rastgu, Sara Karami, Behrooz Moradpour

“…At the first step, in order to detect and observe the intensity of the dust concentration over the study area, the MODIS AOD product from the Deep blue and Dark target algorithms has been analyzed using the ENVI software, and the generated images have been displayed in the ArcGIS software. …”
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Information extraction from green channel textual records on expressways using hybrid deep learning by Jiaona Chen, Jing Zhang, Weijun Tao, Yinli Jin, Heng Fan

“…As the results, it is discovered that the text features extracted from pre-training substantially enhance the prediction accuracy of deep learning algorithms. Surprisingly, the RoBERTa model is highly effective in the task for the expressway green channel NER. …”
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Explainable few-shot learning workflow for detecting invasive and exotic tree species by Caroline M. Gevaert, Alexandra Aguiar Pedro, Ou Ku, Hao Cheng, Pranav Chandramouli, Farzaneh Dadrass Javan, Francesco Nattino, Sonja Georgievska

“…While few-shot learning algorithms can address the first problem, they still lack sufficient explanations for the results. …”
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Generalizability of machine learning models for diabetes detection a study with nordic islet transplant and PIMA datasets by Dinesh Chellappan, Harikumar Rajaguru

“…Researchers utilizing a hybrid feature extraction method such as Artificial Bee Colony (ABC) and Particle Swarm Optimization (PSO) followed by metaheuristic feature selection algorithms as Harmonic Search (HS), Dragonfly Algorithm (DFA), Elephant Herding Algorithm (EHA). …”
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Introducing a Novel Method for Determining the Future Price of the Financial Markets: A Case Study of the Hang Seng Index by Afreen Akashi, Md Sanadiule Ullash, Apurba Das

“…Grey Wolf Optimization, Slime Mold Algorithm, and Genetic Algorithm are the optimization techniques included in this study. …”
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Chronic liver disease detection using ranking and projection-based feature optimization with deep learning by Sumaiya Noor, Salman A. AlQahtani, Salman Khan

“…Early detection of liver conditions is crucial, and recent advancements in machine learning (ML) have proven highly effective in predicting diseases like chronic obstructive pulmonary disease (COPD), hypertension, and diabetes. …”
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