Analyzing Random Forest’s Predictive Capability for Type 1 Diabetes Progression by Niels F. Cleymans, Mark Van De Casteele, Julie Vandewalle, Aster K. Desouter, Frans K. Gorus, Kurt Barbe

“…This explorative study aims to uncover the potential of random forest machine learning algorithms as survival models within the biomedical context of T1D. …”
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Amyloid Cardiomyopathy: Review of A Fatal Case Report by O. V. Soldatova, I. Ya. Goryanskaya

“…Even with early diagnosis of ATTR-amyloidosis, the life expectancy from the moment the first symptoms appear is 10-12 years, as the disease progresses irreversibly, leading to disability due to severe heart damage and polyneuropathy. …”
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Deep Learning-Based Coding Strategy for Improved Cochlear Implant Speech Perception in Noisy Environments by Billel Essaid, Hamza Kheddar, Noureddine Batel, Muhammad E. H. Chowdhury

“…Automatic speech recognition (ASR) and speech enhancement are essential tools in modern life, aiding not only in machine interaction but also in supporting individuals with hearing impairments. …”
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Artificial Intelligence (AI) in Neurofeedback Therapy Using Electroencephalography (EEG), Heart Rate Variability (HRV), and Galvanic Skin Response (GSR): A Review by Teddy Marcus Zakaria, Armein Zainal R. Langi, Muhamad Sophian Nazaruddin, Isa Anshori

“…Attention problems, such as attention deficit hyperactivity disorder (ADHD), have a significant impact on quality of life and academic achievement. Using Electroencephalogram (EEG), Heart Rate Variability (HRV), and Galvanic Skin Response (GSR), this literature review analyzes the use of Artificial Intelligence (AI) in Neurofeedback Therapy (NFT). …”
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Digital augmentation of aftercare for patients with anorexia nervosa: the TRIANGLE RCT and economic evaluation by Janet Treasure, Katie Rowlands, Valentina Cardi, Suman Ambwani, David McDaid, Jodie Lord, Danielle Clark Bryan, Pamela Macdonald, Eva Bonin, Ulrike Schmidt, Jon Arcelus, Amy Harrison, Sabine Landau

“…Eating disorder-related disability-adjusted life-years are high both for patients and their carers. …”
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Cross-cohort analysis identifies shared gut microbial signatures and validates microbial risk scores for colorectal cancer by Yuhan Zhang, Jiahui Luo, Kuangyu Chen, Na Li, Chenyu Luo, Shuang Di, Junjie Qin, Feng Zhang, Hongda Chen, Min Dai

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Non-stereotypy (to species) in mysticete downsweeps by Paul Nguyen Hong Duc, Christine Erbe, Shyam Madhusudhana, Daniel Wilkes, Lachlan Gill, Cristina Tollefsen, Narissa de Bruin, Aiyana Erbeking, Curt Jenner, Micheline Jenner, Angela Recalde-Salas, Chandra P. Salgado Kent, Chandra P. Salgado Kent, Kautilya Srivastava, Kautilya Srivastava, Chong Wei, Robert McCauley

“…The Australian EEZ provides habitat for ten species of mysticete whales seasonally supporting critical life functions ranging from feeding to breeding. …”
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Critical review of patient outcome study in head and neck cancer radiotherapy by Jingyuan Chen, Yunze Yang, Chenbin Liu, Hongying Feng, Jason M. Holmes, Lian Zhang, Steven J. Frank, Charles B. Simone, II, Daniel J. Ma, Samir H. Patel, Wei Liu

“…Three transformative methodological advances are reviewed: radiomics, AI-based algorithms, and causal inference frameworks. The integration of linear energy transfer in patient outcomes study, which has uncovered critical mechanisms behind unexpected toxicity, was also introduced for proton therapy. …”
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A Comprehensive Review on Lithium-Ion Battery Lifetime Prediction and Aging Mechanism Analysis by Seyed Saeed Madani, Yasmin Shabeer, François Allard, Michael Fowler, Carlos Ziebert, Zuolu Wang, Satyam Panchal, Hicham Chaoui, Saad Mekhilef, Shi Xue Dou, Khay See, Kaveh Khalilpour

“…Synthesizing a wide array of studies on battery aging, the review identifies gaps in current methodologies and highlights innovative approaches for accurate remaining useful life (RUL) estimation. It introduces emerging strategies that leverage advanced algorithms to improve predictive model precision, ultimately driving enhancements in battery performance and supporting their integration into various systems, from electric vehicles to renewable energy infrastructures.…”
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DISPEL: A Python Framework for Developing Measures From Digital Health Technologies by A. Scotland, G. Cosne, A. Juraver, A. Karatsidis, J. Penalver-Andres, E. Bartholome, C. M. Kanzler, C. Mazza, D. Roggen, C. Hinchliffe, S. Del Din, S. Belachew

“…While the framework has already been refined based on clinical trials’ data, ad-hoc validation of the provided algorithms in their specific context of use is recommended to the users.…”
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Non-invasive detection of Parkinson’s disease based on speech analysis and interpretable machine learning by Huanqing Xu, Wei Xie, Mingzhen Pang, Ya Li, Luhua Jin, Fangliang Huang, Xian Shao

“…Several machine learning algorithms, including K-Nearest Neighbors (KNN), Support Vector Machine (SVM), Decision Trees, Random Forests, and Neural Networks, were implemented and evaluated. …”
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Trade-Offs Between Simplifying Inertial Measurement Unit–Based Movement Recordings and the Attainability of Different Levels of Analyses: Systematic Assessment of Method Variations... by Manu Airaksinen, Okko Räsänen, Sampsa Vanhatalo

“…The IMU data can be used for an algorithmic detection of different postures and movements, which may support more detailed assessments of complex behaviors, such as daily activities. …”
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Explainable machine learning model and nomogram for predicting the efficacy of Traditional Chinese Medicine in treating Long COVID: a retrospective study by Jisheng Zhang, Yang Chen, Aijun Zhang, Yi Yang, Liqian Ma, Hangqi Meng, Jintao Wu, Kean Zhu, Jiangsong Zhang, Ke Lin, Xianming Lin

“…IntroductionLong COVID significantly affects patients' quality of life, yet no standardized treatment has been established. …”
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A Clinically Interpretable Approach for Early Detection of Autism Using Machine Learning With Explainable AI by Oishi Jyoti, Hafsa Binte Kibria, Zareen Tasnim Pear, Md Nahiduzzaman, Md. Faysal Ahamed, Khandaker Reajul Islam, Jaya Kumar, Muhammad E. H. Chowdhury

“…The global concern associated with ASD diagnosis is increasing at a rapid rate due to its significant impact on quality of life. Early identification of ASD can significantly support timely intervention and treatment planning. …”
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Enhancing forest biodiversity indicators in inventories through harmonized protocols by Moreno-Fernández D, Breidenbach J, Cañellas I, Chirici G, D’Amico G, Ferretti M, Giannetti F, Puliti S, Schnell S, Shackleton R, Skudnik M, Alberdi I

“…Once the bird and mammal data have been collected, advanced algorithms could facilitate and enhance the efficiency of the analyses. …”
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Quality improvement tools to manage deceased organ donation processes: a scoping review by Sonny Dhanani, Ken Lotherington, Lindsay Wilson, Vanessa Silva e Silva, Laura Hornby, Andrea Rochon, Marian Luctkar-Flude, Amina Silva, Samantha Arora, Luciana P. Giorno, Elayne Jackson, Marzieh Latifi, Stefany Petry

“…The tools identified included checklists, algorithms, flow charts, charts, pathways, decision tree maps and mobile apps. …”
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Digital transformation of modern corporation management tools: the current state and development paths by V. A. Laptev, S. Yu. Chucha, D. R. Feyzrakhmanova

“…Digital technologies have been integrated into all aspects of public life, including politics, law, finance, business, education, science, and society. …”
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Trust, Trustworthiness, and the Future of Medical AI: Outcomes of an Interdisciplinary Expert Workshop by Melanie Goisauf, Mónica Cano Abadía, Kaya Akyüz, Maciej Bobowicz, Alena Buyx, Ilaria Colussi, Marie-Christine Fritzsche, Karim Lekadir, Pekka Marttinen, Michaela Th Mayrhofer, Janos Meszaros

“…Stakeholder engagement throughout the AI life cycle emerged as crucial, supporting a human- and multicentered framework for trustworthy AI implementation. …”
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Adverse drug reaction assessment of pembrolizumab in cervical cancer treatment: a real-world pharmacovigilance study using the FAERS database by Huiping Zhang, Zhuo Zhou, Juan Wang, Shan Wang, Jie Ren, Ming Zhang, Mingyi Yang

“…Clinical outcomes were categorized as other (52.80%), hospitalization (27.00%), death (10.25%), unknown (6.06%), life-threatening (2.77%), and disability (1.12%). …”
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Acute Respiratory Infections Identification With Cough Sounds and Overlapping Patch Modulated Vision Transformers by P. V. V. Kishore, D. Anil Kumar, Pasupuleti Sasikiran, Kaja Krishna Mohan, P. Praveen Kumar, Mogadala Vinod Kumar

“…Rapid detection of Acute Respiratory Infections (ARI) is crucial to reduce breathing difficulties and severe life-threatening conditions. Automatic cough identification is being conducted using speech frequency analysis and machine learning models. …”
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