soundscape_IR: A source separation toolbox for exploring acoustic diversity in soundscapes by Yi‐Jen Sun, Shih‐Ching Yen, Tzu‐Hao Lin

“…This toolbox provides algorithms for supervised and unsupervised source separation (SS). …”
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Casualty Analysis of the Drivers in Traffic Accidents in Turkey: A CHAID Decision Tree Model by Zeliha Cagla Kuyumcu, Hakan Aslan, Nilufer Yurtay

“…This study aims to establish a model to predict the driver’s status (survived–injured–dead) as a result of the fatal-injury type of accident. …”
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Computation strategies and clinical applications in neoantigen discovery towards precision cancer immunotherapy by Zhenchang Wang, Yu Gu, Xiao Sun, Hao Huang

“…Driven by advancements in high-throughput sequencing technologies, mass spectrometry, and artificial intelligence, researchers have developed a growing interest in establishing more accurate neoantigen prediction algorithms. Here, we presented a comprehensive review of integrated neoantigen prediction algorithms, encompassing task definition, theoretical developments, benchmark datasets, cutting-edge applications, and future research directions. …”
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Abilities and limitations in counteracting urban heat islands by Michał Musiał, Anna Pomykała, Lech Lichołai

“…While AI models can expedite predictions, their precision may still lag behind traditional numerical weather prediction methods. …”
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Integrative molecular subtyping and diagnostic model construction for Moyamoya disease based on diverse programmed cell death gene patterns by Qikai Tang, Chenfeng Ma, Hu Li, Jiaheng Xie, Weiqi Bian, Qingyu Lu, Zeyu Wan, Wei Wu

“…Diagnostic models were constructed using machine learning algorithms, and key model genes were validated by qRT-PCR in arterial samples from MMD patients. …”
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Integrated bioinformatics identifies ferroptosis biomarkers and therapeutic targets in idiopathic pulmonary arterial hypertension by Yuhao Zhang, Tao Qian, Wei Jiang, Haoyong Yuan, Ting Lu, Ni Yin, Zhongshi Wu, Can Huang

“…GO and KEGG analyses were performed to explore biological functions and potential pathways. LASSO and SVM-RFE algorithms were used to identify optimal gene biomarkers for IPAH. …”
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Immunogenic cell death-related genes as prognostic biomarkers and therapeutic insights in uterine corpus endometrial carcinoma: an integrative bioinformatics analysis by Tianfei Yi, Zhenglun Yang, Peng Shen, Yan Huang

“…The immune landscape was characterized through multiple bioinformatics approaches, and immunotherapy response was predicted using the Tumor Immune Dysfunction and Exclusion (TIDE) algorithm. …”
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Prevention and management of degenerative lumbar spine disorders through artificial intelligence-based decision support systems: a systematic review by Paolo Giaccone, Federico D’Antoni, Fabrizio Russo, Luca Ambrosio, Giuseppe Francesco Papalia, Onorato d’Angelis, Gianluca Vadalà, Albert Comelli, Luca Vollero, Mario Merone, Rocco Papalia, Vincenzo Denaro

“…Several different machine learning and deep learning algorithms were employed, and their predictive ability on clinical, demographic, psychosocial, and imaging data was assessed. …”
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Deep-learning based detection of vessel occlusions on CT-angiography in patients with suspected acute ischemic stroke by Gianluca Brugnara, Michael Baumgartner, Edwin David Scholze, Katerina Deike-Hofmann, Klaus Kades, Jonas Scherer, Stefan Denner, Hagen Meredig, Aditya Rastogi, Mustafa Ahmed Mahmutoglu, Christian Ulfert, Ulf Neuberger, Silvia Schönenberger, Kai Schlamp, Zeynep Bendella, Thomas Pinetz, Carsten Schmeel, Wolfgang Wick, Peter A. Ringleb, Ralf Floca, Markus Möhlenbruch, Alexander Radbruch, Martin Bendszus, Klaus Maier-Hein, Philipp Vollmuth

“…We provide an imaging platform ( https://stroke.ccibonn.ai/ ) for online processing of medical imaging data with the developed ANN, including provisions for data crowdsourcing, which will allow continuous refinements and serve as a blueprint to build robust and generalizable AI algorithms.…”
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Detection of Cyanuric Acid and Melamine in Infant Formula Powders by Mid-FTIR Spectroscopy and Multivariate Analysis by Edwin García-Miguel, Ofelia Gabriela Meza-Márquez, Guillermo Osorio-Revilla, Darío Iker Téllez-Medina, Cristian Jiménez-Martínez, Maribel Cornejo-Mazón, Diana Maylet Hernández-Martínez, Tzayhrí Gallardo-Velazquez

“…Chemometric models were constructed using the algorithms Partial Least Squares (PLS1, PLS2) and Principal Component Regression (PCR) in order to correlate the IR signal with the levels of melamine or cyanuric acid in the infant formula samples. …”
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Combining a Risk Factor Score Designed From Electronic Health Records With a Digital Cytology Image Scoring System to Improve Bladder Cancer Detection: Proof-of-Concept Study by Sandie Cabon, Sarra Brihi, Riadh Fezzani, Morgane Pierre-Jean, Marc Cuggia, Guillaume Bouzillé

“…MethodsThe first step relied on designing a predictive model based on clinical data (ie, risk factors identified in the literature) extracted from the clinical data warehouse of the Rennes Hospital and machine learning algorithms (logistic regression, random forest, and support vector machine). …”
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Mechanisms of drug resistance to neoadjuvant chemotherapy in breast cancer by K. A. Aliev, E. Yu. Zyablitskaya, T. P. Makalish, L. E. Sorokina, E. R. Asanova

“…The presented results can serve as the basis for the creation of diagnostic algorithms that have predictive value regarding the effectiveness of NCT, and also to help identify new targets to justify the use of combined breast cancer treatments in the early stage.…”
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%diag_test: a generic SAS macro for evaluating diagnostic accuracy measures for multiple diagnostic tests by Jacques K. Muthusi, Peter W. Young, Frankline O. Mboya, Samuel M. Mwalili

“…We also used the macro to reproduce results of published work on evaluating performance of multiple classification machine learning algorithms for predicting coronary artery disease. Conclusion The SAS macro presented here is a powerful analytic tool for analyzing data from multiple diagnostic tests. …”
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Emerging Healthcare Technologies in Gastrointestinal Endoscopy: 75 Years of Evolution by Irina Florina CHERCIU HARBIYELI, Elena Daniela BURTEA, Vlad IOVANESCU, Dan Nicolae FLORESCU, Ion ROGOVEANU, Dan Ionut GHEONEA, Adrian SAFTOIU

“…One of the most significant advancements is AI-driven endoscopy systems (EndoBrain, NvisionVLE, EndoAngel, GI Genius). Machine learning algorithms assist in real-time polyp detection, classification, and predictive analytics, enhancing diagnostic accuracy while reducing inter-observer variability and human error. …”
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New Insights into the Role of the Immune Microenvironment in Breast Carcinoma by Luis de la Cruz-Merino, Antonio Barco-Sánchez, Fernando Henao Carrasco, Esteban Nogales Fernández, Ana Vallejo Benítez, Javier Brugal Molina, Antonio Martínez Peinado, Ana Grueso López, Manuel Ruiz Borrego, Manuel Codes Manuel de Villena, Víctor Sánchez-Margalet, Adoración Nieto-García, Emilio Alba Conejo, Noelia Casares Lagar, José Ibáñez Martínez

“…Infiltration by tumor infiltrating lymphocytes (TIL) and their subtypes, tumor-associated macrophages (TAM) and myeloid-derived suppressive cells (MDSC) seem bona fide prognostic and even predictive biomarkers, that will eventually be incorporated into diagnostic and therapeutic algorithms of breast cancer. …”
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Deployment of real-time particle detection monitoring system in operating theatres for airborne contamination assessments: a methodological evaluation by Frans Stålfelt, Johan Tenghamn, Henrik Malchau, Karin Svensson Malchau

“…Future research should focus on integrating predictive algorithms and machine-learning to enhance clinical utility and drive improvements in surgical safety. …”
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Digital Self-Management Intervention Paths for Early Breast Cancer Patients: Results of a Pilot Study by Paula Poikonen-Saksela, Evangelos Karademas, Leena Vehmanen, Meri Utriainen, Haridimos Kondylakis, Konstadina Kourou, Georgios C. Manikis, Eleni Kolokotroni, Panagiotis Argyropaidas, Berta Sousa, Ruth Pat Horenczyk, Ketti Mazzocco, Johanna Mattson

“…Based on these answers and predictive algorithms for anxiety and depression, they were guided onto one or several digital intervention paths. …”
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Identification and validation of biomarkers, construction of diagnostic models, and investigation of immunological infiltration characteristics for idiopathic frozen shoulder by Han-tao Jiang, Li-ping Shen, Meng-Qi Pang, Min-jiao Wu, Jiang Li, Wei-jie Gong, Gang Jin, Rang-teng Zhu

“…The nomogram constructed based on them had a good predictive value for the occurrence of FS. Except for DCN, the other four genes were upregulated in FS samples, and the expression of SNAI1, TWIST1, and TUBB2B was also observed to be significantly upregulated in RT-qPCR. …”
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The influence of pH and temperature on benthic chlorophyll-a: Insights from SHAP-XGBoost and random forest models by Sangar Khan, Noël P.D. Juvigny-Khenafou, Tatenda Dalu, Paul J. Milham, Yasir Hamid, Kamel Mohamed Eltohamy, Habib Ullah, Bahman Jabbarian Amiri, Hao Chen, Naicheng Wu

“…There is little information on machine learning predictive models of benthic chl–a and input parameters in lotic ecosystems, and to fill this gap, we predict benthic chl–a levels in China's Thousand Islands Lake (TIL) watershed using machine learning algorithms. …”
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Machine learning-assisted quantitative metabolomics of West African patients with advanced breast cancer by Aboubacar Dit Tietie Bissan, Mathieu Michel, Xavier Dieu, Cinzia Bocca, Awo Emmanuela Hilda Amegonou, Fatoumata Matokoma Sidibe, Madani Ly, Bocary Sidi Koné, Nènè Oumou Kesso Barry, Kletigui Casimir Dembélé, Bakary Cissé, Bourèma Kouriba, Gilles Simard, Delphine Mirebeau-Prunier, Juan Manuel Chao de la Barca, Zahra Ouzzif, Pascal Reynier

“…The data were compared with those of 79 healthy controls using a combination of several machine learning approaches and statistical analyses. The predictive models obtained with the machine learning algorithms were comparable, with the best AUC of 0.878 obtained with ridge logistic regression using Boruta feature selection. …”
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