Exploring the Landscape of Operating Room Scheduling: A Bibliometric Analysis of Recent Advancements and Future Prospects by Md Al Amin, Majed Hadid, Adel Elomri, Rabah Ismaen, Ismail Dergaa, Hind Alashi, Amal Jobran Al-Hajaji, Moustafa Alkhalil, Omar M Aboumarzouk, Abdelfatteh EL Omri

“…Citation analysis highlighted heuristic algorithms and integer programing as central ORS themes. …”
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Comprehensive evaluation of phosphoproteomic-based kinase activity inference by Sophia Müller-Dott, Eric J. Jaehnig, Khoi Pham Munchic, Wen Jiang, Tomer M. Yaron-Barir, Sara R. Savage, Martin Garrido-Rodriguez, Jared L. Johnson, Alessandro Lussana, Evangelia Petsalaki, Jonathan T. Lei, Aurelien Dugourd, Karsten Krug, Lewis C. Cantley, D. R. Mani, Bing Zhang, Julio Saez-Rodriguez

“…We then demonstrate how kinase activity inference aids characterize kinase inhibitor responses in cell lines. …”
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Development and validation of web-based, interpretable predictive models for sepsis and mortality in extensive burns by Shi-Qi Wang, Shi-Qi Wang, Kan Qiu, Qi-Rui Zheng, Bing-Jie Zhou, Ming-Yu Li, Hai-Yan Zhong, Yong Chen, Si-Ming Yuan, Si-Ming Yuan

“…We applied ten machine learning algorithms, including random forest, gradient boosting tree (GBT), and logistic regression, to predict sepsis and mortality. …”
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Distilling knowledge from graph neural networks trained on cell graphs to non-neural student models by Vasundhara Acharya, Bülent Yener, Gillian Beamer

“…Abstract The development and refinement of artificial intelligence (AI) and machine learning algorithms have been an area of intense research in radiology and pathology, particularly for automated or computer-aided diagnosis. …”
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Perioperative management of patients with rheumatic disorders: problems and solutions by A. A. Klimenko, A. A. Kondrashov

“…Currently management of patients with rheumatic disorders (RD) involves not only application of all of the known spectrum of mediations in accordance with current guidelines and algorithms but also timely use of high-tech medical care, for example, endoprosthesis of the large joints, spinal surgery, dental care, endovascular surgery, aimed at decreasing the level of disability and improving patients’ quality of life. …”
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Data-Driven Revolution in Academic Support for Mathematics Underachievers through Random Forest Individual and Hybrid Model by Asadi Srinivasulu, Vanithamani Palanisamy

“…Furthermore, metaheuristic algorithms like Smell Agent Optimization and Giant Trevally Optimizer were employed to optimize model's hyperparameters, with the intention of enhancing accuracy and precision in performance estimations. …”
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Defect Detection and 3D Reconstruction of Complex Urban Underground Pipeline Scenes for Sewer Robots by Ruihao Liu, Zhongxi Shao, Qiang Sun, Zhenzhong Yu

“…Comprehensive comparisons and analyses are conducted with 12 mainstream detection algorithms to validate the superiority of the proposed model. …”
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Comprehensive evaluation of machine learning models for predicting the cognitive status of Alzheimer's disease subjects and susceptible by Lucien Gnegne Meteumba, Vaghawan Prasad Ojha, Shantia Yarahmadian

“…Overall, this work shows us how machine learning can aid in the understanding of Alzheimer disease and its identification by offering an important means to improve patient outcomes through early treatment strategies based on predictive analytics.…”
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Virtual Reality-Assisted Goalkeeper Training for Upper Limb Rehabilitation in a Safe and Adapted Patient Environment by Vanesa Herrera, Javier Albusac, Eusebio Angulo, Carlos Gonzalez-Morcillo, Ana de Los Reyes-Guzman, David Vallejo

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Diagnosis of Lung Cancer Using Endobronchial Ultrasonography Image Based on Multi-Scale Image and Multi-Feature Fusion Framework by Huitao Wang, Takahiro Nakajima, Kohei Shikano, Yukihiro Nomura, Toshiya Nakaguchi

“…The primary aim of this study is to develop a computer-aided diagnosis (CAD) system for lung cancer using endobronchial ultrasonography (EBUS) images and deep learning algorithms to facilitate early detection and improve patient survival rates. …”
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Interpretable machine learning models for prolonged Emergency Department wait time prediction by Hao Wang, Nethra Sambamoorthi, Devin Sandlin, Usha Sambamoorthi

“…We employed five ML algorithms - cross-validation logistic regression (CVLR), random forest (RF), extreme gradient boosting (XGBoost), artificial neural network (ANN), and support vector machine (SVM) - for predicting patient prolonged wait times. …”
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A recurrence model for non-puerperal mastitis patients based on machine learning. by Gaosha Li, Qian Yu, Feng Dong, Zhaoxia Wu, Xijing Fan, Lingling Zhang, Ying Yu

“…A combination of four machine learning algorithms (XGBoost、Logistic Regression、Random Forest、AdaBoost) was employed to predict NPM recurrence, and the model with the highest Area Under the Curve (AUC) in the test set was selected as the best model. …”
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RETRACTED ARTICLE: A combined microfluidic deep learning approach for lung cancer cell high throughput screening toward automatic cancer screening applications by Hadi Hashemzadeh, Seyedehsamaneh Shojaeilangari, Abdollah Allahverdi, Mario Rothbauer, Peter Ertl, Hossein Naderi-Manesh

“…The rapid development of machine learning techniques, especially deep learning algorithms, has attracted much interest in its application to medical image problems. …”
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Artificial Intelligence-based Approaches for Characterizing Plaque Components From Intravascular Optical Coherence Tomography Imaging: Integration Into Clinical Decision Support Sy... by Michela Sperti, Camilla Cardaci, Francesco Bruno, Syed Taimoor Hussain Shah, Konstantinos Panagiotopoulos, Karim Kassem, Giuseppe De Nisco, Umberto Morbiducci, Raffaele Piccolo, Francesco Burzotta, Fabrizio D’Ascenzo, Marco Agostino Deriu, Claudio Chiastra

“…To increase productivity, precision, and reproducibility, researchers are increasingly integrating artificial intelligence (AI)-based techniques into IVOCT analysis pipelines. Machine learning algorithms, trained on labelled datasets, have demonstrated robust classification of various plaque types. …”
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Applications of Artificial Intelligence in Psychiatry and Psychology Education: Scoping Review by Julien Prégent, Van-Han-Alex Chung, Inès El Adib, Marie Désilets, Alexandre Hudon

“…Barriers included limited AI training, ethical concerns, lack of digital literacy, algorithmic opacity, and insufficient curricular integration. …”
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A mobile app to improve adherence to colorectal cancer screening and post polypectomy surveillance guidelines by María A. Casas, Francisco Schlottmann, Leandro Steinberg, Xavier Bessa, Anna Serradesanferm, Angels Pozo, Sonia Torres, Antoni Castells, Francesc Balaguer, Jaume Grau, Lisandro Pereyra, María Pellisé

“…Methods A mobile app including ergonomic algorithms integrating all pertinent guideline information was created by a group of experts. …”
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The Clinical Significance of Abnormal Electroencephalography (EEG) Patterns in Patients with Neuropsychiatric Disorders Due to Anti-NMDA Receptor Encephalitis: A Comparative Study by Alvaro Moreno-Avellán, Arely Juarez-Jaramillo, Maria del Carmen Fernandez Gonzalez-Aragon, Gerardo Quiñones-Pesqueira, Luz Maria Pineda-Centeno, Mariana Espinola-Nadurille, Victoria Martinez-Angeles, Francisco Martinez-Carrillo, Veronica Rivas-Alonso, Daniel San-Juan, Jose Flores-Rivera, Jesus Ramirez-Bermudez

“…These findings support the integration of EEG into diagnostic algorithms to guide early detection and management of autoimmune encephalitis.…”
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A machine learning model for predicting obesity risk in patients with diabetes mellitus: analysis of NHANES 2007–2018 by Wenqiang Wang, Ruiqing Mo, Xingyu Chen, Sijie Yang

“…Our findings highlight key clinical features associated with obesity risk and provide a practical tool to aid in early identification and individualized management of high-risk patients.…”
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Exploring ribosome biogenesis in lung adenocarcinoma to advance prognostic methods and immunotherapy strategies by Zipei Song, Yuheng Wang, Miaolin Zhu, Pengpeng Zhang, Zhihua Li, Xin Geng, Xincen Cao, Jianan Zheng, Jianwei Tang, Liang Chen

“…Employing various machine learning algorithms, a ribosome biogenesis-related signature (RBS) was constructed and compared to 140 published LUAD prognostic models. …”
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Computer vision applications for the detection or analysis of tuberculosis using digitised human lung tissue images - a systematic review by Kapongo D. Lumamba, Gordon Wells, Delon Naicker, Threnesan Naidoo, Adrie J. C. Steyn, Mandlenkosi Gwetu

“…The ultimate goal is to promote the development of more efficient and accurate algorithms for the detection or analysis of TB, and raise awareness about the importance of early detection. …”
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