Flow cytometry for screening and prioritisation of urine samples: a retrospective comparison with culture by Vicky Sender, John Kerr White, Ludvig Bolinder, Karin Amilon, Mirja Hägg, Karin Haij Bhattarai, Niklas K. Björkström, Baharak Saeedi

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Comparative Effectiveness of Fumarates Versus Sphingosine-1-Phosphate Receptor Modulators in Black Patients with Multiple Sclerosis by Sophia Woodson, Edward J. Gettings, Chu-Yueh Guo, Sylvia Klineova, Jong-Mi Lee, Rebecca S. Romero, Aljoeson Walker, Nicholas Belviso, Sai L. Shankar, Jason P. Mendoza, Boyang Bian, James B. Lewin, Kinyee Fong

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Rotor Location During Atrial Fibrillation: A Framework Based on Data Fusion and Information Quality by Miguel A. Becerra, Diego H. Peluffo-Ordoñez, Johana Vela, Cristian Mejía, Juan P. Ugarte, Catalina Tobón

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Co‐Expression of MHC‐II and ANXA1: Mediators of PD‐1/PD‐L1 Therapy Resistance in Breast Cancer by Hao Wang, Ji‐Feng Sun, Chen Wang, Zhan‐Sheng Jiang, Zhong‐Sheng Tong

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Artificial Intelligence in Pediatric Blood Transfusion during Anesthesia: A Scoping Review by Parisa Akbarpour, Parisa Moradimajd, Azam Saei, Maryam Aligholizadeh, Siavash Sangi

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Otitis externa in dogs (prevalence, etiology, clinical course, and treatment regimens) by D. L. Datsiuk, V. M. Hunchak, B. V. Gutyj, I. I. Khariv, R. O. Vasiv, V. P. Martynyshyn

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Multi-omics analysis identifies SNP-associated immune-related signatures by integrating Mendelian randomization and machine learning in hepatocellular carcinoma by Qingyan Kou, Zhichao Wu, Wenbin Zhao, Zhenyuan Liu, Shengxian Qiao, Qiang Mu, Xu Zhang

“…And the key gene SLC16A3 and STRBP can significantly promote the proliferation and invasion ability of HCC cells. …”
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Tensor RT optimized driver drowsiness detection system using edge device by Chandramohan Dhasarathan, Sambasivam Gnanasekaran, Arnab Pattanayak, Gourav Kumar, Kartik Vig, Vaibhav Narain, K.M. Deva Narayan, Sunidhi Garg

“…The proposed approach utilizes multiple models to improve and accurately detecting driver drowsiness, with the models being InceptionV3, ResNet50, VGG-16, and MobileNetV1. The system uses transfer learning techniques for implementing CNN model algorithms to analyze live video from the camera module, allowing for real-time detection of driver behavior such as fatigue or distraction. …”
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Projecting future changes in potato yield using machine learning techniques: a case study for Prince Edward Island, Canada by Dania Tamayo-Vera, Kai Liu, Antonio Bolufé-Röhler, Xiuquan Wang

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Development of a warning model for drug-induced liver injury in the older patients by Qiaozhi Hu, Qiaozhi Hu, Xiaoqi Li, Xiaoqi Li, Dan Zou, Zhiyao He, Zhiyao He, Ting Xu

“…The performance of 8 ML algorithms—XGBoost, LightGBM, Random Forest, AdaBoost, CatBoost, Gradient Boosting Decision Trees, Artificial Neural Network, and TabNet—was assessed. …”
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Automated Recognition of Abnormalities in Gastrointestinal Endoscopic Images – Evaluation of an AI Tool for Identifying Polyps and Other Irregularities by Weronika Jarych, Elżbieta Tokarczyk, Patryk Iglewski, Daria Ziemińska, Karina Motolko, Rafał Burczyk, Konrad Duszyński, Michał Kociński, Jan Reinald Wendt

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Exploring the Current Status of Risk Stratification in Hypertrophic Cardiomyopathy: From Risk Models to Promising Techniques by Alexandros Kasiakogias, Christos Kaskoutis, Christos-Konstantinos Antoniou, Stavros Georgopoulos, Dimitrios Tsiachris, Petros Arsenos, Alexandrina Kouroutzoglou, Dimitrios Klettas, Charalambos Vlachopoulos, Konstantinos Tsioufis, Konstantinos Gatzoulis

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Establishing a clinical prediction model for diabetic foot ulcers in type 2 diabetic patients with lower extremity arteriosclerotic occlusion using machine learning by Yubo Wang, Chunyu Jiang, Yi qi Xing, Linxuan Zou, Mingzhi Song, Xueling Qu, Zhuqiang Jia, Lin Zhao, Xin Han, Junwei Zong, Shouyu Wang

“…Logistic regression analyses, 3 kinds of machine learning algorithms, a predictive model and nomogram was formulated to estimate the risk of DFU occurrence among diabetic patients with lower extremity ASO. …”
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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

“…Second, we investigated 3 strategies (logistic regression, decision tree, and a custom strategy based on score interpretation) to combine the model’s score with the score from an image-based model to produce a robust bladder cancer scoring system. …”
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Artificial intelligence (AI) in restorative dentistry: current trends and future prospects by Mariya Najeeb, Shahid Islam

“…Key challenges include data privacy concerns, algorithmic bias, interpretability of AI decision-making processes, and the need for standardized AI training programs in dental education. …”
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Investigating Whether AI Will Replace Human Physicians and Understanding the Interplay of the Source of Consultation, Health-Related Stigma, and Explanations of Diagnoses on Patien... by Weiqi Guo, Yang Chen

“…Health-related stigma had no significant effect on how people evaluated the medical consultation or contributed to preferring AI-powered systems over humans (P>.05); however, providing explanations of the diagnosis significantly improved the functional (P<.001), relational (P<.05), and emotional (P<.05) evaluations of the consultation for all 3 medical agents. ConclusionsThe findings imply that at the current stage of AI development, people trust human expertise more than accurate AI, especially for decisions traditionally made by humans, such as medical diagnosis, supporting the algorithm aversion theory. …”
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Predicting Treatment Outcomes in Patients with Low Back Pain Using Gene Signature-Based Machine Learning Models by Youzhi Lian, Yinyu Shi, Haibin Shang, Hongsheng Zhan

“…These key genes were then used to train 45 machine learning models by combining nine different algorithms: Logistic Regression, K-Nearest Neighbors, Support Vector Machine, Decision Tree, Random Forest, Gradient Boosting Machine, Multilayer Perceptron, Naive Bayes, and Linear Discriminant Analysis. …”
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Multi-Level Depression Severity Detection with Deep Transformers and Enhanced Machine Learning Techniques by Nisar Hussain, Amna Qasim, Gull Mehak, Muhammad Zain, Grigori Sidorov, Alexander Gelbukh, Olga Kolesnikova

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Evaluating axillary lymph node metastasis risks in breast cancer patients via Semi-ALNP: a multicenter studyResearch in context by Limeng Qu, Jinfeng Zhu, Xilong Mei, Zixi Yi, Na Luo, Songlin Yuan, Xuan Liu, Mingwen Liu, Haiqing Xie, Xiongqiang Hu, Liangrui Pan, Qingchun Liang, Yanhui Li, Qiongyan Zou, Qin Zhou, Danhua Zhang, Meirong Zhou, Lei Pei, Ke Qian, Qian Long, Qitong Chen, Xi Chen, Jennifer K. Plichta, Qingyao Shang, Meishuo Ouyang, Jiachi Xu, Wenjun Yi

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Artificial Intelligence in Healthcare: Medical Students' Perspectives on Balancing Innovation, Ethics, and Patient-Centered Care by Eleanor Roy, Sara Malafa, Lina M. Adwer, Houda Tabache, Tanishqa Sheth, Vasudha Mishra, Moaz Elsayed Abouelmagd, Andrea Cushieri, Sajjad Ahmed Khan, Mihnea-Alexandru Gaman, Juan C. Puyana, Francisco Javier Bonilla-Escobar

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