Trends in management of odontoid fractures 2010–2021 by Michael J. Gouzoulis, BS, Anthony E. Seddio, BS, Albert Rancu, BS, Sahir S. Jabbouri, MD, Jay Moran, MD, Arya Varthi, MD, Daniel R. Rubio, MD, Jonathan N. Grauer, MD

“…While these decisions were predicted by some clinical factors, both also correlated with nonclinical factors suggesting room for more consistent algorithms.…”
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Diagnosing prostate cancer in the PSA gray zone through machine learning and transrectal ultrasound video by Qin Wu, Chengyi Wu, Maoliang Zhang, Jie Yang, Junxiang Zhang, Yun Jin, Yanhong Du, Xingbo Sun, Liyuan Jin1, Kai Wang, Zhengbiao Hu, Xiaoyang Qi1, Jincao Yao, Zhengping Wang, Dong Xu

“…Background: We developed a machine learning-based predictive model for diagnosing prostate cancer within the gray zone of prostate-specific antigen (PSA) levels, leveraging transrectal prostate ultrasound video clips. …”
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Enhancing Ophthalmic Diagnosis and Treatment with Artificial Intelligence by David B. Olawade, Kusal Weerasinghe, Mathugamage Don Dasun Eranga Mathugamage, Aderonke Odetayo, Nicholas Aderinto, Jennifer Teke, Stergios Boussios

“…Despite these advancements, challenges remain, particularly concerning data privacy, security, and algorithmic bias. Ensuring robust data governance and ethical practices is crucial for the continued success of AI integration in ophthalmology. …”
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Integration of AI with artificial sensory systems for multidimensional intelligent augmentation by Changyu Tian, Youngwook Cho, Youngho Song, Seongcheol Park, Inho Kim, Soo-Yeon Cho

“…We introduce specialized AI algorithms and raw data processing methods for each function, designed to enhance and optimize sensing performance. …”
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Investigating imperceptibility of adversarial attacks on tabular data: An empirical analysis by Zhipeng He, Chun Ouyang, Laith Alzubaidi, Alistair Barros, Catarina Moreira

“…Adversarial attacks are a potential threat to machine learning models by causing incorrect predictions through imperceptible perturbations to the input data. …”
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Deep Learning and Automatic Detection of Pleomorphic Esophageal Lesions—A Necessary Step for Minimally Invasive Panendoscopy by Miguel Martins, Miguel Mascarenhas, Maria João Almeida, João Afonso, Tiago Ribeiro, Pedro Cardoso, Francisco Mendes, Joana Mota, Patrícia Andrade, Hélder Cardoso, Miguel Mascarenhas-Saraiva, João Ferreira, Guilherme Macedo

“…Deep-learning (DL) algorithms were developed for the detection of enteric and gastric lesions. …”
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DAFDM: A Discerning Deep Learning Model for Active Fire Detection Based on Landsat-8 Imagery by Xu Gao, Wenzhong Shi, Min Zhang, Lukang Wang

“…The proposed method outperforms other AF detection algorithms, achieving IoU and F1-score of 87.28% and 93.21%, respectively. …”
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Machine learning integration of multimodal data identifies key features of circulating NT-proBNP in people without cardiovascular diseases by Zhiyuan Ning, Xuanfei Jiang, Huan Huang, Honggang Ma, Ji Luo, Xiangyan Yang, Bing Zhang, Ying Liu

“…The optimal features predicting NT-proBNP levels were identified using univariate and step-forward multivariate models. …”
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Thermal one-point functions and their partial wave decomposition by Ilija Burić, Francesco Russo, Volker Schomerus, Alessandro Vichi

“…With the help of Casimir differential equations we develop efficient algorithms to compute the relevant conformal blocks for an external field of arbitrary spin and with any spin exchange along the thermal circle, at least in three dimensions. …”
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Optimization Strategies in Quantum Machine Learning: A Performance Analysis by Nouf Ali AL Ajmi, Muhammad Shoaib

“…This study presents a comprehensive comparison of multiple optimization algorithms applied to a quantum classification model, utilizing the Cleveland dataset. …”
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Artificial Intelligence: The Latest Advances in the Diagnosis of Bladder Cancer by Satyendra Singh, Ram Mohan Shukla

“…This review explores the current state and potential of AI technologies, including machine learning algorithms, deep learning networks, and computer vision, in enhancing the diagnostic process for bladder cancer. …”
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Roles of Modeling and Artificial Intelligence in LPBF Metal Print Defect Detection: Critical Review by Scott Wahlquist, Amir Ali

“…The primary objectives of this article are to introduce the reader to the most widely read published data on (1) the roles of numerical and analytical models in LPBF defect detection; (2) AI algorithms and models applicable to predict LPBF metal defects and causes; and (3) the integration of modeling, AI, and sensing technology, which is commonly used in material characterization and has been proven efficient and applicable to LPBF metal part defect detection over extended periods.…”
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The Evolution of Portfolio Theory: Integrating Machine Learning with Markowitz Optimization by Xu Junhao

“…Techniques such as linear regression, clustering algorithms, and principal component analysis (PCA) facilitate superior forecasting and portfolio design in various market environments. …”
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Kinetic Modelling of Methanol to Propylene Process on Cerium-hierarchical SAPO-34 Catalyst by masoumeh ghalbi-ahangary, Ali Taheri Najafabadi, Parviz Rashidi-Ranjbar, Zahra Taheri

“…The parameters were then estimated based on the experimental data using genetic algorithms. Comparing the experiments with the predicted data suggests a good correlation between the experimental data and the model.…”
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Radiomic nomograms in CT diagnosis of gall bladder carcinoma: a narrative review by Nirupam Konwar Baishya, Kangkana Baishya

“…Abstract Radiomics is a method that extracts many features from medical images using various algorithms. Medical nomograms are graphical representations of statistical predictive models that produce a likelihood of a clinical event for a specific individual based on biological and clinical data. …”
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Machine Learning and Data Science in Social Sciences: Methods, Applications, and Future Directions by Elias Dritsas, Maria Trigka

“…While these tools enhance analytical capacity, they raise critical concerns about algorithmic bias, transparency, and ethical accountability. …”
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Lay beliefs about AI assessment of interpersonal skills in personnel selection by Ilyung Cheong, Young Eun Huh, Stefano Puntoni

“…This effect was not observed for analytical skills, suggesting that the results stem from lay beliefs about the suitability of AI in interpersonal contexts and not from a generalized aversion to algorithms. These lay beliefs bias managers’ perceptions of employees: managers were less likely to assign tasks requiring interpersonal skills to AI-selected (vs. human-selected) employees. …”
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Advanced Operator Theory for Energy Market Trading: A New Framework by Michele Bufalo, Viviana Fanelli

“…Furthermore, we apply these findings to energy market trading by developing specialized simulation algorithms and forecasting models. These methodologies were tested across all assets comprising the S&P 500 Energy Index, evaluating their predictive accuracy and effectiveness in capturing market dynamics. …”
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APOPTOSIS IN CITY SYSTEMS: A BIOMIMETIC APPROACH TO CITY REGENERATION by Stephen Ajadi

“…Aided with streamlined programmatic principles, computational and algorithmic design, city systems are studied in an African context. …”
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Detecting and Explaining Postpartum Depression in Real-Time with Generative Artificial Intelligence by Silvia García-Méndez, Francisco de Arriba-Pérez

“…Moreover, it addresses the black box problem since the predictions are described to the end users thanks to the combination of LLMS with interpretable ML models (i.e. tree-based algorithms) using feature importance and natural language. …”
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