Using multiple drug similarity networks to promote adverse drug event detection by Biswajit Padhi, Ruoqi Liu, Yuedi Yang, Xueqiao Peng, Lang Li, Pengyue Zhang, Ping Zhang

“…Results demonstrate that enhanced drug safety signals with pre-clinical information outperform the standard safety signal detection algorithms on early ADE detection. In addition, we systematically evaluate the performance of different drug similarities against different types of ADEs. …”
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Parallax-Tolerant Weakly-Supervised Pixel-Wise Deep Color Correction for Image Stitching of Pinhole Camera Arrays by Yanzheng Zhang, Kun Gao, Zhijia Yang, Chenrui Li, Mingfeng Cai, Yuexin Tian, Haobo Cheng, Zhenyu Zhu

“…Camera arrays typically use image-stitching algorithms to generate wide field-of-view panoramas, but parallax and color differences caused by varying viewing angles often result in noticeable artifacts in the stitching result. …”
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Updates, Applications and Future Directions of Deep Learning for the Images Processing in the Field of Cranio-Maxillo-Facial Surgery by Luca Michelutti, Alessandro Tel, Massimo Robiony, Lorenzo Marini, Daniele Tognetto, Edoardo Agosti, Tamara Ius, Caterina Gagliano, Marco Zeppieri

“…Further development of deep learning algorithms capable of analyzing image sequences, integrating multimodal data, i.e., combining information from different sources, and developing human–machine interfaces to facilitate the integration of these tools with clinical reality are expected. …”
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Screening biomarkers related to cholesterol metabolism in osteoarthritis based on transcriptomics by ChenDeng Lao, Wei Wei, JianWen Cheng, ShiJie Liao, XiaoLin Luo, Qian Huang, HengZhen Huang, JinMin Zhao

“…Three machine learning algorithms identified ATF3, CHKA, CLU, CTNNB1, and FASN as potential biomarkers. …”
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Machine learning-based identification of exosome-related biomarkers and drugs prediction in nasopharyngeal carcinoma by Zhengyu Wei, Guoli Wang, Yanghao Hu, Chongchang Zhou, Yuna Zhang, Yi Shen, Yaowen Wang

“…Results Through the application of three machine learning algorithms, five key genes (LTF, IDH1, ITGAV, CCL2, and LGALS3BP) were identified for the construction of a diagnostic model. …”
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Monitoring poultry social dynamics using colored tags: Avian visual perception, behavioral effects, and artificial intelligence precision by Florencia B. Rossi, Nicola Rossi, Gabriel Orso, Lucas Barberis, Raul H. Marin, Jackelyn M. Kembro

“…However, maintaining the identity of individuals over time, especially in homogeneous poultry flocks, remains challenging for algorithms. We propose using differentially colored “backpack” tags (black, gray, white, orange, red, purple, and green) detectable with computer vision (eg. …”
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Comparison of Radiomics and conventional SUVr methods for Alzheimer’s disease classification using AV45 PET imaging by Haiyan Gao, Arui Tan, Junhao Wu, Zhen Cao, Ziyang Zhu, Wei Zhang

“…Model accuracy, sensitivity, specificity, and precision were evaluated using the Mann–Whitney test, DeLong test, and confusion matrices.ResultsThere were no significant differences in gender and age between AD and NAD groups (p > 0.05). …”
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Automatic Analysis of Ultrasound Images to Estimate Subcutaneous and Visceral Fat and Muscle Tissue in Patients with Suspected Malnutrition by Antonio Cuesta-Vargas, José María Arjona-Caballero, Gabriel Olveira, Daniel de Luis Román, Diego Bellido-Guerrero, Jose Manuel García-Almeida

“…However, area-based measurements demonstrated lower precision due to differences between manual adjustments by experts and automatic geometric approximations. …”
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Intelligent diagnosis of thyroid nodules with AI ultrasound assistance and cytology classification by Xiaojuan Cai, Ya Zhou, Jie Ren, Jinrong Wei, Shiyu Lu, Hanbing Gu, Weizhe Xu, Xun Zhu

“…ObjectiveAccurate evaluation of thyroid nodules is crucial for effective management; however, methods such as ultrasonography and Fine Needle Aspiration Cytology (FNAC) can be subjective and operator-dependent. …”
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Deep Learning Network Selection and Optimized Information Fusion for Enhanced COVID-19 Detection: A Literature Review by Olga Adriana Caliman Sturdza, Florin Filip, Monica Terteliu Baitan, Mihai Dimian

“…Recent developments in COVID-19 diagnosis involve constructing expansive multi-noise information sets while creating clinical process-oriented AI algorithms and implementing distributed learning protocols for securing information security and system stability. …”
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The Impact of AI-Generated Instructional Videos on Problem-Based Learning in Science Teacher Education by Nikolaos Pellas

“…The limited impact of the preview feature highlights the need for careful design and evaluation of instructional elements, such as interactivity and adaptive learning algorithms, to fully realize their potential.…”
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Mortality prediction of heart transplantation using machine learning models: a systematic review and meta-analysis by Ida Mohammadi, Setayesh Farahani, Asal Karimi, Saina Jahanian, Shahryar Rajai Firouzabadi, Mohammadreza Alinejadfard, Alireza Fatemi, Bardia Hajikarimloo, Mohammadhosein Akhlaghpasand

“…Model performance was evaluated using pooled area under the curve (AUC) values, with subgroup analyses for algorithm type, validation methods, and prediction timeframes. …”
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Facial emotion based smartphone addiction detection and prevention using deep learning and video based learning by C. Joseph, P. Uma Maheswari

“…Based on detected emotions such as happiness, sadness, or anger, the system dynamically shuffles motivational videos using advanced algorithms like Fisher-Yates and Durstenfeld shuffling techniques to promote behavioral change. …”
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A Machine-Learning Model for the Prediction of Triple-Negative Breast Cancer Based on Multiparameter MRI by Cai Y, Li Y, Wang W, Zhou Y, Wang J, Zhang L, Lu H

“…In the primary cohort, univariate analysis, logistic regression analysis and Boruta algorithm were used to determine the independent predictors for TNBC and non-TNBC. …”
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Deep learning methods for clinical workflow phase-based prediction of procedure duration: a benchmark study by Emanuele Frassini, Teddy S. Vijfvinkel, Rick M. Butler, Maarten van der Elst, Benno H. W. Hendriks, John J. van den Dobbelsteen

“…This study evaluates the performance of deep learning models in the prediction of the end time of procedures performed in the cardiac catheterization laboratory (cath lab). …”
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Assessing the Impact of Land Use Changes on Ecosystem Service Values in Coal Mining Regions Using Google Earth Engine Classification by Shi Chen, Jiwei Qin, Shuning Dong, Yixi Liu, Pingping Sun, Dongze Yao, Xiaoyan Song, Congcong Li

“…We employed a random forest algorithm to classify land use patterns and calculated key indices—including the normalized difference vegetation index (NDVI), normalized difference built-up index (NDBI), enhanced vegetation index (EVI), and bare soil index (BSI)—which were combined with topographic features. …”
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Effects of the unity vacuum suspension system on transtibial gait for simulated non-level surfaces. by Gabrielle Thibault, Hossein Gholizadeh, Emily Sinitski, Natalie Baddour, Edward D Lemaire

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A Novel Audio Copy Move Forgery Detection Method With Classification of Graph-Based Representations by Beste Ustubioglu, Gul Tahaoglu, Arda Ustubioglu, Guzin Ulutas, Muhammed Kilic

“…The trained model was evaluated using five different datasets, demonstrating that this approach generally outperforms existing methods in terms of detection accuracy. …”
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Assessing CO2 separation performances of IL/ZIF-8 composites using molecular features of ILs by Hasan Can Gulbalkan, Alper Uzun, Seda Keskin

“…Given the vast number and diversity of metal-organic frameworks (MOFs) and ionic liquids (ILs), it is impractical to experimentally test the gas adsorption and separation potential of each one of the possible IL/MOF composites formed by the different combinations of these two components. In this study, we developed a comprehensive computational approach integrating Conductor-like Screening Model for Realistic Solvents (COSMO-RS) calculations, density functional theory (DFT) calculations, Grand Canonical Monte Carlo (GCMC) simulations, and machine learning (ML) algorithms to evaluate a wide variety of IL-incorporated ZIF-8 composites for CO2 separations. …”
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Effect of Time-of-Flight and Regularized Reconstructions on Quantitative Measurements and Qualitative Assessments in Newly Diagnosed Prostate Cancer With F-Fluorocholine Dual Time... by Spencer C. Behr MD, Brett J. Mollard MD, Jaewon Yang PhD, Robert R. Flavell MD, PhD, Randall A. Hawkins MD, PhD, Youngho Seo PhD

“…Recent technical advances in positron emission tomography/magnetic resonance imaging (PET/MRI) technology allow much improved time-of-flight (TOF) and regularized iterative PET reconstruction regularized iterative reconstruction (RIR) algorithms. We evaluated the effect of TOF and RIR on standardized uptake values (maximum and peak SUV [SUV max and SUV peak ]) and their metabolic tumor volume dependencies and visual image quality for 18 F-fluorocholine PET/MRI in patients with newly diagnosed prostate cancer. …”
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