Acoustic-based machine learning approaches for depression detection in Chinese university students by Yange Wei, Yange Wei, Shisen Qin, Fengyi Liu, Rongxun Liu, Yunze Zhou, Yuanle Chen, Xingliang Xiong, Wei Zheng, Guangjun Ji, Yong Meng, Fei Wang, Fei Wang, Ruiling Zhang

“…Among five machine learning algorithms, LDA model demonstrated the highest classification performance, with an AUC of 0.771. …”
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Novel insights of disulfidptosis-mediated immune microenvironment regulation in atherosclerosis based on bioinformatics analyses by Huanyi Zhao, Zheng Jin, Junlong Li, Junfeng Fang, Wei Wu, J. F. Fang

“…In addition, we established a foam cell model in vitro and an AS mouse model in vivo to verify the expressions of hub genes. …”
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Cadmium Exposure Disrupts Uterine Energy Metabolism and Coagulation Homeostasis During Labor in Institute of Cancer Research Mice: Insights from Transcriptomic Analysis by Yueyang Wang, Yichen Bai, Yi Wang, Yan Cai

“…This study is the first to establish a model of Cd exposure in the uterus of laboring mice and investigate the underlying metabolic mechanisms through transcriptomic analysis. …”
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Sialyltransferase-related genes as predictive factors for therapeutic response and prognosis in cervical cancer by Jia Shao, Can Zhang, Yaonan Tang, Aiqin He, Xiangyan Cheng

“…Cox regression analysis and “glmnet” R package were applied to establish the relevant risk model. “MCPcounter” R package, ESTIMATE algorithm and TIMER online tools were used to depict the tumor immune microenvironment in CC. …”
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Artificial intelligence-driven label-free detection of chronic myeloid leukemia cells using ghost cytometry by Kohjin Suzuki, Naoki Watanabe, Yutaka Tsukune, Tadaaki Inano, Shintaro Kinoshita, Sayuri Tomoda, Kohei Yamada, Yusuke Konishi, Takuya Kuwana, Takeshi Sugiyama, Kenji Fukada, Kazuhiro Yamada, Miki Ando, Tomoiku Takaku

“…The AI model accurately detected CML cells and a strong correlation between AI-detected CML cells and actual BCR::ABL1 IS mRNA levels was observed. …”
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Predictive Study on the Cutting Energy Efficiency of Dredgers Based on Specific Cutting Energy by Junlang Yuan, Ke Yang, Taiwei Yang, Haoran Xu, Ting Xiong, Shidong Fan

“…Based on the machine learning framework, a model framework for predicting the specific cutting energy according to the relevant parameters of the suction-lifting system is constructed. …”
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Robustness evaluation of commercial liveness detection platform by Pengcheng WANG, Haibin ZHENG, Jianfei ZOU, Ling PANG, Hu LI, Jinyin CHEN

“…Liveness detection technology has become an important application in daily life, and it is used in scenarios including mobile phone face unlock, face payment, and remote authentication.However, if attackers use fake video generation technology to generate realistic face-swapping videos to attack the living body detection system in the above scenarios, it will pose a huge threat to the security of these scenarios.Aiming at this problem, four state-of-the-art Deepfake technologies were used to generate a large number of face-changing pictures and videos as test samples, and use these samples to test the online API interfaces of commercial live detection platforms such as Baidu and Tencent.The test results show that the detection success rate of Deepfake images is generally very low by the major commercial live detection platforms currently used, and they are more sensitive to the quality of images, and the false detection rate of real images is also high.The main reason for the analysis may be that these platforms were mainly designed for traditional living detection attack methods such as printing photo attacks, screen remake attacks, and silicone mask attacks, and did not integrate advanced face-changing detection technology into their liveness detection.In the algorithm, these platforms cannot effectively deal with Deepfake attacks.Therefore, an integrated live detection method Integranet was proposed, which was obtained by integrating four detection algorithms for different image features.It could effectively detect traditional attack methods such as printed photos and screen remakes.It could also effectively detect against advanced Deepfake attacks.The detection effect of Integranet was verified on the test data set.The results show that the detection success rate of Deepfake images by proposed Integranet detection method is at least 35% higher than that of major commercial live detection platforms.…”
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Digital augmentation of aftercare for patients with anorexia nervosa: the TRIANGLE RCT and economic evaluation by Janet Treasure, Katie Rowlands, Valentina Cardi, Suman Ambwani, David McDaid, Jodie Lord, Danielle Clark Bryan, Pamela Macdonald, Eva Bonin, Ulrike Schmidt, Jon Arcelus, Amy Harrison, Sabine Landau

“…However, some feedback was that the intervention offered too little, too late, and that a more personalised intervention would be more helpful. …”
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The Hajj legacy and Saudi Arabia’s exemplary response to COVID-19 by Ghadah Alsaleh, Bander Balkhi, Bander Balkhi, Ahmed Alahmari, Anas Khan

“…The Hajj legacy strengthened laboratory diagnostics and surge staffing, informed border screening algorithms, and guided large-event risk assessments. …”
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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

“…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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Randomization-Driven Hybrid Deep Learning for Diabetic Retinopathy Detection by A. M. Mutawa, G. R. Hemalakshmi, N. B. Prakash, M. Murugappan

“…We enhance the model’s diagnostic capability through complex image preprocessing techniques, such as improved noise reduction and morphological approaches. …”
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Data augmentation of time-series data in human movement biomechanics: A scoping review. by Christina Halmich, Lucas Höschler, Christoph Schranz, Christian Borgelt

“…These challenges make it difficult to train models that perform reliably across individuals, tasks, and settings. …”
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Opportunities and Challenges of Cardiovascular Disease Risk Prediction for Primary Prevention Using Machine Learning and Electronic Health Records: A Systematic Review by Tianyi Liu, Andrew J. Krentz, Zhiqiang Huo, Vasa Ćurčin

“…The synthesis underscores the superiority of ML in modeling intricate EHR-derived risk factors, facilitating precision-driven cardiovascular risk assessment. …”
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Lesion classification and diabetic retinopathy grading by integrating softmax and pooling operators into vision transformer by Chong Liu, Weiguang Wang, Jian Lian, Wanzhen Jiao

“…Therefore, plenty of automated screening technique have been developed to address this task.MethodsAmong these techniques, the deep learning models have demonstrated promising outcomes in various types of machine vision tasks. …”
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Prevalence and associated factors of mammography uptake among the women aged 45 years and above: policy implications from the longitudinal ageing study in India wave I survey by Priyanka Sharma, Dipak Das, Divya Khanna, Atul Budukh, Anita Khokhar, Satyajit Pradhan, Ajay Kumar Khanna, Pankaj Chaturvedi, Rajendra Badwe

“…A low proportion of Indian female population in reproductive age group (30–49 years) underwent breast cancer screening. The national operational framework includes mammography as one of the investigation modalities under the algorithm for early detection and management of breast cancer. …”
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AI-Guided Delineation of Gross Tumor Volume for Body Tumors: A Systematic Review by Lea Marie Pehrson, Jens Petersen, Nathalie Sarup Panduro, Carsten Ammitzbøl Lauridsen, Jonathan Frederik Carlsen, Sune Darkner, Michael Bachmann Nielsen, Silvia Ingala

“…<b>Results</b>: After screening 2430 articles, 48 were included. The pooled diagnostic performance from the use of AI algorithms across different tumors and topological areas ranged 0.62–0.92 in dice similarity coefficient (DSC) and 1.33–47.10 mm in Hausdorff distance (HD). …”
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Artificial intelligence in molecular and genomic prostate cancer diagnostics by A. O. Morozov, A. K. Bazarkin, S. V. Vovdenko, M. S. Taratkin, M. S. Balashova, D. V. Enikeev

“…They have the potential to develop artificial intelligence (AI) algorithms by processing large amounts of data and define connections between them.Objective. …”
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Enhancing Stroke Prediction with Logistic Regression and Support Vector Machine Using Oversampling Techniques by Syamsul Risal, Fajar Apriyadi, A. Sumardin, Andini Dani Achmad, Annisa Nurul Puteri

“…Simultaneously, SVM with Borderline-SMOTE may be more appropriate for resource-constrained environments.…”
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The Growing Impact of Natural Language Processing in Healthcare and Public Health by Aadit Jerfy, Owen Selden, Rajesh Balkrishnan PhD

“…Automating labor intensive and tedious tasks with language processing algorithms, using text analytics systems and machine learning to analyze social media data and extracting insights from unstructured data allows for better public sentiment analysis, enhancement of risk prediction models, improved patient communication, and informed treatment decisions. …”
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Role of Artificial Intelligence and Personalized Medicine in Enhancing HIV Management and Treatment Outcomes by Ashok Kumar Sah, Rabab H. Elshaikh, Manar G. Shalabi, Anass M. Abbas, Pranav Kumar Prabhakar, Asaad M. A. Babker, Ranjay Kumar Choudhary, Vikash Gaur, Ajab Singh Choudhary, Shagun Agarwal

“…Despite these innovations, challenges such as data privacy, algorithmic bias, and the need for clinical validation remain. …”
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