Nurse management of minor problems in primary care emergencies: a non-randomized controlled trial by Jordi Estarlich-Corominas, Neus Soler-Abril, Anna Casanellas-Chuecos, Sara Becerra-Corzo, Andrea Sofia Bianco, Pere Torán-Monserrat, Rosa García-Sierra

“…Nurse resolution capacity, after applying algorithms, offered quality care, with fewer prescriptions and good patient satisfaction without increasing the total number of consultations due to the same problem. …”
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Validation of Sea Surface Temperature From GK-2A Geostationary Satellite and Error Reduction Considering Impact of Satellite Zenith Angle by Kyung-Ae Park, Hye-Jin Woo, Stephane Saux Picart, Anne O'Carroll, Eunha Sohn, HuiTae Joo, Joon-Soo Lee, Joon-Yong Yang

“…By proposing optimal algorithms for SST retrievals from geostationary satellites, this study is anticipated to improve the monitoring of SSTs in regions covered by GK-2A. …”
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Deciphering mitochondrial dysfunction in keratoconus: Insights into ACSL4 from machine learning-based bulk and single-cell transcriptome analyses and experimental validation by Yuchen Cai, Tianyi Zhou, Xueyao Cai, Wenjun Shi, Hao Sun, Yao Fu

“…Hub genes were further screened and validated by multiple machine learning (ML) algorithms, followed by a comprehensive visualization of single-cell atlas and immune landscape. …”
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Geographic origin discrimination and quantification of phenolic compounds and moisture in Artemisia argyi folium using NIRS and chemometrics by Lifei Hu, Yifan Wang, Xin Wu, Yuanyuan Shan, Fengxiao Zhu, Fan Zhang, Qiang Yang, Mingxing Liu

“…Multivariate statistical analysis (four methods) and six machine learning algorithms were employed for origin discrimination. …”
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Exploration of common pathogenesis and candidate hub genes between HIV and monkeypox co-infection using bioinformatics and machine learning by Jialu Li, Yiwei Hao, Liang Wu, Hongyuan Liang, Liang Ni, Fang Wang, Sa Wang, Yujiao Duan, Qiuhua Xu, Jinjing Xiao, Di Yang, Guiju Gao, Yi Ding, Chengyu Gao, Jiang Xiao, Hongxin Zhao

“…After gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis and construction of protein-protein interaction (PPI) network, candidate hub genes were further screened based on machine learning algorithms. Transcriptional factors (TFs) and miRNA-candidate hub gene networks were constructed to understand regulatory mechanisms and protein-drug interactions to identify potential therapeutic drugs. …”
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Cost-of-illness of gastroenteritis caused by rotavirus in Chinese children less than 5 years by Xiao-Li Fu, Yan Ma, Zheng Li, Yang-Yang Qi, Si-Jie Wang, Li-Jun Fu, Song-Mei Wang, Lorenz von Seidlein, Xuan-Yi Wang

“…A meta-analysis was conducted applying standardized algorithms. Articles published before January 1, 2023, in English and Chinese were searched through PubMed, CNKI, and WanFang Data. …”
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Machine learning-based Diagnostic model for determining the etiology of pleural effusion using Age, ADA and LDH by Qing-Yu Chen, Shu-Min Yin, Ming-Ming Shao, Feng-Shuang Yi, Huan-Zhong Shi

“…The dataset was divided into training and test set with a ratio of 7:3 with 6 machine learning algorithms implemented to diagnosis pleural effusion. …”
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Decoding the diagnostic biomarkers of mitochondrial dysfunction related gene variants in pediatric T cell acute lymphoblastic leukemia by Yunfeng Lu, Xi Yang, Liying Liu, Xiaojun Sun, Xiuli Li, Ping Zhao, Guotao Guan, Yunpeng Dai

“…The intersection of LASSO regression and RF algorithms highlighted two pivotal genes: RNLS and ULK1. …”
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Spectroscopic photoacoustic denoising framework using hybrid analytical and data-free learning method by Fangzhou Lin, Shang Gao, Yichuan Tang, Xihan Ma, Ryo Murakami, Ziming Zhang, John D. Obayemi, Winston O. Soboyejo, Haichong K. Zhang

“…Advanced methods, including learning-based approaches and analytical algorithms, have demonstrated promise but often require extensive training data and parameter tuning. …”
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Machine learning-based prediction of scale formation in produced water as a tool for environmental monitoring by Arash Tayyebi, Ali Alshami, Erfan Tayyebi, Ademola Owoade, MusabbirJahan Talukder, Nadhem Ismail, Zeinab Rabiei, Xue Yu, Glavic Tikeri

“…We used a database comprised of 2313 quality data points from different locations in the Bakken Shale Play, including values such as ionic compositions, pH, and the saturation index of the potential mineral scales in PW at 60°F and 60 psi to train the ML algorithms and identify what scale will likely form in the PW. …”
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A Hybrid Speech Enhancement Technique Based on Discrete Wavelet Transform and Spectral Subtraction by Yasir Iqbal, Tao Zhang, Teddy Surya Gunawan, Agus Pratondo, Xin Zhao, Yanzhang Geng, Mira Kartiwi, Nasir Saleem, Sami Bourouis

“…In low Signal-to-Noise Ratio (SNR) conditions, various approaches and algorithms are applied to improve speech quality and intelligibility. …”
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ScannerVision: Scanner-based image acquisition of medically important arthropods for the development of computer vision and deep learning models by Song-Quan Ong, Nathan Pinoy, Min Hui Lim, Kim Bjerge, Francisco Javier Peris-Felipo, Rob Lind, Jordan P. Cuff, Samantha M. Cook, Toke Thomas Høye

“…In this paper, we present a high-throughput scanner-based method for capturing images of arthropods that can be used to generate large datasets suitable for training machine learning algorithms for identification. We demonstrate the ability of this approach to image arthropod samples collected with different sampling methods, such as sticky traps (unbaited, in different colors), baited mosquito traps as used by the US Centers for Disease Control and Prevention (CDC) and BioGents-Sentinel (BGS), and UV light traps with a sticky pad. …”
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Development of a deep learning system for predicting biochemical recurrence in prostate cancer by Lu Cao, Ruimin He, Ao Zhang, Lingmei Li, Wenfeng Cao, Ning Liu, Peisen Zhang

“…Finally, patient-level artificial intelligence models were developed by integrating deep learning -generated pathology features with several machine learning algorithms. Results The BCR prediction system demonstrated great performance in the testing cohort (AUC = 0.911, 95% Confidence Interval: 0.840–0.982) and showed the potential to produce favorable clinical benefits according to Decision Curve Analyses. …”
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A novel bone metastasis-related gene signature for predicting prognosis, anti-androgen resistance, and drug choice in prostate cancer by Yu Luo, Xiaoqi Deng, Chengcheng Wei, Zhangcheng Liu, Liangdong Song, Kun Han, Yunfan Li, Jindong Zhang, Shuai Su, Delin Wang

“…The immune landscape heterogeneity of subgroups was analyzed using CIBERSORT, ESTIMATE, and xCell algorithms. Drug sensitivity and molecular docking analysis were performed to identify drugs associated with BMRPS. …”
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Exploring the Current Applications and Future Implications of Artificial Intelligence in Public Health Dentistry: A Narrative Review by Tanushri Mahendra Dalvi, Rajeshri Kotwadekar, Shrivardhan R Kalghatgi, Priyanka Paul Madhu, Priyanka Methildeotare

“…AI based applications in preventive dentistry can identify high risk individuals for dental caries, periodontal infections and oral cancer to allow targeted dental care. Deep learning algorithms can also be applied in imaging diagnostics and dental care can be personalised using patient’s history, habits and genetics. …”
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Quantitative digital pathology enables automated and quantitative assessment of inflammatory activity in patients with autoimmune hepatitis by Piotr Socha, Elizabeth Shumbayawonda, Abhishek Roy, Caitlin Langford, Paul Aljabar, Malgorzata Wozniak, Sylwia Chełstowska, Elzbieta Jurkiewicz, Rajarshi Banerjee, Ken Fleming, Maciej Pronicki, Kamil Janowski, Wieslawa Grajkowska

“…We evaluated the performance of computational algorithms in the assessment of hepatic inflammation in an autoimmune hepatitis in which inflammation is a major component. …”
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Audio-based digital biomarkers in diagnosing and managing respiratory diseases: a systematic review and bibliometric analysis by Vivianne Landry, Jessica Matschek, Roger Pang, Meghana Munipalle, Kenneth Tan, Jill Boruff, Nicole Y.K. Li-Jessen

“…Future research on audio biomarkers should focus on testing their validity in clinically diverse populations and resolving algorithmic bias. If successful, digital audio biomarkers hold promise for complementing existing clinical tools in enabling more accessible applications in telemedicine, communicable disease monitoring, and chronic condition management.…”
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A machine-learning approach for predicting butyrate production by microbial consortia using metabolic network information by Claudia Silva-Andrade, Sergio Hernández, Pedro Saa, Ernesto Perez-Rueda, Daniel Garrido, Alberto J. Martin

“…The performance of the algorithms was evaluated using k-fold cross-validation and new experimental data, displaying a Pearson correlation coefficient exceeding 0.75 for the predicted and observed butyrate production in two bacteria consortia. …”
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Detecting and localizing cervical lesions in colposcopic images with deep semantic feature mining by Li Wang, Ruiyun Chen, Jingjing Weng, Huiping Li, Shi Ying, Jinghui Zhang, Zehao Yu, Chengbin Peng, Siming Zheng

“…The segmentation results were then coherently mapped back onto the original images, ensuring an integrated visualization of the findings.ResultsExperimental findings demonstrated that compared to algorithms solely based on image segmentation or classification, the proposed approach exhibited superior accuracy in distinguishing between normal and lesioned colposcopic images. …”
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Non-contact tracking of shoulder bones using ultrasound and stereophotogrammetry by Ahmed Sewify, Ahmed Sewify, Maxence Lavaill, Maxence Lavaill, Dermot O’Rourke, Dermot O’Rourke, Maria Antico, Maria Antico, Peter Pivonka, Peter Pivonka, Davide Fontanarosa, Davide Fontanarosa, Saulo Martelli, Saulo Martelli

“…The bone registration approach used was based on in silico analyses that investigated the effects of different — 1) registration algorithms (Iterative-Closest-Point–ICP, and Coherent Point Drift–CPD) and 2) initial estimate levels of the bone model pose relative to the targeted final bone pose—on the overall registration efficiency and accuracy in a controlled environment.ResultsCPD provided the highest accuracy in the simulation at the cost of 8x longer computation compared to ICP. …”
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