Using Digital Technology to Conduct COVID-19 Surveillance: A Systematic Review by Fitrisia Rahma, Fatmah Fatmah, Rachmadhi Purwana

“…Unique Contribution: This study emphasises the role of digital technologies in virus detection, monitoring, and prevention as a medium of infectious disease transmission, particularly in contact tracing, symptom monitoring, location tracking, and real-time data management. …”
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Thyroid nodule classification in ultrasound imaging using deep transfer learning by Yan Xu, Mingmin Xu, Zhe Geng, Jie Liu, Bin Meng

“…In this study, we investigate the predictive efficacy of distinguishing between benign and malignant thyroid nodules by employing traditional machine learning algorithms and a deep transfer learning model, aiming to advance the diagnostic paradigm in this field. …”
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Transferring Learned ECG Representations for Deep Neural Network Classification of Atrial Fibrillation with Photoplethysmography by Jayroop Ramesh, Zahra Solatidehkordi, Raafat Aburukba, Assim Sagahyroon, Fadi Aloul

“…However, the scarcity of large-scale public PPG datasets acquired from wearable devices hinders the development of intelligent automatic AF detection algorithms unaffected by motion artifacts, saturated ambient noise, inter- and intra-subject differences, or limited training data. …”
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Exploring the role of hepsin in prostate cancer: bioinformatics, molecular Docking and molecular dynamics simulations by Hongying Peng, Dan Du, Zhonggui Hu, Zhiliang Xia

“…Although significant advances have been made in early detection, therapeutic strategies for advanced and metastatic PCa remain limited. …”
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Classification of intracranial tumors based on optical-spectral analysis by I. D. Romanishkin, T. A. Savelieva, A. Ospanov, K. G. Linkov, S. V. Shugai, S. A. Goryajnov, G. V. Pavlova, I. N. Pronin, V. B. Loschenov

“…In case the number of parameters exceeds a couple of dozens, it is necessary to use machine learning algorithms  to build a intraoperative decision support system for the surgeon. …”
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Diagnosis and Management of Alzheimer’s Disease in Primary Care: A Real-World Study in Ontario, Canada by Zahinoor Ismail, Melanie Wilson, Hany Khalifa, Daniela Belovich, Eileen Shaw, Tram Pham, Suzanne McMullen, Yuhao Chen, Nafiz Sadman, Jackson Cai, Farhana Zulkernine, David Barber

“…Individuals ≥50 years old with dementia or AD were identified using AD and dementia-related diagnostic codes, medications, and keywords searched using natural language processing (NLP) and Artificial Intelligence (AI) algorithms from EMR chart notes. Diagnostic and screening tools included scales, neuroimaging, and laboratory tests. …”
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Single-Image Superresolution for RGB Remote Sensing Imagery via Multiscale CNN-Transformer Feature Fusion by Xudong Yao, Haopeng Zhang, Sizhe Wen, Zhenwei Shi, Zhiguo Jiang

“…Single-image superresolution (SISR) of remote sensing images aims to improve image resolution through algorithmic means while restoring rich high-frequency detailed information. …”
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Exploring Transfer Learning for Anthropogenic Geomorphic Feature Extraction from Land Surface Parameters Using UNet by Aaron E. Maxwell, Sarah Farhadpour, Muhammad Ali

“…Semantic segmentation algorithms, such as UNet, that rely on convolutional neural network (CNN)-based architectures, due to their ability to capture local textures and spatial context, have shown promise for anthropogenic geomorphic feature extraction when using land surface parameters (LSPs) derived from digital terrain models (DTMs) as input predictor variables. …”
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Amyloid Cardiomyopathy: Review of A Fatal Case Report by O. V. Soldatova, I. Ya. Goryanskaya

“…Close attention to the problem of amyloid cardiomyopathy in recent years has been caused by a significant increase in the disease detection simultaneously with increased sensitivity and specificity of imaging methods used in cardiological practice, along with the emergence of new promising diagnostic methods and specific therapy. …”
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Quantifying leaf symptoms of sorghum charcoal rot in images of field‐grown plants using deep neural networks by Emmanuel M. Gonzalez, Ariyan Zarei, Sebastian Calleja, Clay Christenson, Bruno Rozzi, Jeffrey Demieville, Jiahuai Hu, Andrea L. Eveland, Brian Dilkes, Kobus Barnard, Eric Lyons, Duke Pauli

“…The objective of this work was to implement various machine learning algorithms to evaluate their ability to accurately detect and quantify CRS in red‐green‐blue images of sorghum plants exhibiting symptoms of infection. …”
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Optical Remote Sensing for Global Flood Disaster Mapping: A Critical Review Towards Operational Readiness by Molan Zhang, Zhiqiang Chen, Jun Wang, Bandana Kar, Marlon Pierce, Kristy Tiampo, Ronald Eguchi, Margaret Glasscoe

“…We will cross-verify traditional machine learning and current deep learning methods and provide both benchmark databases and algorithms for the research community. Last, with this suite of data and algorithms, we will demonstrate the development of a cloud-computing-supported computing gateway, which houses the services of both our remote-sensing-based machine learning engine and a web-based user interface. …”
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Machine learning with the body roundness index and associated indicators: a new approach to predicting metabolic syndrome by Yaxuan He, Zekai Chen, Zhaohui Tang, Yuexiang Qin, Fang Wang

“…Developing a non-invasive, accurate prediction model is clinically significant for early MetS detection and prevention. Objective To develop a non-invasive prediction model for MetS by integrating body roundness index (BRI), gender, age, height, and waist circumference with machine learning algorithms, and to validate its generalizability across different ethnic groups. …”
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Comparison of safety of lecanemab and aducanumab: a real-world disproportionality analysis using the FDA adverse event reporting system by Lingti Kong, Lingti Kong, Lingti Kong, Xiaohu Yang, Xiaohu Yang, Jian Xu, Jian Xu

“…Four positive signal detection algorithms were used, namely, the Ratio-to-Ratio (ROR), proportional reporting ratio (PRR), multi item gamma poisson shrinker (MGPS), and bayesian belief propagation neural network (BCPNN). …”
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Construction of a feature gene and machine prediction model for inflammatory bowel disease based on multichip joint analysis by Yan Chaosheng, Sun Haowen, Rao Jingjing, Dai Yuanyuan, Duan Wenhui, Sheng Yingyue, Xue Yuzheng

“…Our findings suggest that machine learning algorithms outperform ANNs in the diagnosis of IBD. …”
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Artificial intelligence-aided endoscopic in-line particle size analysis during the pellet layering process by Orsolya Péterfi, Nikolett Kállai-Szabó, Kincső Renáta Demeter, Ádám Tibor Barna, István Antal, Edina Szabó, Emese Sipos, Zsombor Kristóf Nagy, Dorián László Galata

“…A convolutional neural network-based instance segmentation algorithm was employed to detect particles in focus, ensuring that pellet size could be accurately determined despite the dense flow of the particles. …”
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Ultrasound-based machine learning model to predict the risk of endometrial cancer among postmenopausal women by Yi-Xin Li, Yu Lu, Zhe-Ming Song, Yu-Ting Shen, Wen Lu, Min Ren

“…Three models were developed: (1) R model: radiomics-based machine learning (ML) algorithms; (2) CNN model: image-based CNN algorithms; (3) DLR model: a hybrid model combining radiomics and deep learning features with ML algorithms. …”
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Classification of ROI-based fMRI data in short-term memory tasks using discriminant analysis and neural networks by Magdalena Fafrowicz, Marcin Tutajewski, Igor Sieradzki, Jeremi K. Ochab, Jeremi K. Ochab, Anna Ceglarek-Sroka, Koryna Lewandowska, Tadeusz Marek, Barbara Sikora-Wachowicz, Igor T. Podolak, Paweł Oświęcimka, Paweł Oświęcimka, Paweł Oświęcimka

“…The presented results reveal the benefits of applying machine learning algorithms to investigate working memory dynamics.…”
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Point-of-Care Ultrasound Pulse Checks During Cardiopulmonary Resuscitation on a Patient Simulator (PUPRAS) by Susanne Betz, Harald Bergmann, Franz Rettich, Julian Kreutz, Birgit Ploeger, Christoph W. Jaenig, Stephan Grosch, Karl M. Meggiolaro, Andreas Jerrentrup, Willi Schmidbauer, Bernhard Schieffer, Tobias Gruebl

“…Point-of-care ultrasound (POCUS) may be more reliable for detecting the ROSC. We investigated whether a POCUS pulse check algorithm could be used in compliance with the CPR guidelines. …”
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Non-stereotypy (to species) in mysticete downsweeps by Paul Nguyen Hong Duc, Christine Erbe, Shyam Madhusudhana, Daniel Wilkes, Lachlan Gill, Cristina Tollefsen, Narissa de Bruin, Aiyana Erbeking, Curt Jenner, Micheline Jenner, Angela Recalde-Salas, Chandra P. Salgado Kent, Chandra P. Salgado Kent, Kautilya Srivastava, Kautilya Srivastava, Chong Wei, Robert McCauley

“…Challenges in automated detection, variability in environmental noise, and human biases in manual classification were acknowledged. …”
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Deep learning in microbiome analysis: a comprehensive review of neural network models by Piotr Przymus, Krzysztof Rykaczewski, Adrián Martín-Segura, Jaak Truu, Enrique Carrillo De Santa Pau, Mikhail Kolev, Mikhail Kolev, Irina Naskinova, Aleksandra Gruca, Alexia Sampri, Alexia Sampri, Marcus Frohme, Alina Nechyporenko, Alina Nechyporenko

“…By automating the detection of functional genes, microbial interactions, and host-microbiome dynamics, DL methods offer unprecedented precision in understanding microbiome composition and its impact on health, disease, and the environment. …”
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