Machine learning based screening of biomarkers associated with cell death and immunosuppression of multiple life stages sepsis populations by Jie Yang, Fanyan Ou, Binbin Li, Lixiong Zeng, Qiuli Chen, Houyu Gan, Jianing Yu, Qian Guo, Jihua Feng, Jianfeng Zhang

“…Nine machine learning algorithms (Logistic Regression LR, Decision Tree DT, Gradient Boosting Machine GBM, K-Nearest Neighbors KNN, LASSO, Principal Component Analysis PCA, Random Forest RF, Support Vector Machine SVM, and XGBoost) were applied to training and testing datasets with 10-fold cross-validation to select three optimized algorithm models. …”
Get full text

Advancing Diabetic Retinopathy Screening: A Systematic Review of Artificial Intelligence and Optical Coherence Tomography Angiography Innovations by Alireza Hayati, Mohammad Reza Abdol Homayuni, Reza Sadeghi, Hassan Asadigandomani, Mohammad Dashtkoohi, Sajad Eslami, Mohammad Soleimani

“…In comparison to conventional ML techniques, our results indicated that DL algorithms significantly improve the accuracy, sensitivity, and specificity of DR screening. …”
Get full text

Screening and Validation of Potential Biomarkers of Immune Cells in Childhood Asthma Patients via Mendelian Randomization and Machine Learning by Zhang Y, Hai Y, Song B, Xu J, Cao L, Yasen R, Xu W, Zhang J, Hu J

Get full text

Optimizing diabetic retinopathy detection with electric fish algorithm and bilinear convolutional networks by Udayaraju Pamula, Venkateswararao Pulipati, G. Vijaya Suresh, M. V. Jagannatha Reddy, Anil Kumar Bondala, Srihari Varma Mantena, Ramesh Vatambeti

“…Abstract Diabetic Retinopathy (DR) is a leading cause of vision impairment globally, necessitating regular screenings to prevent its progression to severe stages. …”
Get full text

Artificial intelligence in the service of entrepreneurial finance: knowledge structure and the foundational algorithmic paradigm by Robert Kudelić, Tamara Šmaguc, Sherry Robinson

“…A rigorous search and screening of the web of science core collection identified 1,890 journal articles for analysis. …”
Get full text

HMCFormer (hierarchical multi-scale convolutional transformer): a hybrid CNN+Transformer network for intelligent VIA screening by Bo Feng, Chao Xu, Zhengping Li, Chuanyi Zhang

“…On this dataset, the proposed algorithm achieves a screening accuracy of 97.4% and a grading accuracy of 94.8%.…”
Get full text

Validation of an Eye-Tracking Algorithm Based on Smartphone Videos: A Pilot Study by Wanzi Su, Damon Hoad, Leandro Pecchia, Davide Piaggio

“…<b>Methods:</b> The investigation primarily focused on comparing two algorithms, which were named CHT_TM and CHT_ACM, abbreviated from the core functions: Circular Hough Transform (CHT), Active Contour Models (ACMs), and Template Matching (TM). …”
Get full text

Screening colorectal cancer associated autoantigens through multi-omics analysis and diagnostic performance evaluation of corresponding autoantibodies by Zan Qiu, Yifan Cheng, Haiyan Liu, Tiandong Li, Yinan Jiang, Yin Lu, Donglin Jiang, Xiaoyue Zhang, Xinwei Wang, Zirui Kang, Lei Peng, Keyan Wang, Liping Dai, Hua Ye, Peng Wang, Jianxiang Shi

“…Ten machine learning algorithms were utilized to develop diagnostic models, with the optimal one selected and integrated into an R Shiny-based GUI to enhance usability and accessibility. …”
Get full text

Artificial intelligence-enabled non-invasive ubiquitous anemia screening: The HEMO-AI pilot study on pediatric population by Daniel Gordon, Jason Hoffman, Keren Gamrasni, Yotam Barlev, Alex Levine, Tamar Landau, Ronen Shpiegel, Avishai Lahad, Ariel Koren, Carina Levin, Osnat Naor, Hannah Lee, Xin Liu, Shwetak Patel, Gilad Chayen, Michael Brandwein

“…Results 823 samples, 531 from a 12.2 megapixel camera and 256 from a 12.2 megapixel camera, were collected. 26 samples were excluded by the study coordinator for irregularities. 97% of fingernails and 68% of skin samples were successfully identified by a post-trained machine learning model. Separate models built to detect anemia using images taken from the Pixel 3 had an average precision of 0.64 and an average recall of 0.4, whereas models built using the Pixel 6 had an average precision of 0.8 and an average recall of 0.84. …”
Get full text

Cervical cancer screening uptake and its associated factor in Sub-Sharan Africa: a machine learning approach by Fetlework Gubena Arage, Zinabu Bekele Tadese, Eliyas Addisu Taye, Tigist Kifle Tsegaw, Tsegasilassie Gebremariam Abate, Eyob Akalewold Alemu

“…These algorithms were employed to predict cervical cancer screening uptake. …”
Get full text

Applications of digital health technologies and artificial intelligence algorithms in COPD: systematic review by Zhenli Chen, Jie Hao, Haixia Sun, Min Li, Yuan Zhang, Qing Qian

“…Future research should focus on enhancing global collaboration to explore the cost-effectiveness and data-sharing capabilities of DHTs, enhancing the interpretability of AI models, and validating these algorithms through clinical trials to facilitate their safe integration into the routine COPD management.…”
Get full text

Diagnostic accuracy of artificial intelligence for the screening of prostate cancer in biparametric magnetic resonance imaging: a systematic review by Oksana V. Kryuchkova, Elena V. Schepkina, Natalia A. Rubtsova, Boris Y. Alekseev, Anton I. Kuznetsov, Svetlana V. Epifanova, Elena V. Zarya, Ali E. Talyshinskii

Get full text

Development and validation of prediction algorithm to identify tuberculosis in two large California health systems by Heidi Fischer, Lei Qian, Zhuoxin Li, Katia Bruxvoort, Jacek Skarbinski, Yuching Ni, Jennifer H. Ku, Bruno Lewin, Saadiq Garba, Parag Mahale, Sally F. Shaw, Brigitte Spence, Sara Y. Tartof

Get full text

An improved algorithm of segmented orthogonal matching pursuit based on wireless sensor networks by Xinmiao Lu, Yanwen Su, Qiong Wu, Yuhan Wei, Jiaxu Wang

“…Aiming at the problems of low data reconstruction accuracy in wireless sensor networks and users unable to receive accurate original signals, improvements are made on the basis of the stagewise orthogonal matching pursuit algorithm, combined with sparseness adaptation and the pre-selection strategy, which proposes a sparsity adaptive pre-selected stagewise orthogonal matching pursuit algorithm. …”
Get full text

Host Circulating Immunometabolism-Associated Biomarkers for Early Diagnosis of Active Tuberculosis: Multi-Omics Screening with Experimental Validation by Yang Z, Dong Y, Shang Y, Li H, Ren W, Li S, Pang Y

Get full text

Assessment of enthesitis in patients with psoriasis: Relationships with clinical features, screening questionnaries results, and quality of life: An ultrasound study by Dulović Dragan, Rančić Nemanja, Božić Ksenija, Stamatović Ratko, Mijušković Željko, Pešić Jasna, Kremić Zorana, Vojinović Radiša, Petronijević Milan

“…Ultrasound (US) expanding use with the development of accurate assessments through standardized US algorithms as the Glasgow Ultrasound Enthesis Scoring System (GUESS) and the Madrid Sonographic Enthesitis Index Scoring System (MASEI) scores made the US the dominant imaging technique in diagnosing enthesitis. …”
Get full text

Diagnosis of bipolar disorder based on extracted significant biomarkers using bioinformatics and machine learning algorithms by Hamid Mohseni, Massoud Sokouti, Akram Nezhadi, Ali Sayadi

“…Conclusion. We presented two models to diagnose bipolar disorder. One model was developed using artificial neural network and tanh functions and the other model was developed using decision tree algorithm. …”
Get full text

Fault detection algorithm for underground conveyor belt deviation based on improved RT-DETR by AN Longhui, WANG Manli, ZHANG Changsen

“…Three improvements were made to the RT-DETR backbone network: ① To reduce the number of parameters and floating-point operations (FLOPs), FasterNet Block was used to replace the BasicBlock in ResNet34. ② To enhance model accuracy and efficiency, the concept of structural reparameterization was introduced into the FasterNet Block structure. ③ To improve the feature extraction capability of FasterNet Block, an efficient multi-scale attention (EMA) Module was incorporated to capture both global and local feature maps more effectively. …”
Get full text

Automatic screening for posttraumatic stress disorder in early adolescents following the Ya’an earthquake using text mining techniques by Yuzhuo Yuan, Yuzhuo Yuan, Zhiyuan Liu, Wei Miao, Xuetao Tian

“…Meanwhile, participants completed the PTSD Checklist for DSM-5 (PCL-5). Text classification models were constructed using three supervised learning algorithms (BERT, SVM, and KNN) to identify PTSD symptoms and their corresponding behavioral indicators in each sentence of the self-narratives.ResultsThe prediction accuracy for symptom-level classification reached 73.2%, and 67.2% for behavioral indicator classification, with the BERT performing the best.ConclusionsThese findings demonstrate that self-narratives combined with text mining techniques provide a promising approach for automated, rapid, and accurate PTSD screening. …”
Get full text

Automated Cervical Cancer Screening Using Single-Cell Segmentation and Deep Learning: Enhanced Performance with Liquid-Based Cytology by Mariangel Rodríguez, Claudio Córdova, Isabel Benjumeda, Sebastián San Martín

“…A novel image segmentation algorithm was employed to extract single-cell patches for training a ResNet-50 model. …”
Get full text