Mitochondrial-Localized Protein Transcript Abundance can Predict the Prognosis of Endometrial Carcinoma: A Retrospective Analysis by Weifei Liang, Hong Lin, Donglin Sun, Minghui Tang

“…Moreover, a nomogram was constructed through the combination of the scoring algorithm and the patient’s clinical features. Conclusions: The scoring algorithm based on mitochondrial gene expression can assist clinicians in predicting the postoperative survival rate of patients, allowing them to devise more precise treatment programs.…”
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A Dynamic Adaptive Ensemble Learning Framework for Noninvasive Mild Cognitive Impairment Detection: Development and Validation Study by Aoyu Li, Jingwen Li, Yishan Hu, Yan Geng, Yan Qiang, Juanjuan Zhao

“…To address the challenges (eg, the curse of dimensionality and increased model complexity) posed by high-dimensional features, we developed a dynamic adaptive feature selection optimization algorithm to identify the most impactful subset of features for classification performance. …”
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Fetal electrocardiography and artificial intelligence for prenatal detection of congenital heart disease by Ivar R. deVries, Judith O. E. H. vanLaar, Marieke B. van der Hout‐van der Jagt, Sally‐Ann B. Clur, Rik Vullings

“…More research is required to improve performance and determine the benefits to clinical practice.…”
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Predicting Affinity Through Homology (PATH): Interpretable binding affinity prediction with persistent homology. by Yuxi Long, Bruce R Donald

“…Compared to current binding affinity prediction algorithms, PATH+ shows similar or better accuracy and is more generalizable across orthogonal datasets. …”
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Integrating status-neutral and targeted HIV testing in Zimbabwe: A complementary strategy. by Hamufare D Mugauri, Owen Mugurungi, Joconiah Chirenda, Kudakwashe Takarinda, Prosper Mangwiro, Mufuta Tshimanga

“…First tests were 65% more likely to test HIV positive (a95%CI: 1.43, 1.91) whilst screened patients were 3.89 times more likely to link to HIV prevention services (a95%CI: 3.05, 4.97), against 25.5% (n = 1,871) linkage among patients not screened.…”
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Proposed Comprehensive Methodology Integrated with Explainable Artificial Intelligence for Prediction of Possible Biomarkers in Metabolomics Panel of Plasma Samples for Breast Canc... by Cemil Colak, Fatma Hilal Yagin, Abdulmohsen Algarni, Ali Algarni, Fahaid Al-Hashem, Luca Paolo Ardigò

“…The SHapley Additive Descriptions (SHAP) analysis evaluated the optimal prediction model for interpretability. <i>Results</i>: The RF algorithm showed improved accuracy (0.963 ± 0.043) and sensitivity (0.977 ± 0.051); however, LightGBM achieved the highest ROC AUC (0.983 ± 0.028). …”
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Increasing comprehensiveness and reducing workload in a systematic review of complex interventions using automated machine learning by Olalekan A Uthman, Rachel Court, Jodie Enderby, Lena Al-Khudairy, Chidozie Nduka, Hema Mistry, GJ Melendez-Torres, Sian Taylor-Phillips, Aileen Clarke

“…Background As part of our ongoing systematic review of complex interventions for the primary prevention of cardiovascular diseases, we have developed and evaluated automated machine-learning classifiers for title and abstract screening. The aim was to develop a high-performing algorithm comparable to human screening. …”
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Breast cancer detection and classification with digital breast tomosynthesis: a two-stage deep learning approach by Yazeed Alashban

“…CLINICAL SIGNIFICANCE: The proposed two-tier DL algorithm, combining a modified VGG19 model for image classification and YOLOv5-CBAM for lesion detection, can improve the accuracy, efficiency, and reliability of breast cancer screening and diagnosis through innovative artificial intelligence-driven methodologies.…”
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Cheetah optimized CNN: A bio-inspired neural network for automated diabetic retinopathy detection by V. K. U. Ahamed Gani, N. Shanmugasundaram

“…The proposed CO-CNN approach shows superior performance compared to that of state-of-the-art methods, offering potential applications in telemedicine, treatment planning, early detection, screening, and patient education. Integrating fuzzy logic enhances the model’s interpretability and robustness, paving the way for improved healthcare outcomes in diabetic retinopathy management.…”
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Naive Bayes Analysis for Nutritional Fulfillment Prediction in Children by Satrio Agung Wicaksono, Satrio Hadi Wijoyo, Fatmawati Fatmawati, Tri Afirianto, Diva Kurnianingtyas, Mochammad Chandra Saputra

“…The study’s implications are twofold: practically, the model can be integrated into health monitoring systems to assist healthcare professionals and policymakers in designing more effective nutrition programs; theoretically, it highlights the adaptability of Naive Bayes for handling complex, multi-dimensional health data. …”
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Application of artificial intelligence in the diagnosis and treatment of lacrimal disorders: challenges and opportunities by PENG Xintong, LI Guangyu

“…AI has the ability to provide more precise disease identification and treatment strategies through efficient image analysis, multimodal data fusion, and deep learning algorithms. …”
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A FixMatch Framework for Alzheimer&#x2019;s Disease Classification: Exploring the Trade-Off Between Supervision and Performance by Al Hossain, Umme Hani Konok, MD Tahsin, Raihan Ul Islam, Mohammad Rifat Ahmmad Rashid, Mohammad Shahadat Hossain, Karl Andersson

“…While experienced medical professionals can often identify AD through conventional assessment methods, limited resources and growing patient populations make large-scale and rapid screening increasingly necessary. In this work, we explore whether the FixMatch algorithm&#x2014;a semi-supervised learning approach&#x2014;can aid in classifying Alzheimer&#x2019;s Disease (AD), Mild Cognitive Impairment (MCI), and Cognitively Normal (CN) by using the ADNI fMRI dataset of 5,182 images. …”
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Factors Influencing Misinformation Propagation: A Systemic Review by HAN Xi, LIAO Ke

“…This study constructs an integrated model of the influencing factors for misinformation propagation, which can provide direction for targeted interventions and algorithm design to mitigate the spread of misinformation. …”
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Effectiveness of mindfulness-based therapy, stress reduction in hypertension and prehypertension: a systematic review by D. I. Nozdrachev, M. N. Solovieva, K. A. Zamyatin

“…The systematic review was prepared according to the PRISMA algorithm with minor modifications. The search algorithm included articles in Russian and English, indexed in the Pubmed/MEDLINE and Cochrane Library databases. …”
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Research on predicting the risk level of coal mine roof accident based on machine learning by Zhao-Yang Guan, Jin-Ling Xie, Shen-Kuang Wu, Chao Liang

“…Finally, KNN, SVM and DT algorithms are used to evaluate the model performance. …”
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Implementation costs and cost-effectiveness of ultraportable chest X-ray with artificial intelligence in active case finding for tuberculosis in Nigeria. by Tushar Garg, Stephen John, Suraj Abdulkarim, Adamu D Ahmed, Beatrice Kirubi, Md Toufiq Rahman, Emperor Ubochioma, Jacob Creswell

“…We provide implementation cost and cost-effectiveness estimates of different screening algorithms using symptoms, CXR and AI in Nigeria. …”
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Enhancing glaucoma diagnosis: Generative adversarial networks in synthesized imagery and classification with pretrained MobileNetV2 by I. Govindharaj, D. Santhakumar, K. Pugazharasi, S. Ravichandran, R. Vijaya Prabhu, J. Raja

“…This approach does not only contribute to glaucoma screening but also can also reveal the benefits of the GANs and transfer learning in medical imaging. • A GAN approach to generate high-quality fundus image datasets in an attempt to minimize dataset differences. • Implemented improved Enhanced Level Set Algorithm for Optic Cup segmentation. • Built on top of the pretrained MobileNetV2 to obtain better results of glaucoma classification.…”
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Multi-Class Classification Using Improved Mahalanobis-Taguchi System Based on Binary Tree and Its Application by Niu Junlei

“…Aiming at the inadequacy of Mahalanobis-Taguchi System(MTS), an improved MTS optimization model(MTSO) is proposed. The core idea is that a number of optimization objectives are proposed based on the purpose and characteristics of the data classification problem and optimization model is used for screening important variables instead of orthogonal arrays and signal-noise-ratio. …”
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Iterative phase contrast CT reconstruction with novel tomographic operator and data-driven prior. by Stefano van Gogh, Subhadip Mukherjee, Jinqiu Xu, Zhentian Wang, Michał Rawlik, Zsuzsanna Varga, Rima Alaifari, Carola-Bibiane Schönlieb, Marco Stampanoni

“…Moreover, the highly ill-conditioned differential nature of the GI-CT forward operator renders the inversion from corrupted data even more cumbersome. In this paper, we propose a novel regularized iterative reconstruction algorithm with an improved tomographic operator and a powerful data-driven regularizer to tackle this challenging inverse problem. …”
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A statistical method for high-throughput emergence rate calculation for soybean breeding plots based on field phenotypic characteristics by Yan Sun, Mengqi Li, Meiling Liu, Jingyi Zhang, Yingli Cao, Xue Ao

“…Then, a soybean seedling counting algorithm was constructed: by establishing a soybean seedling growth model, the idea of “growth normalization” was proposed, and the expansion-compression factor was defined to eliminate the influence of soybean seedling growth inconsistency on counting. …”
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