ϵ-Confidence Approximately Correct (ϵ-CoAC) Learnability and Hyperparameter Selection in Linear Regression Modeling by Soosan Beheshti, Mahdi Shamsi

“…Linear regression modeling is an important category of learning algorithms. The practical uncertainty of the label samples in the training data set has a major effect in the generalization ability of the learned model. …”
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Exposure patterns and the risk factors of Crimean Congo hemorrhagic fever virus amongst humans, livestock and selected wild animals at the human/livestock/wildlife interface in Isi... by Eugine Mukhaye, James M Akoko, Richard Nyamota, Athman Mwatondo, Mathew Muturi, Daniel Nthiwa, Lynn J Kirwa, Joel L Bargul, Hussein M Abkallo, Bernard Bett

“…For instance, the existing CCHF surveillance measures could be enhanced by incorporating algorithms that simulate disease risk based on the environmental factors identified in the study. …”
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Risk Factors for Gout in Taiwan Biobank: A Machine Learning Approach by Liu YR, Nfor ON, Zhong JH, Lin CY, Liaw YP

“…Both the RF and GB demonstrated high performance across multiple metrics, with RF consistently achieving a high area under the curve (AUC) of 0.986 to 0.987, alongside excellent sensitivity (0.945– 0.947) and specificity (0.998– 0.999). GB also performed robustly, with AUC values around 0.987– 0.988 and maintaining high sensitivity (0.944– 0.950) and specificity (0.995– 0.999) across different model variations. …”
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The Use of Machine Learning for Analyzing Real-World Data in Disease Prediction and Management: Systematic Review by Norah Hamad Alhumaidi, Doni Dermawan, Hanin Farhana Kamaruzaman, Nasser Alotaiq

“…The search focused on extracting data regarding the ML algorithms applied; disease categories studied; types of study designs (eg, clinical trials and cohort studies); and the sources of RWE, including EHRs, patient registries, and wearable devices. …”
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Construction and Validation of a Machine Learning-Based Risk Prediction Model for Sleep Quality in Patients with OSA by Tong Y, Wen K, Li E, Ai F, Tang P, Wen H, Guo B

“…This study not only deepens understanding of the factors affecting sleep quality in OSA patients, but also provides a powerful predictive tool for clinical doctors. …”
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The underlying molecular mechanisms and biomarkers of Hip fracture combined with deep vein thrombosis based on self sequencing bioinformatics analysis by Guanghua Shi, Xiaocui Shi, Meng Zhang, Rui Cheng, Mengqing Hu, Yu Zhao, Shimei Li, Xiuxiu Li, Haiyun Ma, Pengcui Li

“…Feature genes were further refined by intersecting results from three machine learning algorithms and constructing an artificial neural network (ANN). …”
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Tumor tissue-of-origin classification using miRNA-mRNA-lncRNA interaction networks and machine learning methods by Ankita Lawarde, Ankita Lawarde, Masuma Khatun, Prakash Lingasamy, Prakash Lingasamy, Andres Salumets, Andres Salumets, Andres Salumets, Vijayachitra Modhukur, Vijayachitra Modhukur

“…Furthermore, in silico validation revealed that many of the top miRNAs, including miR-21-5p, miR-93-5p, and miR-10b-5p, were not only highly central in the network but also correlated with patient survival and drug response. …”
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A machine learning model for predicting obesity risk in patients with diabetes mellitus: analysis of NHANES 2007–2018 by Wenqiang Wang, Ruiqing Mo, Xingyu Chen, Sijie Yang

“…Subsequently, nine machine learning algorithms—including logistic regression, random forest (RF), radial support vector machine (RSVM), k-nearest neighbors (KNN), XGBoost, LightGBM, decision tree (DT), elastic net regression (ENet), and multilayer perceptron (MLP)—were employed to construct predictive models. …”
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Peripherex Home Visual Field Demonstrates High Test-Retest Reliability, Validity by Schweitzer J, Ibach M, Berdahl J, Daoud M, Daoud YA, Kempinski Y, Goldberg JL

“…PRX-VFT represents an opportunity for enhancing patient care at minimal additional equipment cost to the patient or healthcare system.Plain Language Summary: The Peripherex Visual Field Test (PRX VFT) uses a patient’s home computer or laptop with built-in eye tracking and patented algorithms. For this study, the PRX VFT was tested in the real-world, in-home setting, compared to in-office Humphrey visual field tests. …”
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UBE2N as a novel prognostic and therapeutic biomarker of lung adenocarcinoma by Haofeng Yin, Yibo Xue, Chen Wang, Yanqin Wu, Yuchen Guo, Chunzhen Li, Yunyan Zhang, Shulei Yin, Tiejun Zhao

“…The role of UBE2N in predicting tumor therapeutic susceptibility was characterized using bioinformatics algorithms combined with publicly available CRISPR screening datasets and immunotherapy cohorts. …”
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The curvilinear associations between Life’s Crucial 9 and frailty: cross-sectional study of NHANES 2003 - 2023 by Bo Wang, Chunqi Jiang, Ning Wang, Yinuo Qu, Jun Wang, Guang Zhao, Xin Zhang, Xin Zhang

“…BackgroundFrailty not only affects disease survival rates but also the quality of life. The Life’s Crucial 9 (LC9) is a recently proposed cardiovascular health risk score that incorporates mental health along with Life’s Essential 8 (LE8). …”
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DYNAMICS OF MMP-8, SRANKL, AND OSTEOCALCIN CONCENTRATIONS IN THE ORAL FLUID OF PATIENTS WITH SECONDARY EDENTULISM AND AFTER PROSTHETIC TREATMENT by R.V. Tsynkush, O.V. Voznyi

“…The presence of strong correlations was also confirmed: positive between MMP-8 and sRANKL and negative between these markers and osteocalcin. …”
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Novel exosome-associated LncRNA model predicts colorectal cancer prognosis and drug response by Chi Zhou, Qian Qiu, Xinyu Liu, Tiantian Zhang, Leilei Liang, Yihang Yuan, Yufo Chen, Weijie Sun

“…Knocking down the expression of MIR4713HG significantly inhibited proliferation and migration, and also impaired subcutaneous tumor growth in nude mice. …”
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Leveraging Spectral Neighborhood Information for Corn Yield Prediction with Spatial-Lagged Machine Learning Modeling: Can Neighborhood Information Outperform Vegetation Indices? by Efrain Noa-Yarasca, Javier M. Osorio Leyton, Chad B. Hajda, Kabindra Adhikari, Douglas R. Smith

“…Accurate and reliable crop yield prediction is essential for optimizing agricultural management, resource allocation, and decision-making, while also supporting farmers and stakeholders in adapting to climate change and increasing global demand. …”
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Using Video Cameras to Assess Physical Activity and Other Well-Being Behaviors in Urban Environments: Feasibility, Reliability, and Participant Reactivity Studies by Jack S Benton, James Evans, Jamie Anderson, David P French

“…This research is a significant first step in demonstrating the potential for camera-based methods to improve natural experimental studies of real-world environmental interventions. It also provides a rigorous foundation for developing more scalable automated computer vision algorithms for assessing human behaviors.…”
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Remote sensing reveals the role of forage quality and quantity for summer habitat use in red deer by Thomas Rempfler, Christian Rossi, Jan Schweizer, Wibke Peters, Claudio Signer, Flurin Filli, Hannes Jenny, Klaus Hackländer, Sven Buchmann, Pia Anderwald

“…Abstract Background The habitat use of wild ungulates is determined by forage availability, but also the avoidance of predation and human disturbance. …”
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Widespread use of ChatGPT and other Artificial Intelligence tools among medical students in Uganda: A cross-sectional study. by Elizabeth Ajalo, David Mukunya, Ritah Nantale, Frank Kayemba, Kennedy Pangholi, Jonathan Babuya, Suzan Langoya Akuu, Amelia Margaret Namiiro, Yakobo Baddokwaya Nsubuga, Joseph Luwaga Mpagi, Milton W Musaba, Faith Oguttu, Job Kuteesa, Aloysius Gonzaga Mubuuke, Ian Guyton Munabi, Sarah Kiguli

“…<h4>Background</h4>Chat Generative Pre-trained Transformer (ChatGPT) is a 175-billion-parameter natural language processing model that uses deep learning algorithms trained on vast amounts of data to generate human-like texts such as essays. …”
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Aneuploidy screening in women of advanced age in the public healthcare setting of a low- to middle- income country – an observational cohort study by L Geerts, N Du Toit, M Schoeman

“…Screening was age- and ultrasound-based, and DS risks were calculated using published algorithms. Non-directive genetic counselling was provided to all women ≥40 years old (pre-screen if feasible), women with a relevant history, a fetal anomaly or DS risk higher than that of a woman aged 37 years. …”
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Development of a Cohesive Predictive Model for Substance Use Disorder Rehabilitation Using Passive Digital Biomarkers, Psychological Assessments, and Automated Facial Emotion Recog... by Andrea P Garzón-Partida, Kimberly Magaña-Plascencia, Diana Emilia Martínez-Fernández, Joaquín García-Estrada, Sonia Luquin, David Fernández-Quezada

“…The collected data will then be used to train models with a neural network, which will then be validated against other models and compared with other algorithms. Demographic, psychological, digital biomarkers, and craving profiles will be created, correlations will be analyzed, and they will be compared with controls to generate a digital phenotype of SUD. …”
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FROM FARCE TO HYPE (ISSUES OF MODERN INTERNET COMMUNICATION) / ОТ БАЛАГАНА ДО ХАЙПА (ПРОБЛЕМЫ СОВРЕМЕННОЙ ИНТЕРНЕТ-КОММУНИКАЦИИ)... by SЕMЕNОVА ELENA А. / СЕМЕНОВА Е.А.

“…The author draws attention to the fact that not only young people born in the 1990s and the 2000s, but also the older generation of adults born in the 1960s, do not always distinguish Internet humor from live laughter and carnival communication. …”
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