Optimized Bayesian regularization-back propagation neural network using data-driven intrusion detection system in Internet of Things حسب Ashok Kumar K (21441108)

الموضوعات:

Calibration plot of the apparent and optimism-corrected models. حسب Dominika Szabo (14129304)

Event-driven data flow processing. حسب Yixian Wen (12201388)

"…Subsequently, we implement an optimal binary tree decision-making algorithm, grounded in dynamic programming, to achieve precise allocation of elastic resources within data streams, significantly bolstering resource utilization. …"

UK Biobank data wrangling statistics and results. حسب Simeone Marino (81051)

Flow diagram of the proposed model. حسب Uğur Ejder (22683228)

"…<div><p>Machine learning models are increasingly applied to assisted reproductive technologies (ART), yet most studies rely on conventional algorithms with limited optimization. This proof-of-concept study investigates whether a hybrid Logistic Regression–Artificial Bee Colony (LR–ABC) framework can enhance predictive performance in in vitro fertilization (IVF) outcomes while producing interpretable, hypothesis-driven associations with nutritional and pharmaceutical supplement use. …"

<b>Spatial modeling of gully density on the Qinghai-Tibet Plateau: Application of hyperparameter optimization in interpretable machine learning</b> حسب Zhoujiang Liu (22741966)

Experimental observation of gastruloids and shape quantification using LOCO-EFA. حسب Martijn A. de Jong (17896732)

Data_Sheet_1_A Data-Driven Framework for Identifying Intensive Care Unit Admissions Colonized With Multidrug-Resistant Organisms.docx حسب Çaǧlar Çaǧlayan (12253934)

"…</p>Materials and Methods<p>Leveraging data from electronic healthcare records and a unique MDRO universal screening program, we developed a data-driven modeling framework to predict MRSA, VRE, and CRE colonization upon intensive care unit (ICU) admission, and identified the associated socio-demographic and clinical factors using logistic regression (LR), random forest (RF), and XGBoost algorithms. …"

Confusion matrix. حسب Yixian Wen (12201388)

"…Subsequently, we implement an optimal binary tree decision-making algorithm, grounded in dynamic programming, to achieve precise allocation of elastic resources within data streams, significantly bolstering resource utilization. …"

Parameter settings. حسب Yixian Wen (12201388)

"…Subsequently, we implement an optimal binary tree decision-making algorithm, grounded in dynamic programming, to achieve precise allocation of elastic resources within data streams, significantly bolstering resource utilization. …"

Dynamic resource allocation process. حسب Yixian Wen (12201388)

"…Subsequently, we implement an optimal binary tree decision-making algorithm, grounded in dynamic programming, to achieve precise allocation of elastic resources within data streams, significantly bolstering resource utilization. …"

Thesis-RAMIS-Figs_Slides حسب Felipe Santibañez-Leal (10967991)

"…In this direction, the option of estimating the statistics of the model directly from the training image (performing a refined pattern search instead of simulating data) is a very promising.<br><br>Finally, although the developed concepts, ideas and algorithms have been developed for inverse problems in geostatistics, the results are applicable to a wide range of disciplines where similar sampling problems need to be faced, included but not limited to design of communication networks, optimal integration and communication of swarms of robots and drones, remote sensing.…"

Table_1_Enriching the Study Population for Ischemic Stroke Therapeutic Trials Using a Machine Learning Algorithm.pdf حسب Jenish Maharjan (11998331)

"…Patient data were extracted from electronic health records and used to train and test a gradient boosted machine learning algorithm (MLA) to predict the patients' risk of experiencing ischemic stroke from the period of 1 day up to 1 year following the patient encounter. …"

Image_1_Enriching the Study Population for Ischemic Stroke Therapeutic Trials Using a Machine Learning Algorithm.pdf حسب Jenish Maharjan (11998331)

"…Patient data were extracted from electronic health records and used to train and test a gradient boosted machine learning algorithm (MLA) to predict the patients' risk of experiencing ischemic stroke from the period of 1 day up to 1 year following the patient encounter. …"

Image 1_A multimodal AI-driven framework for cardiovascular screening and risk assessment in diverse athletic populations: innovations in sports cardiology.png حسب Minjin Guo (22751300)

"…RSEE projects heterogeneous input data into an exertion-conditioned latent space, aligning model predictions with observed physiological variance and mitigating false positives by explicitly modeling the overlap between athletic remodeling and subclinical pathology.…"

Supplementary Material for: The Therapeutic Evaluation of Steroids in IgA Nephropathy Global (TESTING) Study: Trial Design and Baseline Characteristics حسب Wong M.G. (11640685)

"…The Therapeutic Evaluation of STeroids in IgA Nephropathy Global (TESTING) study was designed to assess the benefits and risks of steroids in people with IgAN. …"

<b>A Primary Care Guide to the Screening and Pharmacologic Management of Chronic Kidney Disease in People Living With Type 2 Diabetes</b> حسب Eugene E. Wright (21500539)

"…<p dir="ltr">This paper reports the expert opinions and recommendations made by primary care physicians (PCPs) to optimize screening and management of chronic kidney disease (CKD) associated with diabetes and presents algorithms to provide a practical and simplified guide for PCPs. …"

Assessing individual genetic susceptibility to metabolic syndrome: interpretable machine learning method حسب Tao Huang (110613)

"…The XGBoost-based SHAP algorithm not only elucidated the global effects of 17 SNPs across all samples, but also described the interaction between SNPs, providing a visual representation of how SNPs impact the prediction of MetS in an individual. …"

Table_1_A Phenotyping of Diastolic Function by Machine Learning Improves Prediction of Clinical Outcomes in Heart Failure.DOCX حسب Haruka Kameshima (11870333)

"…During a mean follow-up period of 2.6 ± 2.0 years, 62 patients (22%) experienced the primary endpoint. Cluster-based classification predicted events with a hazard ratio 1.68 (p = 0.019) that was independent from and incremental to the Meta-analysis Global Group in Chronic Heart Failure (MAGGIC) risk score for HF, and from left ventricular end-diastolic volume and global longitudinal strain, whereas guidelines-based classification did not retain its independent prognostic value (hazard ratio = 1.25, p = 0.202).…"

Supplementary Material for: The importance of early diagnosis and intervention in chronic kidney disease: Calls-to-action from nephrologists based mainly in Central/Eastern Europe حسب Covic A. (4148122)

"…Key Messages Our key calls-to-action to address these unmet needs, thus improving the standard of care for patients with CKD, are: increase disease awareness, such as through education; encourage provision of financial support for patients; develop screening algorithms; revisit primary care physician referral practices; and create epidemiological databases that rectify the paucity of data on early-stage disease. …"