Table 3_Predictive modeling of acute radiation-induced dermatitis in nasopharyngeal carcinoma patients undergoing tomotherapy using machine learning with multimodal data integratio... حسب Jiabiao Hong (22354900)

"…SVM method demonstrated superior overall performance across various model constructions. The combined model based on the SVM method exhibited optimal predictive performance, achieving the best results in both the test and validation cohorts.…"

Table 1_Predictive modeling of acute radiation-induced dermatitis in nasopharyngeal carcinoma patients undergoing tomotherapy using machine learning with multimodal data integratio... حسب Jiabiao Hong (22354900)

"…SVM method demonstrated superior overall performance across various model constructions. The combined model based on the SVM method exhibited optimal predictive performance, achieving the best results in both the test and validation cohorts.…"

Table 2_Predictive modeling of acute radiation-induced dermatitis in nasopharyngeal carcinoma patients undergoing tomotherapy using machine learning with multimodal data integratio... حسب Jiabiao Hong (22354900)

"…SVM method demonstrated superior overall performance across various model constructions. The combined model based on the SVM method exhibited optimal predictive performance, achieving the best results in both the test and validation cohorts.…"

Image 1_Interplay between noise-induced sensorineural hearing loss and hypertension: pathophysiological mechanisms and therapeutic prospects.png حسب Carola Y. Förster (11595118)

"…Computational methods, including molecular docking, molecular dynamics simulations, QSAR/QSPR analysis with machine/deep learning algorithms, and network pharmacology, hold potential for identifying drug candidates and optimizing their interactions with BLB transporters, such as the glutamate transporter. …"

Image 1_Development of machine learning predictive model for type 2 diabetic retinopathy using the triglyceride-glucose index explained by SHAP method.png حسب Xiaoqin Liu (296429)

"…The performance of five machine learning algorithms, including Logistic Regression model (LR), Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM), and XGBoost (XGB), was assessed based on accuracy, sensitivity, specificity, and Area Under the Curve (AUC) of the Receiver Operating characteristic Curve (ROC). …"

Image 2_Development of machine learning predictive model for type 2 diabetic retinopathy using the triglyceride-glucose index explained by SHAP method.png حسب Xiaoqin Liu (296429)

"…The performance of five machine learning algorithms, including Logistic Regression model (LR), Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM), and XGBoost (XGB), was assessed based on accuracy, sensitivity, specificity, and Area Under the Curve (AUC) of the Receiver Operating characteristic Curve (ROC). …"

Image 1_Automated machine learning for predicting perioperative ischemia stroke in endovascularly treated ruptured intracranial aneurysm patients.jpeg حسب Yuhang Peng (11072070)

"…Nine machine learning algorithms were evaluated using stratified 10-fold cross-validation. …"

An Ecological Benchmark of Photo Editing Software: A Comparative Analysis of Local vs. Cloud Workflows حسب Pierre-Alexis DELAROCHE (22092572)

"…Experimental Methodology Framework Local Processing Pipeline Architecture Data Flow: Storage I/O → Memory Buffer → CPU/GPU Processing → Cache Coherency → Storage I/O ├── Input Vector: mmap() system call for zero-copy file access ├── Processing Engine: OpenMP parallelization with NUMA-aware thread affinity ├── Memory Management: Custom allocator with hugepage backing └── Output Vector: Direct I/O bypassing kernel page cache Cloud Processing Pipeline Architecture Data Flow: Local Storage → Network Stack → TLS Tunnel → CDN Edge → Origin Server → Processing Grid → Response Pipeline ├── Upload Phase: TCP window scaling with congestion control algorithms ├── Network Layer: Application-layer protocol with adaptive bitrate streaming ├── Server-side Processing: Containerized microservices on Kubernetes orchestration ├── Load Balancing: Consistent hashing with geographic affinity routing └── Download Phase: HTTP/2 multiplexing with server push optimization Dataset Schema and Semantic Structure Primary Data Vectors Field Data Type Semantic Meaning Measurement Unit test_type Categorical Processing paradigm identifier {local_processing, cloud_processing} photo_count Integer Cardinality of input asset vector Count avg_file_size_mb Float64 Mean per-asset storage footprint Mebibytes (2^20 bytes) total_volume_gb Float64 Aggregate data corpus size Gigabytes (10^9 bytes) processing_time_sec Integer Wall-clock execution duration Seconds (SI base unit) cpu_usage_watts Float64 Thermal design power consumption Watts (Joules/second) ram_usage_mb Integer Peak resident set size Mebibytes network_upload_mb Float64 Egress bandwidth utilization Mebibytes energy_consumption_kwh Float64 Cumulative energy expenditure Kilowatt-hours co2_equivalent_g Float64 Carbon footprint estimation Grams CO₂e test_date ISO8601 Temporal execution marker RFC 3339 format hardware_config String Node topology identifier Alphanumeric encoding Statistical Distribution Characteristics The dataset exhibits non-parametric distribution patterns with significant heteroscedasticity across computational load vectors. …"

Table 2_Histone-related gene WDR77 promotes tumor progression through cell cycle regulation in skin cutaneous melanoma.xls حسب Haoxue Zhang (12208580)

"…The optimal model, based on seven histone-related genes, showed the highest C-index and was validated in both training and validation cohorts. …"

Supplementary information for Efficient distributed edge computing for dependent delay-sensitive tasks in multi-operator multi-access networks حسب Alia Asheralieva (17562462)

"…We prove that the game has a perfect Bayesian equilibrium (PBE) yielding unique optimal values, and formulate new Bayesian reinforcement learning and Bayesian deep reinforcement learning algorithms enabling each PN to reach the PBE autonomously (without communicating with other PNs).…"

Table 3_Histone-related gene WDR77 promotes tumor progression through cell cycle regulation in skin cutaneous melanoma.xlsx حسب Haoxue Zhang (12208580)

"…The optimal model, based on seven histone-related genes, showed the highest C-index and was validated in both training and validation cohorts. …"

Table 1_Histone-related gene WDR77 promotes tumor progression through cell cycle regulation in skin cutaneous melanoma.xlsx حسب Haoxue Zhang (12208580)

"…The optimal model, based on seven histone-related genes, showed the highest C-index and was validated in both training and validation cohorts. …"

Data Sheet 2_Histone-related gene WDR77 promotes tumor progression through cell cycle regulation in skin cutaneous melanoma.zip حسب Haoxue Zhang (12208580)

"…The optimal model, based on seven histone-related genes, showed the highest C-index and was validated in both training and validation cohorts. …"

Data Sheet 1_Histone-related gene WDR77 promotes tumor progression through cell cycle regulation in skin cutaneous melanoma.zip حسب Haoxue Zhang (12208580)

"…The optimal model, based on seven histone-related genes, showed the highest C-index and was validated in both training and validation cohorts. …"

Supplementary data حسب Joon Young Kim (22352152)

"…<p dir="ltr">This repository contains supplementary tables and figures for the article <i>“Development of a Machine Learning-Based Model for Methimazole Dosage Adjustment in Youth with Hyperthyroidism.”…"

An embedded system for automatic pathological characterization classification by EEG حسب Xia HAN (20831246)

"…<p dir="ltr">This study presents an system for the automatic classification of pathological EEG signals using artificial intelligence (AI) algorithms. The research explores the application of deep learning and machine learning techniques, including 1D CNN and KNN to classify EEG signals into different pathological states. …"

Seasonal Pasture Distribution Maps of Qinghai-Tibet Plateau from 1990 to 2020 حسب panfei Fang (14280560)

"…The data is generated through an innovative technical framework that integrates machine learning algorithms and Landsat imagery. The framework uses time-series spectral analysis to determine the optimal time window for differentiating cold- and warm-season pastures. …"

Collaborative Research: SCIPE: Interdisciplinary Research Support Community for Artificial Intelligence and Data Sciences حسب Sanmukh Kuppannagari (21798863)

"…<br><br>To achieve 10x-100x reduction in DNN energy consumption, a holistic approach is pursued, which encompasses: (1) new circuit designs that leverage emerging CMOS+X technologies; (2) a novel near-memory architecture in which processing elements are seamlessly integrated with traditional Dynamic RAM (DRAM); (3) novel 3D-matrix-based per-layer DNN computations and data-layout optimizations for kernel weights; and (4) algorithms and hardware/software co-design tailored for near-real-time DNN-based signal classification in next-generation wireless systems. …"

Table 2_Development and validation of interpretable machine learning models for postoperative pneumonia prediction.xlsx حسب Bingbing Xiang (17198547)

"…</p>Objective<p>Our study aims to develop and validate a predictive model for POP in surgical patients using nine machine learning algorithms. By evaluating the performance differences among these machine learning models, this study aims to assist clinicians in early prediction and diagnosis of POP, providing optimal interventions and treatments.…"

Data Sheet 1_Tumor tissue-of-origin classification using miRNA-mRNA-lncRNA interaction networks and machine learning methods.docx حسب Ankita Lawarde (16544943)

"…Our comparative analysis demonstrated that models based on miRNA outperformed those using mRNA or lncRNA classifiers.…"