New Method Filters Highway Sensor Data in Real Time
A new real-time machine learning framework reduces highway structural health monitoring data storage by 91.63% while maintaining a 0.91 recall ...
Tag: Machine Learning
AI Models Show Promise in Pancreatic Cancer Diagnosis and Biomarker Discovery
A review in Cell Division evaluates AI and machine learning models for pancreatic cancer diagnosis, highlighting their high reliability in ...
Machine Learning Accurately Forecasts Monthly Malaria Incidence Across Southeastern Senegal Districts
Researchers evaluated three gradient boosting algorithms on six years of epidemiological and climatic data from southeastern Senegal, identifying an optimized ...
Machine Learning Model Predicts High-Flow Nasal Cannula Failure in COVID-19 Patients
A prospective cohort study evaluated machine learning models combining clinical and metabolomic features to predict high-flow nasal cannula failure in ...
Study Evaluates Emerging Technologies and Challenges in Vehicular Driving Pattern Analysis
A review of 117 studies evaluates how machine learning and sensor fusion are applied to vehicular driving pattern analysis while ...
Iterative Learning Model Estimates Tendon Loss in Concrete Bridges
A new iterative ensemble learning method estimates tendon loss in prestressed concrete bridges by analyzing vertical deck deflections, offering a ...
Machine Learning for Hip Replacement Outcomes Shows Performance Drop in Welsh Data
A preliminary study found that machine learning models predicting hip replacement outcomes trained on English data experienced performance drops when ...
Support Vector Machine Leads Prediction of Infection After Open Pulmonary Lobectomy
A retrospective study of 3,160 open pulmonary lobectomy patients found that a support vector machine model achieved the highest discrimination ...
Lab-based XGBoost model predicts lung adenocarcinoma recurrence on EGFR-TKIs
A retrospective study developed an XGBoost model using routine laboratory tests to predict recurrence risk in lung adenocarcinoma patients treated ...
Gut Microbiota Genes and Drug Candidates Identified for Peripheral Artery Disease
Researchers integrated multi-omics analyses and machine learning to identify core gut microbiota-related genes and candidate therapeutic compounds for peripheral artery ...
Stable MRI Radiomics Predicts Chemotherapy Response in Breast Cancer
A retrospective multicenter study of 686 patients with HR+/HER2− breast cancer established a stability-driven MRI radiomics model that accurately predicted ...
Machine learning tracks grazing damage in Himalayan grassland soils
A machine learning study of Himalayan alpine grasslands found that soil organic carbon fell 40.7 percent along a grazing disturbance ...
Random Forest Classifies Global Disaster Impact Severity From Spatiotemporal Event Data
A fine-tuned random forest model categorized global disaster events into impact classes using spatiotemporal and contextual data available at initial ...
AI Vehicle Maintenance System Merges Environmental Context With Internal Sensor Diagnostics
A new artificial intelligence framework improves connected vehicle predictive maintenance by fusing internal diagnostic telemetry with external environmental and behavioural ...
CT Radiomics Detects Lung Scarring in Scleroderma Patients as Well as Clinical Data, Small Study Finds
An exploratory study of 67 systemic sclerosis patients found that machine learning models built from HRCT radiomic features detected interstitial ...
Slope Aspect Shifts Fuel Drying Timing in Subtropical Forests
A year-long study in subtropical Masson pine forests reveals that slope aspect significantly delays fuel drying on shady slopes, impacting ...
Computational Deconvolution Review Benchmarks Twenty Spatial Transcriptomics Methods Across Diverse Technologies
A comprehensive review evaluates twenty computational algorithms designed to deconvolve mixed cellular signals from low-resolution spatial transcriptomics data into distinct ...
Fire hawks inspire encryption and AI pairing to guard healthcare cloud data
A dual-layer framework combining optimizer-guided XOR encryption with a probabilistic learning ensemble achieved 95.68 percent detection accuracy on healthcare cloud ...
Machine Learning Framework Optimizes Seismic Retrofitting for Aging Railway Viaduct Columns
Researchers have integrated a random forest machine learning model into a digital architecture framework to rapidly evaluate and optimize one-sided ...
Hybrid Feature Selection Boosts IoT DDoS Detection Accuracy
A new hybrid feature selection framework combining Particle Swarm Optimization and Grey Wolf Optimizer achieves high accuracy in detecting IoT ...
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