BMJ Open

Generating actionable insights to support point-of-care suicide risk decision-making in a safety-net healthcare system: a machine learning approach to predicting dynamic risk ...

Background Suicide rates have increased over the last couple of decades globally, particularly in the United States and among populations with lower economic status who present at safety-net ...
Beebom

What is the Difference Between Deep Learning and Machine Learning

Machine learning requires humans to manually label features while deep learning automatically learns features directly from raw data. ML uses traditional algorithms like decision tress, SVM, etc., ...
Scientific Research Publishing

Explainable Machine Learning in Risk Management: Balancing Accuracy and Interpretability ()

1 School of Taxation and Public Administration, Shanghai Lixin University of Accounting and Finance, Shanghai, China. 2 School of Business, Computing and Social Sciences, University of Gloucestershire ...
Scientific Research Publishing

Deformation Control and Early Warning Analysis of Deep Riverside Foundation Pit Construction Process Based on Machine Learning ()

1 China Communications Third Shipping Engineering Bureau Co., Ltd., Shanghai, China. 2 School of Civil Engineering, Wuhan University, Wuhan, China. The large deep foundation pit projects usually face ...
VentureBeat

Chinese startup Z.ai launches powerful open source GLM-4.5 model family with PowerPoint creation

Want smarter insights in your inbox? Sign up for our weekly newsletters to get only what matters to enterprise AI, data, and security leaders. Subscribe Now Another week in the summer of 2025 has ...
C&EN

Reinforcement Learning-Based Nonlinear Model Predictive Controller for a Jacketed Reactor: A Machine Learning Concept Validation Using Jetson Orin

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. In this research work authors have experimentally validated a blend of Machine ...
IEEE

Hybrid Machine Learning for CNC Process Monitoring

Abstract: The transition to highly customized, one-off production in modern manufacturing necessitates sophisticated process monitoring to reduce waste, minimize downtime, and alleviate operator ...
Frontiers

Construction and clinical visualization application of a predictive model for mortality risk in sepsis patients based on an improved machine learning model

Objective: To explore the construction and clinical visualization application of a mortality risk prediction model for sepsis patients based on an improved machine learning model. Methods: This ...
C&EN

Physics-Assisted Machine Learning for the Simulation of the Slurry Drying in the Manufacturing Process of Battery Electrodes: A Hybrid Time-Dependent VGG16-DEM Model

Laboratoire de Réactivité et de Chimie des Solides (LRCS), UMR CNRS 7314, Université de Picardie Jules Verne, Hub de l’Energie, 15 rue Baudelocque, 80039 Amiens Cedex, France Réseau sur le Stockage ...