Results 211 to 220 of about 60,192 (299)

A Machine Learning Model for Predicting Posthepatectomy Liver Failure After Hepatectomy With Extrahepatic Bile Duct Resection for Perihilar Cholangiocarcinoma: With and Without Indocyanine Green

open access: yesAnnals of Gastroenterological Surgery, EarlyView.
Using machine learning‐based decision tree models, patients with perihilar cholangiocarcinoma undergoing major hepatectomy with extrahepatic bile duct resection were stratified according to the risk of posthepatectomy liver failure. Separate models were developed with and without indocyanine green data, enabling clinically interpretable preoperative ...
Yuki Homma   +11 more
wiley   +1 more source

AI in chemical engineering: From promise to practice

open access: yesAIChE Journal, EarlyView.
Abstract Artificial intelligence (AI) in chemical engineering has moved from promise to practice: physics‐aware (gray‐box) models are gaining traction, reinforcement learning complements model predictive control (MPC), and generative AI powers documentation, digitization, and safety workflows.
Jia Wei Chew   +4 more
wiley   +1 more source

Sociodemographic determinants of smoking among Jordanian men : insights from the 2023 demographic and health survey. [PDF]

open access: yesJ Health Popul Nutr
Ibrahim AAA   +7 more
europepmc   +1 more source

From continuous to interruptible distillation: Flexible electric heating column architecture with fast start‐up

open access: yesAIChE Journal, EarlyView.
Abstract Electrification of distillation offers a promising route to reducing scope‐1 emissions from one of the chemical industry's most energy‐intensive unit operations. However, conventional adiabatic columns are dynamically inflexible: Long, energy‐intensive start‐ups make shutdown and restart impractical under variable electricity prices and ...
Samuel Mercer, Michael Baldea
wiley   +1 more source

Cell Segmentation Beyond 2D—A Review of the State‐of‐the‐Art

open access: yesAdvanced Intelligent Discovery, EarlyView.
Cell segmentation underpins many biological image analysis tasks, yet most deep learning methods remain limited to 2D despite the inherently 3D nature of cellular processes. This review surveys segmentation approaches beyond 2D, comparing 2.5D and fully 3D methods, analyzing 31 models and 32 volumetric datasets, and introducing a unified reference ...
Fabian Schmeisser   +6 more
wiley   +1 more source

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