Results 51 to 60 of about 8,505,406 (249)

Harnessing the machine learning and nomogram models: elevating prognostication in nonmetastatic gastric cancer with “double invasion” for personalized patient care

European Journal of Medical Research
Objective To develop and validate a machine learning framework combined with a nomogram for predicting recurrence after radical gastrectomy in patients with vascular and neural invasion.
Zhenwen Hao, Zhiming Wang, Jinfeng Ma, Yifan Li, Wenbin Zhang   +4 more
doaj   +1 more source

A Multi-Objective Evaluation Framework for Analyzing Utility-Fairness Trade-Offs in Machine Learning Systems

The evaluation of fairness models in Machine Learning involves complex challenges, such as defining appropriate metrics, balancing trade-offs between utility and fairness, and there are still gaps in this stage. This work presents a novel multi-objective
Özbulak, Gökhan, Jimenez-del-Toro, Oscar, Anjos, André, Berton, Lilian, Fatoretto, Maíra   +4 more
core   +1 more source

Engagement Patterns With an Artificial Intelligence Health Coach for Systemic Sclerosis Self‐Management: A Mixed Methods Study

Arthritis Care &Research, EarlyView.
Objective To evaluate utility of an artificial intelligence (AI) health coach for systemic sclerosis (SSc) self‐management and identify patterns associated with participant engagement. Methods We conducted a mixed methods study in which an AI health coach, powered by a large language model (LLM), was used to support self‐management for SSc.
Nirali Shah, Melanie Morris, Cristina Daraban, Sophia Johnson, Susan L. Murphy   +4 more
wiley   +1 more source

Clinical Validation of Artificial Intelligence (AI)‐based Cartilage Segmentation Predicting Knee Replacement

Arthritis Care &Research, Accepted Article.
Objective For cartilage morphology to serve as a scalable endpoint in clinical trials, analyses should be performed automatically without human interaction. To clinically validate artificial intelligence (AI)‐based analysis, we studied cartilage loss from MRI prior to knee replacement.
Felix Eckstein, David J. Hunter, C. Kent Kwoh, Wolfgang Wirth   +3 more
wiley   +1 more source

Causal Machine Learning for Macroeconomic Forecasting Under Structural Breaks and Economic Uncertainty

Economies
Macroeconomic forecasting has become increasingly challenging in environments characterized by structural breaks, nonlinear dynamics, and elevated economic uncertainty.
Oumaima Abouzaid, Faouzi Boussedra
doaj   +1 more source

Extending Service Beyond Active Duty: Generalizability of Rheumatoid Arthritis Research Conducted Among US Veterans

Arthritis Care &Research, EarlyView.
Biomedical research involving US veterans continues to advance health care beyond the Veterans Health Administration. This is particularly true in rheumatoid arthritis (RA), where veteran‐centric research has uncovered novel insights into pathogenesis, risk factors, and disease manifestations, informing clinical care and research across both veteran ...
Austin M. Wheeler, Joshua F. Baker, Jennifer L. Barton, Maria I. Danila, Tate M. Johnson, Kamini Kuchinad, Kaleb Michaud, Amir A. Razmjou, J. Steuart Richards, Namrata Singh, Isaac D. Smith, Katherine D. Wysham, Grant W. Cannon, Bryant R. England, Amy Joseph, Deana Lazaro, Katherine P. Liao, Courtney Loecker, Andreas Reimold, Beth I. Wallace, Ted R. Mikuls   +20 more
wiley   +1 more source

Is an Apple an Orange? A Large Language Model Benchmark for Candidate Term Extraction and Subclass Decisions Against Upper Ontologies in Engineering and Materials Science

Advanced Engineering Materials, EarlyView.
Building machine‐readable vocabularies for materials science is slow, expert‐driven work. This study benchmarks 13 large language models on two of its first steps: finding candidate terms in engineering articles and deciding where they belong in a class hierarchy.
Thomas Bjarsch, Maximilian Holland, Klaus Drechsler, Johannes Schilp   +3 more
wiley   +1 more source

Exploring commuter stress dynamics through machine learning and double optimization

Mehran University Research Journal of Engineering and Technology
Travel dynamics significantly impact commuter stress, influenced by traffic behavior, road conditions, travel modes, distance, and socio-demographic characteristics.
Ashar Ahmed, Mario Muñoz-Organero, Bushra Aijaz   +2 more
doaj   +1 more source

Symbolic Regression and Multi‐Objective Optimization of the Flory–Huggins Interaction Parameter for Hydrogels

Advanced Engineering Materials, EarlyView.
We develop a data‐driven method to derive the mathematical expressions of the Flory–Huggins interaction parameter χ for the swelling behavior of temperature–responsive hydrogels. Starting from initial assumptions of χ, our workflow combines Bayesian optimization, Flory–Rehner theory, and symbolic regression to generate candidate χ expressions.
Yawen Wang, Adrian Ehrenhofer, Thomas Wallmersperger   +2 more
wiley   +1 more source

Refined Classification of Young Stellar Objects and Asymptotic Giant Branch Stars by Infrared Magnitudes, Colors, and Time-domain Analysis with Machine Learning

The Astrophysical Journal
We introduce a binary classification model, the double filter model, utilizing various machine learning and deep learning methods to classify young stellar objects (YSOs) and asymptotic giant branch (AGB) stars.
Hyunwook Jheonn, Jeong-Eun Lee, Jinho Lee, Seonjae Lee, Hyeyoon Lee, Shingeon Kim, Carlos Contreras Peña, Mi-Ryang Kim   +7 more
doaj   +1 more source