Results 81 to 90 of about 67,939 (291)

Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories

open access: yesAdvanced Energy Materials, EarlyView.
In this review, we summarize the fundamentals of AI in automated materials science, and review AI applications in perovskite solar cells. Then, we sum up recent progress in AI‐guided manufacturing optimization, and highlight AI‐driven high‐throughput and autonomous laboratories.
Wenning Chen   +4 more
wiley   +1 more source

Applications of cooperative games to business activities

open access: yesIntangible Capital, 2008
We show several applications of the cooperative game theory and the Shapley value to business activities. Among them we emphasize on the sharing of costs or profits.
Rafel Amer   +2 more
doaj   +1 more source

The Role of Artificial Intelligence in Medication Management for Older Adults: A Systematic Review

open access: yesAGING MEDICINE, EarlyView.
Artificial intelligence enhances medication management for older adults by improving adherence, personalizing treatment, and predicting risks. Despite benefits, challenges remain in usability, trust, ethics, and system integration. Successful adoption requires user‐centered design, ethical safeguards, and seamless healthcare integration to ensure safe,
Dipak Chandra Das   +9 more
wiley   +1 more source

A Blockchain-Based E-Participation Framework Utilizing Zero-Knowledge Proofs With Guaranteed Sampling and Differential Reward Mechanisms

open access: yesIEEE Access
Blockchain-based E-participation systems significantly enhance transparency, data integrity, and security compared to traditional E-participation methods.
Jungwon Seo   +5 more
doaj   +1 more source

The Ranking Problem of Alternatives as a Cooperative Game

open access: yes, 2015
This paper considers the ranking problem of candidates for a certain position based on ballot papers filled by voters. We suggest a ranking procedure of alternatives using cooperative game theory methods.
Kondratev, Aleksei, Mazalov, Vladimir
core   +1 more source

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

Dynamic evaluation and realization mechanisms of multi-dimensional benefits for microgrids in new-type power systems

open access: yesFrontiers in Energy Research
Amid high renewable penetration, market reform, and dual-carbon goals, microgrids are expected to deliver economic, environmental, and technical value, yet much work remains static or single-dimensional and lacks a closed loop from evaluation to fair ...
Zhengdong Wan, Jinsong Zhang, Yan Huang
doaj   +1 more source

The Shapley value for bicooperative games [PDF]

open access: yes
The aim of the present paper is to study a one-point solution concept for bicooperative games. For these games introduced by Bilbao (2000), we define a one-point solution called the Shapley value, since this value can be interpreted in a similar way to ...
Jesús Mario Bilbao   +3 more
core  

Matrix approach to consistency of the additive efficient normalization of semivalues [PDF]

open access: yes, 2007
In fact the Shapley value is the unique efficient semivalue. This motivated Ruiz et al. to do additive efficient normalization for semivalues. In this paper, by matrix approach we derive the relationship between the additive efficient normalization of ...
Driessen, T.S.H., Sun, H., Xu, G.
core   +2 more sources

Can Machine Learning Reduce Unnecessary Surgeries? A Retrospective Analysis Using Threshold Optimization to Prevent Negative Appendectomies in Adults

open access: yesAnnals of Gastroenterological Surgery, EarlyView.
Threshold‐optimized machine learning models using routine clinical and laboratory data in 623 adults undergoing appendectomy. Logistic regression (AUC = 0.765) and random forest (AUC = 0.785) were the best‐performing models for appendicitis detection and complicated appendicitis prediction, respectively.
Ivan Males   +8 more
wiley   +1 more source

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