Results 261 to 270 of about 1,786,461 (344)

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

Annals 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, Marko Kumric, Zvonimir Boban, Josip Vrdoljak, Dario Pecenkovic, Matej Ivanda, Marko Grahovac, Zenon Pogorelic, Josko Bozic   +8 more
wiley   +1 more source

TCMI-F-6D benchmark construction and quantitative assessment of interdisciplinary foundational competencies in traditional Chinese medicine informatics using large language models. [PDF]

Front Artif Intell
Teng Z, Chang J, Xu Y, Kan H, Ou Y, Hu J, Gu Z, Yang Y, Shu J.   +8 more
europepmc   +1 more source

PHS 1108 (IC0624499; INGR18005), a Wheat (Triticum aestivum) Germplasm with High Protein Content, Bold Seeds and High Manganese Content.

, 2019
SK Singh, Tiwari, RK Gupta, BS Tyagi, Suresh Kumar, Prakit C. D. Sharma, Karnam Venkatesh, AK Sharma, Charan Singh, GP Singh   +9 more
openalex   +1 more source

Domain‐Aware Implicit Network for Arbitrary‐Scale Remote Sensing Image Super‐Resolution

Advanced Intelligent Discovery, EarlyView.
Although existing arbitrary‐scale image super‐resolution methods are flexible to reconstruct images with arbitrary scales, the characteristic of training distribution is neglected that there exists domain shift between samples of various scales. In this work, a Domain‐Aware Implicit Network (DAIN) is proposed to handle it from the perspective of domain
Xiaoxuan Ren, Qian Jiang, Xin Jin, Puming Wang, Xing Chu, Shaowen Yao, Shengfa Miao   +6 more
wiley   +1 more source

Digital Twin Brain: Generating Multitask Behavior from Connectomes for Personalized Therapy. [PDF]

BME Front
Takahashi Y, Soda T, Tomita H, Yamashita Y.   +3 more
europepmc   +1 more source

Artificial Intelligence‐Driven Insights into Electrospinning: Machine Learning Models to Predict Cotton‐Wool‐Like Structure of Electrospun Fibers

Advanced Intelligent Discovery, EarlyView.
Electrospinning allows the fabrication of fibrous 3D cotton‐wool‐like scaffolds for tissue engineering. Optimizing this process traditionally relies on trial‐and‐error approaches, and artificial intelligence (AI)‐based tools can support it, with the prediction of fiber properties. This work uses machine learning to classify and predict the structure of
Paolo D’Elia, Giovanna Pappalardo, Aldo R. Boccaccini, Liliana Liverani   +3 more
wiley   +1 more source

Introducing Structural Reliance: A New Method to Assess Structure-Function Coupling in the Brain. [PDF]

Hum Brain Mapp
Madden D, Laurienti PJ, Shappell HM, Bahrami M.   +3 more
europepmc   +1 more source

Advancing Clinical Research

Advanced Science, EarlyView.
wiley   +1 more source

Limitations of Foundation Models in Energy Materials Simulations: A Case Study in Polyanion Sodium Cathode Materials

Advanced Intelligent Discovery, EarlyView.
Several simulation techniques are used to explore static and dynamic behavior in polyanion sodium cathode materials. The study reveals that universal machine learning interatomic potentials (MLIPs) struggle with system‐specific chemistry, emphasizing the need for tailored datasets.
Martin Hoffmann Petersen, Chiku Parida, Jonas Busk, Jin Hyun Chang, Arghya Bhowmik, Juan Maria Garcia Lastra   +5 more
wiley   +1 more source