Results 151 to 160 of about 29,456 (261)

SHAP value-based ERP analysis (SHERPA): Increasing the sensitivity of EEG signals with explainable AI methods. [PDF]

Behav Res Methods
Sylvester S, Sagehorn M, Gruber T, Atzmueller M, Schöne B.   +4 more
europepmc   +1 more source

Computed Tomography‐Based Morphometric Analysis Reveals Intercondylar Notch Stenosis and Osteophytes Are Associated With Anterior Cruciate Ligament Injury

Arthroscopy, EarlyView.
Purpose To quantitatively assess intercondylar notch morphometrics using 3‐dimensional computed tomography reconstruction, evaluate their association with anterior cruciate ligament (ACL) injury in Asian populations, and investigate the prevalence of osteophytes in patients with ACL injury.
Xiaozhong Ma, WenMing Jiang, Chao Lu, Tongyue Ji, Su Yan, Heng Zhu, Xue He, Hao Shu, Lei Wang, Luning Sun   +9 more
wiley   +1 more source

Clinical decision support tool for breast cancer recurrence prediction using SHAP value in cooperative game theory. [PDF]

Heliyon
Liu Y, Fu Y, Peng Y, Ming J.
europepmc   +1 more source

Identifying Systemic Lupus Erythematosus From Serum Proteomic Profiles Using Machine Learning and Genetic Risk Stratification

Arthritis &Rheumatology, EarlyView.
Objective Proteome‐wide risk models for lupus remain underexplored. We developed classification models to identify lupus from serum proteomic profiles. Methods Patients with lupus and individuals with other autoimmune diseases in the UK Biobank were included.
Mehmet Hocaoǧlu, Jishnu Das, Amr H. Sawalha   +2 more
wiley   +1 more source

Machine Learning to Predict Remission Between 6 and 24 Months in Rheumatoid Arthritis: Insights From JAK, an International Registry Collaboration

Arthritis &Rheumatology, EarlyView.
Objective To develop, externally validate, and simplify a machine learning model to predict remission between 6 and 24 months in patients with rheumatoid arthritis (RA) initiating tumor necrosis factor inhibitors, JAK inhibitors, interleukin‐6 inhibitors, abatacept, or rituximab using data from 11 international registries in the JAK‐pot collaboration ...
Zubeyir Salis, Denis Mongin, Denis Choquette, Louis Coupal, Catalin Codreanu, Florenzo Iannone, Roberto Caporali, Tore K. Kvien, Sella Provan, Ruth Fritsch‐Stork, Dan Nordström, Nina Trokovic, Karel Pavelka, Jakub Závada, Ana Rodrigues, Ziga Rotar, Prodromos Sidiropoulos, Irini Flouri, Céline Lamacchia, Michele Iudici, Delphine Courvoisier, Kim Lauper, Axel Finckh   +22 more
wiley   +1 more source

Inferring Rheumatoid Arthritis Disease Activity Status From the Electronic Health Records Across Health Systems

Arthritis &Rheumatology, EarlyView.
Objective Disease activity plays a central role in rheumatoid arthritis (RA) clinical studies. The inconsistent availability of data on disease activity in real‐world electronic health records (EHRs) data has limited the ability to generate real‐world evidence (RWE).
David Cheng, Xuan Wang, Gregory C. McDermott, Jennifer S. Hanberg, Zoe Love, Katherine Zhong, Mary Jeffway, Jue Hou, Vidul Panickan, Rahul Sangar, Ying Qi, Connor Melley, Lauren Costa, Dakota Feil, Rachael Matty, Dana Weisenfeld, Abisayo Animashaun, Aimee Schreiner, Sara Morini, Lauren Rusnak, Andrew Cagan, Misti Paudel, J. Michael Gaziano, Brian Sauer, Michael Weinblatt, Joshua Baker, Bryant England, Yuk‐Lam Ho, Kelly Cho, Paul Monach, Grant W. Cannon, Nancy Shadick, Ted R. Mikuls, Tianxi Cai, Katherine P. Liao   +34 more
wiley   +1 more source

Cancer in Systemic Sclerosis: Clinical Associations and Prognostic Impact From the EUSTAR Registry

Arthritis &Rheumatology, EarlyView.
Objective Cancer represents a major cause of death in systemic sclerosis (SSc). Established risk factors are limited to specific subsets, particularly early diffuse anti‐RNA polymerase III (POLR3)–positive disease, needing further exploration. Methods We performed a nested case‐control study within the European Scleroderma Trials and Research group ...
Antonio Tonutti, Francesca Motta, Liala Moschetti, Cosimo Bruni, Carina Mihai, Claudia Iannone, Maria Rosa Pellico, Stefano Stano, Stefano Erba, Claudia Barison, Eleonora Pazzi, Andrea Benini, Beatrice Moccaldi, Kurszán Jász Dávid, Ágnes Ágoston‐Szabó, Beatrice Gabrielli, Francesca Nava, Dóra Tari, Francesca Romana Di Ciommo, Yuri Sasaki, Gonçalo Boleto, Radim Bečvář, Alejandro Brigante, Britta Maurer, Massimiliano Limonta, Rahma A. Elziaty, Fabiola Atzeni, Lilian Maria López Núñez, Roberta Foti, Francesco Benvenuti, Brigitte Granel, Elena Rezus, Leila Caillault, Sophie Blaise, Cristiana Sieiro Santos, Fabio Cacciapaglia, Roberto Giacomelli, Rossella De Angelis, Serena Guiducci, Duygu Temiz Karadag, Gabriella Szűcs, Luca Idolazzi, Gábor Kumánovics, Florenzo Iannone, Maurizio Cutolo, Gianluca Moroncini, Valeria Riccieri, Nicoletta Del Papa, Elisabetta Zanatta, Oliver Distler, Masataka Kuwana, Carlo Selmi, Maria De Santis   +52 more
wiley   +1 more source

Accelerating green heterocyclic synthesis: Convergence of AI, automation, and sustainable chemistry

Bulletin of the Korean Chemical Society, EarlyView.
Green heterocyclic synthesis and data‐driven tools such as AI, high‐throughput experimentation, continuous flow, and self‐driving laboratories have developed largely in parallel. This review connects them and asks how green metrics such as E‐factor and PMI might serve as explicit optimization targets rather than post‐hoc measures, toward sustainable ...
Noor Aisyah Ahmad Shah, Amirreza Mottafegh, Su‐Hyun Yoo, Jongwoon Kim, Minseon Byeon, Juhwan Noh, Yea‐Lee Lee, Jin Suk Myung, Gwang‐Noh Ahn   +8 more
wiley   +1 more source

Bridging the translational gap in clinical nanomedicine: From rational design to clinical reality

BMEMat, EarlyView.
Nanotechnology offers a multi‐faceted approach to modern healthcare, encompassing high‐sensitivity diagnostic imaging, innovative vaccine delivery, and targeted therapeutics. This review explores how these nanomedicine applications address critical challenges in cancer recurrence and the treatment of neurologic and respiratory diseases to combat rising
Ahmed H. Ghonaim, Marwa Ahmed El‐Naka, Wedad M. Nageeb, Atta Ullah Khan, Noura M. Seleem, Aliaa Abdelghafar, Doaa Zamel, Yang Liu, Qigai He, Wentao Li   +9 more
wiley   +1 more source

Do Governance Structures Drive Green Building Adoption? A Machine Learning Approach With Random Forests

Business Strategy and the Environment, EarlyView.
ABSTRACT This study examines the determinants of firms' propensity to adopt green buildings in the Euro Stoxx 300 and the S&P 500 indices, during 2012–2023. Using random forest binary classifiers, we assess the relative importance of financial, sectoral, geographic, and climate governance predictors and uncover nonlinear relationships often overlooked ...
María del Carmen Valls Martínez, José Manuel Santos‐Jaén, María Estefanía Sánchez Pacheco, Fernando José Zambrano Farías   +3 more
wiley   +1 more source