Results 251 to 260 of about 249,220 (290)

Machine Learning‐Informed Nano Co‐Assembly Inhibits Fibroblast Activation Protein and Improves Drug Delivery in Fibrotic Tissue

Advanced Materials, EarlyView.
We present SP‐13786 (SP), a fibroblast activation protein (FAP) inhibitor, as a universal excipient for co‐assembling stable drug nanoparticles (SCAN). Assembly mechanism deciphered by molecular dynamics and explainable machine learning, SCAN attenuate fibrosis‐induced stromal barriers, enhances lesional drug accumulation, and improves therapeutic ...
Zehua Liu, Qiang Long, Yihao Liu, Xiuqiao Sun, Baoding Zhang, Binxin Liao, Weibin Wu, Wangxi Hai, Pei Zhang, Wenhua Lian, Yuewen Zhu, Zheng Wang, Caisheng Wu, Xianming Deng, Hélder A. Santos, Xiaofeng Ye   +15 more
wiley   +1 more source

Impact of Natural Language Processing models on diagnosis and decision-making in healthcare, business, education, and sports: a review. [PDF]

Front Artif Intell
Choudhary A, Pamidimokkala S, R K, R M B.   +3 more
europepmc   +1 more source

Self‐Assembled Monolayers in p–i–n Perovskite Solar Cells: Molecular Design, Interfacial Engineering, and Machine Learning–Accelerated Material Discovery

Advanced Materials, EarlyView.
This review highlights the role of self‐assembled monolayers (SAMs) in perovskite solar cells, covering molecular engineering, multifunctional interface regulation, machine learning (ML) accelerated discovery, advanced device architectures, and pathways toward scalable fabrication and commercialization for high‐efficiency and stable single‐junction and
Asmat Ullah, Ying Luo, Stefaan De Wolf
wiley   +1 more source

Ethical challenges and opportunities for integrating predictive analytics in community-based overdose prevention. [PDF]

Lancet Reg Health Am
Allen B, Urmanche A, Curtis B, Fisher C.
europepmc   +1 more source

Decoding NASICON and Its Metal Interface for Solid‐State Batteries

Advanced Materials, EarlyView.
This review paper focuses on lithium‐ and sodium‐based NASICON solid electrolytes and their interfaces with metal anodes using a top‐down framework. It begins with NASICON fundamentals, elucidates anode‐induced failure mechanisms, surveys advanced characterization strategies to understand them, summarizes mitigation approaches, and concludes with a ...
Jiaqi Xu, Taiguang Li, Ying Wang, Ruosi Qiao, Quinn Qiao, Yu Chen, Zhou Yu, Chunyi Zhi, Changmin Shi   +8 more
wiley   +1 more source

Predicting Stunting Beyond Borders: Lessons From an Ethiopian Model and Pathways for Global Application. [PDF]

Health Sci Rep
Paramashanti BA.
europepmc   +1 more source

Artificial Intelligence in Medical Education: Transformative Potential, Current Applications, and Future Implications.

JMIR Med Educ
Izquierdo-Condoy JS, Arias-Intriago M, Montero Corrales L, Ortiz-Prado E.   +3 more
europepmc   +1 more source

Machine Learning for Big Data Analytics

Ümit Demirbaga, Gagangeet Singh Aujla, Anish Jindal, Oğuzhan Kalyon   +3 more
openalex   +1 more source

Diagnostic Accuracy of Artificial Intelligence Models for Differentiation of Squamous Cell Carcinoma and Adenocarcinoma of Lung-A Systematic Review. [PDF]

Diagnostics (Basel)
Nayak K, Kadavigere R, Pendem S, Mane PR, Sampathila N, Pattath Sankaran P, Siddeshappa N.   +6 more
europepmc   +1 more source