Results 281 to 290 of about 54,498 (352)

HLA‐DR+ Schwann Cells Generate the Protumor Cancer‐Neuron‐Immune Niche in Head and Neck Squamous Cell Carcinoma

Advanced Science, EarlyView.
Hijacked and educated by HNSCC cells, HLA‐DR+ Schwann cells lost their normal neural‐related functions but acquired immunoregulatory phenotypes to promote CD4+ T cells transform into Tregs. HLA‐DR+ Schwann cells induced a macrophage subpopulation, Il1β.
Xiaoyan Meng, Zhonglong Liu, Shijian Zhang, Luoman Gan, Liren Cao, Jingjing Sun, Lingfang Zhang, Yue He   +7 more
wiley   +1 more source

Early warning score and feasible complementary approach using artificial intelligence-based bio-signal monitoring system: a review. [PDF]

Biomed Eng Lett
Park D, So K, Prabhakar SK, Kim C, Lee JJ, Sohn JH, Kim JH, Lee SH, Won DO.   +8 more
europepmc   +1 more source

Chronic Disease Monitoring Using Advanced Compliant Materials for Bioelectronics

Advanced Electronic Materials, EarlyView.
Compliant bioelectronic systems enable continuous monitoring of chronic disease through soft, stretchable materials and tissue‐conformal designs that support stable electrophysiological, mechanical, and biochemical sensing. Integration of diverse sensing modalities with thoughtful material selection, device architectures, and advanced fabrication ...
Han Kim, Mabel Bartlett, Liyang Wang, Karl Bates, Mengdi He, Myungbo Kim, Carmel Majidi, Tzahi Cohen‐Karni   +7 more
wiley   +1 more source

Development and validation of a transformer model-based early warning score for real-time prediction of adverse outcomes in the emergency department. [PDF]

Sci Rep
Chang H, Park JE, Lee D, Lee K, Jekal SY, Moon KT, Heo S, Kim D, Lee GT, Hwang SY, Cha WC, Kim W, Lim TH, Shin TG.   +13 more
europepmc   +1 more source

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

Advanced 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, Zheyu Zhang, Kelvian T. Mularso, Bonghyun Jo, Hyun Suk Jung   +4 more
wiley   +1 more source

Pediatric Early Warning Score in interhospital ambulance care: a pilot study exploring feasibility and impact. [PDF]

Scand J Trauma Resusc Emerg Med
Luijmes M, Stevens J, Diets N, Tolsma R, de Groot J, Fuijkschot J.   +5 more
europepmc   +1 more source

In adults 18 years and older presenting to the ED with possible sepsis, how does using multiple early warning scoring systems compared to one affect the ability to start sepsis treatment and reduce progression to septic shock and mortality rates?

Tripdatabase
openalex   +1 more source

Organic Photoelectrochemical Cells Beyond Performance: Interface and Catalyst Engineering for Durability

Advanced Energy Materials, EarlyView.
Organic photoelectrochemical cells based on π‐conjugated semiconductors offer a versatile platform for solar fuel generation. This review outlines operating principles, device architectures, and key metrics, and highlights advances in p‐ and n‐type photoelectrodes, interfacial engineering, and catalyst integration.
Jaehyeong Kim, Jung Min Ha, Yeonjeong Lee, Seung Won Oh, Wangyeon Lee, Munsu Kwon, Soonyong Lee, Jin Young Kim, Han Young Woo   +8 more
wiley   +1 more source

Multicenter Development and Prospective Validation of eCARTv5: A Gradient-Boosted Machine-Learning Early Warning Score. [PDF]

Crit Care Explor
Churpek MM, Carey KA, Snyder A, Winslow CJ, Gilbert E, Shah NS, Patterson BW, Afshar M, Weiss A, Amin DN, Rhodes DJ, Edelson DP.   +11 more
europepmc   +1 more source

Machine Learning Interatomic Potentials for Energy Materials: Architectures, Training Strategies, and Applications

Advanced Energy Materials, EarlyView.
Machine learning interatomic potentials bridge quantum accuracy and computational efficiency for materials discovery. Architectures from Gaussian process regression to equivariant graph neural networks, training strategies including active learning and foundation models, and applications in solid‐state electrolytes, batteries, electrocatalysts ...
In Kee Park, Saeed Pourasad, Jinhong Mun, Arunkumar Chitteth Rajan, Tae Hyeon Park, Anand Rohit, Mohammad Zafari, Tan‐Lien Pham, Eunjae Jung, Bonseung Koo, Miran Ha, Gi Beom Sim, Hyun Gyu Park, Won Woong Choi, Kwanghyeon Jo, Soohaeng Yoo Willow, David ChangMo Yang, Chang Woo Myung, Geunsik Lee, Kwang S. Kim   +19 more
wiley   +1 more source