Results 131 to 140 of about 270,692 (266)

Soft Skins With Reversible Thickness Morphing: Materials, Mechanisms, and Applications

Advanced Materials, EarlyView.
Evolution of electronic skin (e‐skin) technologies toward adaptive, multifunctional soft skins. Phase I highlights early rigid and discrete sensory interfaces. Phase II shows the transition toward flexible, stretchable, and large‐area e‐skin. Phase III captures the emergence of computational e‐skin.
Oliver Ozioko, Chiamaka Akah, Ravinder Dahiya   +2 more
wiley   +1 more source

Data‐Driven Materials Science for Energy‐Sustainable Applications

Advanced Materials, EarlyView.
Data‐driven approaches powered by artificial intelligence are transforming materials discovery for energy sustainability. This review examines how auto‐generated high‐quality materials databases and domain‐specific language models accelerate research in photovoltaics, thermoelectrics, batteries and magnetic materials. Applications involve extraction of
Jacqueline M. Cole
wiley   +1 more source

An Ensemble Learning Artificial Intelligence Model for Alzheimer's Disease Detection Using OCT. [PDF]

Ophthalmol Sci
Ran AR, Hu X, Hui HYH, Dai J, Chan VTT, Ho K, Au LWC, Ng CF, Sham K, Zheng C, Liu X, He Q, Tham CC, Kwok TCK, Hilal S, Cheng CY, Chua J, Schmetterer L, Liu TYA, Tham YC, Li-Hsian Chen C, Wong TY, Mok VCT, Cheung CY.   +23 more
europepmc   +1 more source

Four Types of Multiclass Frameworks for Pneumonia Classification and Its Validation in X-ray Scans Using Seven Types of Deep Learning Artificial Intelligence Models. [PDF]

Diagnostics (Basel), 2022
Nillmani, Jain PK, Sharma N, Kalra MK, Viskovic K, Saba L, Suri JS.   +6 more
europepmc   +1 more source

In-context learning in natural and artificial intelligence.

In-context learning refers to the ability of a neural network to learn from information presented in its context. While traditional learning in neural networks requires adjusting network weights for every new task, in-context learning operates purely by updating internal activations without needing any updates to network weights.
Jagadish, Akshay Kumar, Dasgupta, Ishita, Pesnot Lerousseau, Jacques, Binz, Marcel   +3 more
openaire   +1 more source

Closed‐Loop Solid‐State Synthesis Planning for Materials Discovery With Large Language Models

Advanced Materials, EarlyView.
Leveraging literature data, we build a large‐language‐model‐driven workflow that extracts synthesis steps from 4407 papers, retrieves similar precedents, and generates candidate solid‐state synthesis recipes. The system benchmarks against ground‐truth and then operates in a closed loop with experiments to synthesize oxy‐selenide electrolyte materials ...
Dong Won Jeon, Dong Hwi Kim, Taeyang Jeon, Joo Yeong Na, Heegyu Kim, Hyunsouk Cho, Dae Soo Jung, Ju Li, Jin‐Sung Park, Sung Beom Cho   +9 more
wiley   +1 more source

Can algorithms come to the rescue of a failing heart? Machine learning, artificial intelligence, and decision-making in cardiogenic shock. [PDF]

J Anesth Analg Crit Care
Bottussi A, Wieruszewski PM, Bignami EG, Swol J, Buda KG, Cheungpasitporn W, Elmadhoun O, D'Andria Ursoleo J.   +7 more
europepmc   +1 more source

COVLIAS 1.0: Lung Segmentation in COVID-19 Computed Tomography Scans Using Hybrid Deep Learning Artificial Intelligence Models. [PDF]

Diagnostics (Basel), 2021
Suri JS, Agarwal S, Pathak R, Ketireddy V, Columbu M, Saba L, Gupta SK, Faa G, Singh IM, Turk M, Chadha PS, Johri AM, Khanna NN, Viskovic K, Mavrogeni S, Laird JR, Pareek G, Miner M, Sobel DW, Balestrieri A, Sfikakis PP, Tsoulfas G, Protogerou A, Misra DP, Agarwal V, Kitas GD, Teji JS, Al-Maini M, Dhanjil SK, Nicolaides A, Sharma A, Rathore V, Fatemi M, Alizad A, Krishnan PR, Frence N, Ruzsa Z, Gupta A, Naidu S, Kalra M.   +39 more
europepmc   +1 more source

Sustainable and Multifunctional Natural Macromolecular Polymers for Aqueous Zn Metal Batteries

Advanced Materials, EarlyView.
We comprehensively review the structure‐function relationships and regulatory mechanism of natural macromolecular polymers in stabilizing zinc anodes at the microscopic and mesoscopic scales. The interactions among polymer structures, optimization strategies, and regulatory mechanisms are discussed systematically summarizing recent related research ...
Yunuo Shi, Bo Jiang, Jingcheng Zhang, Xiaodong Shao, Peixun Xiong, Lutong Shan, Shengyang Huang, Mengfang Liang, Mengyao Chang, Fangyan Liu, Wenwu Li, Baoyu Xia, Wei Ji, Ho Seok Park   +13 more
wiley   +1 more source

Tumor cell- and infiltrating immune cell-based supervised learning artificial intelligence multimodal platform for tumor prognosis. [PDF]

NPJ Precis Oncol
Cai XJ, Peng CR, Ding CY, Cui YY, Gao L, Xu ZX, Li L, Zhang JY, Li TJ.   +8 more
europepmc   +1 more source