Results 191 to 200 of about 139,836 (280)

Citizen Engagement for Social and Technological Innovation in Sustainable Energy Systems

Advanced Energy and Sustainability Research, EarlyView.
This study underscores the potential of citizen participation in the energy transition by providing insights to foster citizen‐driven innovation. An analysis of energy communities, one of the most dynamic innovations in the energy sector, reveals that these models can be citizen‐led initiatives regarding their operational and organizational structure ...
Ana Belén Cristóbal, Cristina Sanz‐Cuadrado, Kiane Alves e Silva, Luis Narvarte   +3 more
wiley   +1 more source

AΙ-Driven Drug Repurposing: Applications and Challenges. [PDF]

Medicines (Basel)
Keramida P, Syrigos NK, Kouvela M, Poulakou G, Charpidou A, Fiste O.   +5 more
europepmc   +1 more source

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

Advanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source

Evaluating the Role of Machine Learning and Artificial Intelligence in Oncology Drug Repurposing Efforts. [PDF]

J Res Pharm Pract
Mann A.
europepmc   +1 more source

Artificial Intelligence for Bone: Theory, Methods, and Applications

Advanced Intelligent Discovery, EarlyView.
Advances in artificial intelligence (AI) offer the potential to improve bone research. The current review explores the contributions of AI to pathological study, biomarker discovery, drug design, and clinical diagnosis and prognosis of bone diseases. We envision that AI‐driven methodologies will enable identifying novel targets for drugs discovery. The
Dongfeng Yuan, Haicang Zhang, Liping Tong, Di Chen   +3 more
wiley   +1 more source

Drug repurposing in cancer research: a bibliometric analysis. [PDF]

Discov Oncol
Ndidi US, Ogra IO, Jonathan EU, Iroha OK.   +3 more
europepmc   +1 more source

Accelerating Primary Screening of USP8 Inhibitors from Drug Repurposing Databases with Tree‐Based Machine Learning

Advanced Intelligent Discovery, EarlyView.
This study introduces a tree‐based machine learning approach to accelerate USP8 inhibitor discovery. The best‐performing model identified 100 high‐confidence repurposable compounds, half already approved or in clinical trials, and uncovered novel scaffolds not previously studied. These findings offer a solid foundation for rapid experimental follow‐up,
Yik Kwong Ng, Sharon Ai Er Lam, Wei Chun Lim, Hannah Hui Min Toh, Shi Jun Ang   +4 more
wiley   +1 more source

Skin‐Conformal Myography for Real‐Time Hand Tracking Using a Laser‐Induced Graphene Strain Sensor Array

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
A skin‐conformal wearable device based on laser‐induced graphene is developed for continuous strain measurement across the circumference of the forearm for gesture recognition and hand‐tracking applications. Post material optimization, the strain sensor array is integrated with a wearable wireless readout circuit for real‐time control of a robotic arm,
Vinay Kammarchedu, Monther AlSiyabi, Aida Ebrahimi   +2 more
wiley   +1 more source

Editorial: Opportunities and challenges in drug repurposing. [PDF]

Front Pharmacol
Camps I, Künzel SR, Schubert M, Singh RK.   +3 more
europepmc   +1 more source

Data‐Driven Insights into Rare Earth Mineralization: Machine Learning Applications Using Functional Material Synthesis Data

Advanced Intelligent Systems, EarlyView.
Hydrothermal synthesis records for rare‐earth compounds are repurposed to learn mineralization rules. An extreme gradient boosting model ingests precursors, additives, and engineered descriptors to predict product phases, crystallization temperature, and pH. Feature importance indicates dominant thermodynamic control with kinetic modulation, suggesting
Juejing Liu, Xiaoxu Li, Yifu Feng, Zheming Wang, Kevin M. Rosso, Xiaofeng Guo, Xin Zhang   +6 more
wiley   +1 more source