Artificial Intelligence (AI) driven patient assignment: optimizing daily redistribution among hospitalists. [PDF]
Save D, Tillu N.
europepmc +1 more source
An introduction for multidrive and environment‐adaptive micro/nanorobotics: design and fabrication strategies, intelligent actuation, and their applications. Various intelligent actuation approaches—magnetic, acoustic, optical, chemical, and biological—can be synergistically designed to enhance flexibility and adaptive behavior for precision medicine ...
Aiqing Ma +10 more
wiley +1 more source
Building Trust: Validating Artificial Intelligence (AI) and Machine Learning in Agricultural Applications. [PDF]
Riter LS, Bienstock RJ, O'Sullivan W.
europepmc +1 more source
The Future of Research in Cognitive Robotics: Foundation Models or Developmental Cognitive Models?
Research in cognitive robotics founded on principles of developmental psychology and enactive cognitive science would yield what we seek in autonomous robots: the ability to perceive its environment, learn from experience, anticipate the outcome of events, act to pursue goals, and adapt to changing circumstances without resorting to training with ...
David Vernon
wiley +1 more source
Assessment of mental and behavioural non-motor symptoms of Parkinson's Disease using Artificial Intelligence (AI): a systematic review. [PDF]
Chou SC +4 more
europepmc +1 more source
Hard‐Magnetic Soft Millirobots in Underactuated Systems
This review provides a comprehensive overview of hard‐magnetic soft millirobots in underactuated systems. It examines key advances in structural design, physics‐informed modeling, and control strategies, while highlighting the interplay among these domains.
Qiong Wang +4 more
wiley +1 more source
The role of artificial intelligence (AI) in the elimination of malaria: a systematic literature review. [PDF]
Kumar SM +10 more
europepmc +1 more source
Continual Learning for Multimodal Data Fusion of a Soft Gripper
Models trained on a single data modality often struggle to generalize when exposed to a different modality. This work introduces a continual learning algorithm capable of incrementally learning different data modalities by leveraging both class‐incremental and domain‐incremental learning scenarios in an artificial environment where labeled data is ...
Nilay Kushawaha, Egidio Falotico
wiley +1 more source
Artificial intelligence (AI) and machine learning (ML) in ovarian cancer: transforming detection, treatment, and prevention. [PDF]
Singh M, Betgeri SN, Kakar SS.
europepmc +1 more source

