Single-cell delivery platforms like microinjection and nanoprobe electroporation enable unparalleled control over cell manipulation tasks but are generally limited in throughput. Here, we present an automated single-cell electroporation system capabl...
The data processing efficiency of traditional computers is suffering from the intrinsic limitation of physically separated processing and memory units. Logic-in-memory and brain-inspired neuromorphic computing are promising in-memory computing paradi...
Medical & biological engineering & computing
Jan 8, 2021
Rheumatoid arthritis (RA) is an autoimmune disorder that typically affects people between 23 and 60 years old causing chronic synovial inflammation, symmetrical polyarthritis, destruction of large and small joints, and chronic disability. Clinical di...
Insect monitoring methods are typically very time-consuming and involve substantial investment in species identification following manual trapping in the field. Insect traps are often only serviced weekly, resulting in low temporal resolution of the ...
Alzheimer's disease (AD) is the most prevalent neurodegenerative disease causing dementia and poses significant health risks to middle-aged and elderly people. Brain magnetic resonance imaging (MRI) is the most widely used diagnostic method for AD. H...
IEEE transactions on biomedical circuits and systems
Dec 31, 2020
The advent of dedicated Deep Learning (DL) accelerators and neuromorphic processors has brought on new opportunities for applying both Deep and Spiking Neural Network (SNN) algorithms to healthcare and biomedical applications at the edge. This can fa...
With the popularity of smart wearable systems, sensor signal processing poses more challenges to machine learning in embedded scenarios. For example, traditional machine-learning methods for data classification, especially in real time, are computati...
Journal of chemical information and modeling
Nov 10, 2020
A machine learning enhanced spectrum recognition system called spectrum recognition based on computer vision (SRCV) for data extraction from previously analyzed C and H NMR spectra has been developed. The intelligent system was designed with four fun...
Live sheep export has become a public concern. This study aimed to test a non-contact biometric system based on artificial intelligence to assess heat stress of sheep to be potentially used as automated animal welfare assessment in farms and while in...
Patient-reported assessments are transforming many facets of health care, but there is scope to modernize their delivery. Contemporary assessment techniques like computerized adaptive testing (CAT) and machine learning can be applied to patient-repor...