In the intelligent harvesting of eggplant, the lack of in situ identification technology makes it challenging to determine the maturity of purple eggplant fruit. The length of the fruit-setting date can determine when the eggplant is ready to be harv...
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2025
Machine learning is a powerful tool for analyzing biological data and making useful predictions. The surge of biological data from high-throughput omics technologies has raised the need for modeling approaches capable of tackling such amounts of data...
Studies in health technology and informatics
Aug 22, 2024
The significance of intracellular recording in neurophysiology is emphasized in this article, with considering the functions of neurons, particularly the role of first spike latency in response to external stimuli. The study employs advanced machine ...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
Frontotemporal dementia (FTD) is a progressive neurodegenerative disorder with a diverse range of symptoms, including personality changes, behavioral disturbances, language deficits, and impaired executive functions. FTD has three main subtypes: beha...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
Deep learning models are being adopted and applied across various critical medical tasks, yet they are primarily trained to provide point predictions without providing degrees of confidence. Medical practitioner's trustworthiness of deep learning mod...
The international journal of medical robotics + computer assisted surgery : MRCAS
Jun 1, 2024
BACKGROUND: Accurately estimating the 6D pose of snake-like wrist-type surgical instruments is challenging due to their complex kinematics and flexible design.
MOTIVATION: Mass spectrometry-based untargeted lipidomics aims to globally characterize the lipids and lipid-like molecules in biological systems. Ion mobility increases coverage and confidence by offering an additional dimension of separation and a ...
Machine learning models may outperform traditional statistical regression algorithms for predicting clinical outcomes. Proper validation of building such models and tuning their underlying algorithms is necessary to avoid over-fitting and poor genera...
Application of machine and deep learning methods in drug discovery and cancer research has gained a considerable amount of attention in the past years. As the field grows, it becomes crucial to systematically evaluate the performance of novel computa...
The superior performance of machine-learning scoring functions for docking has caused a series of debates on whether it is due to learning knowledge from training data that are similar in some sense to the test data. With a systematically revised met...