AIMC Topic: Machine Learning

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ChatGPT for phenotypes extraction: one model to rule them all?

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Information Extraction (IE) is a core task in Natural Language Processing (NLP) where the objective is to identify factual knowledge in textual documents (often unstructured), and feed downstream use cases with the resulting output. In genomic medici...

Exploring artificial intelligence from a clinical perspective: A comparison and application analysis of two facial age predictors trained on a large-scale Chinese cosmetic patient database.

Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI)
BACKGROUND: Age prediction powered by artificial intelligence (AI) can be used as an objective technique to assess the cosmetic effect of rejuvenation surgery. Existing age-estimation models are trained on public datasets with the Caucasian race as t...

Deep transfer learning-based variable Doppler underwater acoustic communications.

The Journal of the Acoustical Society of America
This paper proposes a deep transfer learning (DTL)-based variable Doppler frequency-hopping binary frequency-shift keying underwater acoustic communication system. The system uses a convolutional neural network (CNN) as the demodulation module of the...

MOViDA: multiomics visible drug activity prediction with a biologically informed neural network model.

Bioinformatics (Oxford, England)
MOTIVATION: The process of drug development is inherently complex, marked by extended intervals from the inception of a pharmaceutical agent to its eventual launch in the market. Additionally, each phase in this process is associated with a significa...

Machine Learning for Analysis of Microscopy Images: A Practical Guide and Latest Trends.

Current protocols
The explosive growth of Machine Learning provided scientists with insights into the data in the ways unattainable using established research techniques. It allowed the detection of biological features that were previously unrecognized and overlooked....

In-situ and fast classification of origins of Baishao (Radix Paeoniae Alba) slices based on auto-focus laser-induced breakdown spectroscopy.

Optics letters
In this Letter, a rapid origin classification device and method for Baishao (Radix Paeoniae Alba) slices based on auto-focus laser-induced breakdown spectroscopy (LIBS) is proposed. The enhancement of spectral signal intensity and stability through a...

KG-Hub-building and exchanging biological knowledge graphs.

Bioinformatics (Oxford, England)
MOTIVATION: Knowledge graphs (KGs) are a powerful approach for integrating heterogeneous data and making inferences in biology and many other domains, but a coherent solution for constructing, exchanging, and facilitating the downstream use of KGs is...

Models That Link Physiology with Outcomes.

American journal of respiratory and critical care medicine

Building the Model.

Archives of pathology & laboratory medicine
CONTEXT.—: Machine learning (ML) allows for the analysis of massive quantities of high-dimensional clinical laboratory data, thereby revealing complex patterns and trends. Thus, ML can potentially improve the efficiency of clinical data interpretatio...