Estonia
October 9, 2023
HUMA
October 15, 20232015 – 2016
Lexical Patterns in Biological Ontologies Boost Axiomatization
In 2015, the metrics revealed details on the engineering of the ontologies and the applicability of the patterns. By prioritizing lexical patterns, connections between classes implicit in the ontology can be suggested. The localization and distribution of lexical patterns might provide insights into the ontology’s subsequent engineering thanks to the priority of the lexical patterns observed in the examined ontologies. Developers can use this knowledge to enhance the axiomatization of their ontologies. (1)
New information on the design of biomedical ontologies provides credence to the idea that the lexical approach can help axiomatically enrich biomedical ontologies. With the usage of data on precise matches in external ontologies, the approach with a cross-products extension (CPE) metric was expanded to quantify the potential interest of a particular regularity for axiomatic enrichment in the lexical analysis. Axioms that link classes from the GO or other biological ontologies to a specific GO class are used to create cross-products. In lexical terms, the GO classes’ labels are very regular, and 80% of them have labels that are precise matches to labels from external ontologies. The CPE measure shows that 31.48% of the classes that show regularities have fractured into the Cell Ontology and the Chemical Entities of Biological Interest ontology, two external ontologies chosen, and 18.90% are entirely decomposable into smaller sections. The findings demonstrated that the approach can identify GO cross-product extensions with a mean recall of 62% and a mean precision of 28% when using the CPE metric. (2)
New information on the design of biomedical ontologies provides credence to the idea that the lexical approach can help axiomatically enrich biomedical ontologies. With the usage of data on precise matches in external ontologies, the approach with a cross-products extension (CPE) metric was expanded to quantify the potential interest of a particular regularity for axiomatic enrichment in the lexical analysis. Axioms that link classes from the GO or other biological ontologies to a specific GO class are used to create cross-products. In lexical terms, the GO classes’ labels are very regular, and 80% of them have labels that are precise matches to labels from external ontologies.
The CPE measure shows that 31.48% of the classes that show regularities have fractured into the Cell Ontology and the Chemical Entities of Biological Interest ontology, two external ontologies chosen, and 18.90% are entirely decomposable into smaller sections. The findings demonstrated that the approach can identify GO cross-product extensions with a mean recall of 62% and a mean precision of 28% when using the CPE metric. (2)
Mobile Stroke Units Invention
Moreover, in 2016, a unique ambulance equipped with specialized technology to diagnose and treat acute stroke in a prehospital setting was created, called Mobile Stroke Units (MSUs). MSU is one of the few proven interventions to treat acute strokes, along with intravenous thrombolysis and stroke units. In the future, stroke leaders and organizations should include this technology in their protocols to benefit the patient’s safety and shorten the time they receive treatment. (3)
Wireless Wearable Sensors Start-Up
Wearable chemical sensing has become an important appliance area for wireless sensors. This multidisciplinary area has proved to be very challenging. The most acknowledgeable benefit of these sensors is that they have the capability to couple communication to different types of wearable devices and obtain real-time data. Wearable electrochemical sensors facilitate acquiring a new perspective into individuals’ health status. This insight is achieved through noninvasive monitoring of clinically relevant biomarkers by analyzing various biofluids without complex sampling, manipulation, and treatment steps. (4)
Wireless Wearable Sensors Start-Up
Wearable chemical sensing has become an important appliance area for wireless sensors. This multidisciplinary area has proved to be very challenging. The most acknowledgeable benefit of these sensors is that they have the capability to couple communication to different types of wearable devices and obtain real-time data. Wearable electrochemical sensors facilitate acquiring a new perspective into individuals’ health status.
This insight is achieved through noninvasive monitoring of clinically relevant biomarkers by analyzing various biofluids without complex sampling, manipulation, and treatment steps. (4)
References