For an electronic nose (E-nose) in wound infection distinguishing, traditional learning methods have always needed large quantities of labeled wound infection samples, which are both limited and expensive; thus, we introduce self-taught learning comb...
IEEE journal of biomedical and health informatics
Sep 28, 2017
Non-invasive diabetes prediction has been gaining prominence over the last decade. Among many human serums evaluated, human breath emerges as a promising option with acetone levels in breath exhibiting a good correlation to blood glucose levels. Such...
Analysis of pesticide residues in irrigated rice grains is important for food security. In this study, we analyzed accelerated solvent extraction (ASE) conditions for the extraction of thiamethoxam and chlorantraniliprole insecticides from rice hulls...
Gas sensors combined with artificial intelligence capable of distinguishing multiple odors hold great promise in volatile organic compounds (VOCs) discriminative detection. However, various issues such as large size, high expenses, and mutual interfe...
There is an increasing need for exposure data to enable more precise information for risk estimates and improved public health protection. While personal monitoring data are preferred, it is often difficult to collect due to the resources needed to c...
Impedimetric biosensors for measuring small molecules based on weak/transient interactions between bioreceptors and target analytes are a challenge for detection electronics, particularly in field studies or in the analysis of complex matrices. Prote...
OBJECTIVE: In the Mexican ethno-medicine, a number of plants have shown a successful anthelmintic activity. This fact could be crucial to identify possible green anti-parasitic strategies against nematodes affecting animal production. This research e...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.