scholarly journals Noninvasive Early Disease Diagnosis by Electronic-Nose and Related VOC-Detection Devices

Biosensors ◽  
2020 ◽  
Vol 10 (7) ◽  
pp. 73 ◽  
Author(s):  
Alphus Dan Wilson
Keyword(s):  
Early Detection ◽  
Electronic Nose ◽  
Disease Diagnosis ◽  
Plant Diseases ◽  
Research Articles ◽  
Special Issue ◽  
Early Disease ◽  
Invasive Pests ◽  
Detection And Diagnosis ◽  
Voc Detection

This editorial provides an overview and summary of recent research articles published in Biosensors journal, volumes 9 (2019) and 10 (2020), within the Special Issue “Noninvasive Early Disease Diagnosis”, which focused on recent sensors, biosensors, and clinical instruments developed for the noninvasive early detection and diagnosis of human, animal, and plant diseases or invasive pests. The six research articles included in this Special Issue provide examples of some of the latest electronic-nose (e-nose) and related volatile organic compound (VOC)-detection technologies, which are being tested and developed to improve the effectiveness and efficiency of innovative diagnostic methodologies for the early detection of particular diseases and pest infestations in living hosts, prior to symptom development.

scholarly journals SALIVA AND SALIVAOMICS IN THE DIAGNOSIS OF ORAL AND SYSTEMIC DISEASES: A REVIEW

2021 ◽  
pp. 8-12
Author(s):  
Sherly Ruth ◽  
Koduri Sridevi ◽  
Buduru Krishnaveni ◽  
Nalli Prasanth Kumar ◽  
Katru Sreekar ◽  
...  
Keyword(s):  
Health Care ◽  
Early Detection ◽  
Patient Care ◽  
Disease Diagnosis ◽  
Response To Therapy ◽  
Response To Treatment ◽  
Systemic Diseases ◽  
Early Disease ◽  
Early Disease Detection ◽  
Salivary Diagnostics

The quest for novel strategies in early disease detection and response to therapy is an essential ongoing process in health care setups.Along with other body fluids such as blood,mucus,urine,semen and vaginal fluids;saliva can also be considered for the detection of the disease.The Salivary diagnostics is a dynamic field that is being incorporated as part of disease diagnosis, clinical monitoring and for making important clinical decisions for patient care. This review presents the translational value of saliva as a credible clinical diagnostic biofluid in detection, early detection of the various diseases and response to treatment.

scholarly journals Ultra-low concentration protein detection based on phenylalanine–Pd/SWCNT as a high sensitivity nanoreceptor

RSC Advances ◽  
2020 ◽  
Vol 10 (5) ◽  
pp. 2650-2660 ◽  
Author(s):  
Mehdi Yoosefian ◽  
Nazanin Etminan ◽  
Alfredo Juan ◽  
Elnaz Mirhaji
Keyword(s):  
Amino Acid ◽  
Early Detection ◽  
Protein Detection ◽  
High Sensitivity ◽  
Disease Diagnosis ◽  
Early Disease ◽  
Low Concentration ◽  
Disease Progress

Early detection of proteins could help to reduce disease progress. The amino acid hybrid with the Pd/SWCNT supporting enhanced transducer provides a high sensitivity biocompatible bioelectrode in nanobiosensors for use in early disease diagnosis.

scholarly journals Special issue on invasive pests of forests and urban trees: pathways, early detection, and management

2019 ◽  
Vol 92 (1) ◽  
pp. 1-2 ◽  
Author(s):  
Jon Sweeney ◽  
Davide Rassati ◽  
Nicolas Meurisse ◽  
Brett Hurley ◽  
Jian Duan ◽  
...  
Keyword(s):  
Early Detection ◽  
Urban Trees ◽  
Special Issue ◽  
Invasive Pests

scholarly journals Machine Learning-Based Presymptomatic Detection of Rice Sheath Blight Using Spectral Profiles

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Anna O. Conrad ◽  
Wei Li ◽  
Da-Young Lee ◽  
Guo-Liang Wang ◽  
Luis Rodriguez-Saona ◽  
...  
Keyword(s):  
Machine Learning ◽  
Early Detection ◽  
Disease Diagnosis ◽  
Sheath Blight ◽  
Machine Learning Algorithms ◽  
Plant Diseases ◽  
Support Vector ◽  
Rice Sheath Blight ◽  
Spectral Profiles ◽  
Testing Accuracy

Early detection of plant diseases, prior to symptom development, can allow for targeted and more proactive disease management. The objective of this study was to evaluate the use of near-infrared (NIR) spectroscopy combined with machine learning for early detection of rice sheath blight (ShB), caused by the fungus Rhizoctonia solani. We collected NIR spectra from leaves of ShB-susceptible rice (Oryza sativa L.) cultivar, Lemont, growing in a growth chamber one day following inoculation with R. solani, and prior to the development of any disease symptoms. Support vector machine (SVM) and random forest, two machine learning algorithms, were used to build and evaluate the accuracy of supervised classification-based disease predictive models. Sparse partial least squares discriminant analysis was used to confirm the results. The most accurate model comparing mock-inoculated and inoculated plants was SVM-based and had an overall testing accuracy of 86.1% (N=72), while when control, mock-inoculated, and inoculated plants were compared the most accurate SVM model had an overall testing accuracy of 73.3% (N=105). These results suggest that machine learning models could be developed into tools to diagnose infected but asymptomatic plants based on spectral profiles at the early stages of disease development. While testing and validation in field trials are still needed, this technique holds promise for application in the field for disease diagnosis and management.

scholarly journals Intelligent Health Services Based on Biomedical Smart Sensors

2020 ◽  
Vol 10 (23) ◽  
pp. 8497
Author(s):  
Ricardo Colomo-Palacios ◽  
Juan A. Gómez-Pulido ◽  
Alfredo J. Pérez
Keyword(s):  
Internet Of Things ◽  
Health Services ◽  
Data Science ◽  
Disease Diagnosis ◽  
Research Articles ◽  
Smart Sensors ◽  
Special Issue ◽  
Human Welfare ◽  
Oriented Area ◽  
Advanced Technologies

Health services can be improved by means of intelligent techniques that handle efficiently massive volumes of data collected from biomedical variables. Nowadays, these services are not only oriented to disease diagnosis and prevention, but wellness too. Advanced technologies and last trends in computing, internet of things, sensors, and data science are driving the development of new systems and applications in the area of intelligent health services based on biomedical smart sensors that deserve to be known. Through five research articles and a review, this Special Issue provides the opportunity to obtain a representative view of the potential of these technologies when applied to such a human welfare-oriented area.

Detection of Leukemia Using Image Processing

2018 ◽  
Vol 8 (4) ◽  
pp. 61
Author(s):  
A. Sivasangari ◽  
G. Sasikumar
Keyword(s):  
Image Processing ◽  
Statistical Analysis ◽  
Early Detection ◽  
Visual Inspection ◽  
Causes Of Death ◽  
Cure Rate ◽  
Blood Disorders ◽  
Detection And Diagnosis ◽  
The Moment ◽  
Early Detection And Diagnosis

Leukemia   disease   is one   of    the   leading   causes   of death   among   human. Its  cure  rate and  prognosis   depends   mainly   on  the  early  detection   and  diagnosis  of   the  disease. At  the  moment, identification  of  blood  disorders  is  through   visual  inspection  of  microscopic  images  by  examining  changes  like  texture, geometry, colour  and   statistical  analysis  of  images . This  project  aims  to  preliminary  of  developing  a  detection  of  leukemia  types  using   microscopic  blood  sample using MATLAB. Images  are  used  as  they  are  cheap  and  do  not  expensive  for testing  and  lab  equipment.

scholarly journals Recent Advances in Kinase Drug Discovery Part I: The Editors’ Take

2021 ◽  
Vol 22 (14) ◽  
pp. 7560
Author(s):  
Julie A. Tucker ◽  
Mathew P. Martin
Keyword(s):  
Drug Discovery ◽  
Research Articles ◽  
Special Issue ◽  
Recent Advances ◽  
Enzyme Family ◽  
Selection Of

This special issue on Advances in Kinase Drug Discovery provides a selection of research articles and topical reviews covering all aspects of drug discovery targeting the phosphotransferase enzyme family [...]

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