Deep learning and artificial intelligence methods for Raman and surface-enhanced Raman scattering

F Lussier, V Thibault, B Charron, GQ Wallace… - TrAC Trends in …, 2020 - Elsevier
Abstract Machine learning is shaping up our lives in many ways. In analytical sciences,
machine learning provides an unprecedented opportunity to extract information from …

Clinical applications of infrared and Raman spectroscopy in the fields of cancer and infectious diseases

M Paraskevaidi, BJ Matthew, BJ Holly… - Applied Spectroscopy …, 2021 - Taylor & Francis
Analytical technologies that can improve disease diagnosis are highly sought after. Current
screening/diagnostic tests for several diseases are limited by their moderate diagnostic …

Comparative analysis of image classification algorithms based on traditional machine learning and deep learning

P Wang, E Fan, P Wang - Pattern recognition letters, 2021 - Elsevier
Image classification is a hot research topic in today's society and an important direction in
the field of image processing research. SVM is a very powerful classification model in …

[HTML][HTML] Fish disease detection using image based machine learning technique in aquaculture

MS Ahmed, TT Aurpa, MAK Azad - … of King Saud University-Computer and …, 2022 - Elsevier
Fish diseases in aquaculture constitute a significant hazard to nutriment security.
Identification of infected fishes in aquaculture remains challenging to find out at the early …

Wayang Image Classification Using SVM Method and GLCM Feature Extraction

M Muhathir, MH Santoso, DA Larasati - Journal Of Informatics And …, 2021 - ojs.uma.ac.id
Wayang is a masterpiece of art that has been able to survive centuries of change and
development as a reflection of life for the majority of society. Wayang has a high value …

Machine learning applied to diagnosis of human diseases: A systematic review

N Caballé-Cervigón, JL Castillo-Sequera… - Applied Sciences, 2020 - mdpi.com
Human healthcare is one of the most important topics for society. It tries to find the correct
effective and robust disease detection as soon as possible to patients receipt the …

Component identification for the SERS spectra of microplastics mixture with convolutional neural network

Y Luo, W Su, D Xu, Z Wang, H Wu, B Chen… - Science of The Total …, 2023 - Elsevier
With the increasing interest in microplastics (MPs) pollutants, relevant detection
technologies are also developing. In MPs analysis, vibrational spectroscopy represented by …

Software defect prediction for healthcare big data: an empirical evaluation of machine learning techniques

B Khan, R Naseem, MA Shah, K Wakil… - Journal of …, 2021 - Wiley Online Library
Software defect prediction (SDP) in the initial period of the software development life cycle
(SDLC) remains a critical and important assignment. SDP is essentially studied during few …

A clinical decision-support system for dengue based on fuzzy cognitive maps

W Hoyos, J Aguilar, M Toro - Health care management science, 2022 - Springer
Dengue is a viral infection widely distributed in tropical and subtropical regions of the world.
Dengue is characterized by high fatality rates when the diagnosis is not made promptly and …

Dengue models based on machine learning techniques: A systematic literature review

W Hoyos, J Aguilar, M Toro - Artificial intelligence in medicine, 2021 - Elsevier
Background Dengue modeling is a research topic that has increased in recent years. Early
prediction and decision-making are key factors to control dengue. This Systematic Literature …