[HTML][HTML] A critical review of recent trends in sample classification using Laser-Induced Breakdown Spectroscopy (LIBS)

L Brunnbauer, Z Gajarska, H Lohninger… - TrAC Trends in Analytical …, 2023 - Elsevier
LIBS-based classification has experienced an ever-increasing interest in the last few years.
LIBS is a well-suited technique for classification tasks based on elemental fingerprinting …

Review on the photonic techniques suitable for automatic monitoring of the composition of multi-materials wastes in view of their posterior recycling

C Araujo-Andrade, E Bugnicourt… - Waste management …, 2021 - journals.sagepub.com
In the increasingly pressing context of improving recycling, optical technologies present a
broad potential to support the adequate sorting of plastics. Nevertheless, the commercially …

Application of deep transfer learning for automated brain abnormality classification using MR images

M Talo, UB Baloglu, Ö Yıldırım, UR Acharya - Cognitive Systems Research, 2019 - Elsevier
Magnetic resonance imaging (MRI) is the most common imaging technique used to detect
abnormal brain tumors. Traditionally, MRI images are analyzed manually by radiologists to …

[PDF][PDF] Novel deep genetic ensemble of classifiers for arrhythmia detection using ECG signals

P Pławiak, UR Acharya - Neural Comput. Appl, 2020 - researchgate.net
The heart disease is one of the most serious health problems in today's world. Over 50
million persons have cardiovascular diseases around the world. Our proposed work based …

Application of new deep genetic cascade ensemble of SVM classifiers to predict the Australian credit scoring

P Pławiak, M Abdar, UR Acharya - Applied Soft Computing, 2019 - Elsevier
In the recent decades, credit scoring has become a very important analytical resource for
researchers and financial institutions around the world. It helps to boost both profitability and …

LDA–GA–SVM: improved hepatocellular carcinoma prediction through dimensionality reduction and genetically optimized support vector machine

L Ali, I Wajahat, N Amiri Golilarz, F Keshtkar… - Neural Computing and …, 2021 - Springer
Hepatocellular carcinoma (HCC) is a common type of liver cancer worldwide. Patients with
HCC have rare chances of survival. The chances of survival increase, if the cancer is …

A novel machine learning approach for early detection of hepatocellular carcinoma patients

W Książek, M Abdar, UR Acharya, P Pławiak - Cognitive Systems Research, 2019 - Elsevier
Liver cancer is quite common type of cancer among individuals worldwide. Hepatocellular
carcinoma (HCC) is the malignancy of liver cancer. It has high impact on individual's life and …

Automated Parkinson's disease recognition based on statistical pooling method using acoustic features

O Yaman, F Ertam, T Tuncer - Medical hypotheses, 2020 - Elsevier
Parkinson's disease is one of the mostly seen neurological disease. It affects to nervous
system and hinders people's vital activities. The majority of Parkinson's patients lose their …

A brief review of new data analysis methods of laser-induced breakdown spectroscopy: machine learning

D Zhang, H Zhang, Y Zhao, Y Chen, C Ke… - Applied Spectroscopy …, 2022 - Taylor & Francis
Laser-induced breakdown spectroscopy (LIBS) is a technology of content analysis and
composition analysis based on the atomic excitation and emission spectrum of materials. It …

Identifying traffic context using driving stress: A longitudinal preliminary case study

OV Bitkina, J Kim, J Park, J Park, HK Kim - Sensors, 2019 - mdpi.com
Many previous studies have identified that physiological responses of a driver are
significantly associated with driving stress. However, research is limited to identifying the …