Advancements in traditional machine learning techniques for detection and diagnosis of fatal cancer types: Comprehensive review of biomedical imaging datasets

HM Rai, J Yoo, SA Moqurrab, S Dashkevych - Measurement, 2024 - Elsevier
Accurate cancer detection and diagnosis are imperative for advancing patient outcomes and
mitigating mortality rates. This extensive review scrutinizes the progress within the domain of …

A bi-level data-driven framework for fault-detection and diagnosis of HVAC systems

P Movahed, S Taheri, A Razban - Applied Energy, 2023 - Elsevier
Long-term operation of heating, ventilation, and air conditioning (HVAC) systems will
eventually lead to a range of HVAC system failures, resulting in excessive energy …

Fusion of transfer learning models with LSTM for detection of breast cancer using ultrasound images

MG Lanjewar, KG Panchbhai, LB Patle - Computers in Biology and …, 2024 - Elsevier
Breast Cancer (BC) is one of the top reasons for fatality in women worldwide. As a result,
timely identification is critical for successful therapy and excellent survival rates. Transfer …

ML‐DDoSnet: IoT intrusion detection based on denial‐of‐service attacks using machine learning methods and NSL‐KDD

M Esmaeili, SH Goki, BHK Masjidi… - Wireless …, 2022 - Wiley Online Library
The Internet of Things (IoT) is a complicated security feature in which datagrams are
protected by integrity, confidentiality, and authentication services. The network is protected …

Automatic Liver Tumor Segmentation from CT Images Using Graph Convolutional Network

M Khoshkhabar, S Meshgini, R Afrouzian, S Danishvar - Sensors, 2023 - mdpi.com
Segmenting the liver and liver tumors in computed tomography (CT) images is an important
step toward quantifiable biomarkers for a computer-aided decision-making system and …

Reconstructing visual stimulus representation from EEG signals based on deep visual representation model

H Pan, Z Li, Y Fu, X Qin, J Hu - IEEE Transactions on Human …, 2024 - ieeexplore.ieee.org
Reconstructing visual stimulus representation is a significant task in neural decoding. Until
now, most studies have considered functional magnetic resonance imaging (fMRI) as the …

Acute Leukemia Diagnosis Based on Images of Lymphocytes and Monocytes Using Type-II Fuzzy Deep Network

S Ansari, AH Navin, A Babazadeh Sangar… - Electronics, 2023 - mdpi.com
A cancer diagnosis is one of the most difficult medical challenges. Leukemia is a type of
cancer that affects the bone marrow and/or blood and accounts for approximately 8% of all …

Miner fatigue detection from electroencephalogram-based relative power spectral topography using convolutional neural network

L Xu, J Li, D Feng - Sensors, 2023 - mdpi.com
Fatigue of miners is caused by intensive workloads, long working hours, and shift-work
schedules. It is one of the major factors increasing the risk of safety problems and work …

A cloud and IoT-enabled workload-aware Healthcare Framework using ant colony optimization algorithm

Z Lu, X Deng - … Journal of Advanced Computer Science and …, 2023 - search.proquest.com
In recent years, smart cities have gained in popularity due to their potential to improve the
quality of life for urban residents. In many smart city services, particularly those in the field of …

Nanocomposite of reduced nanographene oxide with β-lactoglobulin protein (rNGO/β-Lg) as a carrier of the anticancer drug oxaliplatin (Eloxatin)

YQ Almajidi, RH Althomali, MS Maashi, I Ahmad… - Diamond and Related …, 2023 - Elsevier
In this study, reduced nanographene oxide (rNGO) together with β-lactoglobulin (β-Lg)
protein is used for better and more effective encapsulation, loading and release of …