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NDDNet: a deep learning model for predicting neurodegenerative diseases from gait pattern
(
Springer Nature
, 2023 , Article)
Neurodegenerative diseases damage neuromuscular tissues and deteriorate motor neurons which affects the motor capacity of the patient. Particularly the walking gait is greatly influenced by the deterioration process. Early ...
An Overview of Deep Learning Methods Used in Vibration-Based Damage Detection in Civil Engineering
(
Springer
, 2022 , Conference Paper)
This paper presents a brief overview of vibration-based damage identification studies based on Deep Learning (DL) in civil engineering structures. The presence, type, size, and propagation of structural damage on civil ...
Time-series forecasting of Bitcoin prices using high-dimensional features: a machine learning approach
(
Springer
, 2020 , Article)
© 2020, Springer-Verlag London Ltd., part of Springer Nature. Bitcoin is a decentralized cryptocurrency, which is a type of digital asset that provides the basis for peer-to-peer financial transactions based on blockchain ...
The utility of a deep learning-based approach in Her-2/neu assessment in breast cancer
(
Elsevier
, 2023 , Article)
IntroductionHER-2/neu is a protein present on the surface of specific cancer cells and has been linked to the development and progression of certain cancer types. It is present in 15 to 20% of breast cancers and is clinically ...
Second mesiobuccal canal segmentation with YOLOv5 architecture using cone beam computed tomography images
(
Springer
, 2023 , Article)
The objective of this study is to use a deep-learning model based on CNN architecture to detect the second mesiobuccal (MB2) canals, which are seen as a variation in maxillary molars root canals. In the current study, 922 ...
TB-CXRNet: Tuberculosis and Drug-Resistant Tuberculosis Detection Technique Using Chest X-ray Images
(
Springer Nature
, 2024 , Article)
Tuberculosis (TB) is a chronic infectious lung disease, which caused the death of about 1.5 million people in 2020 alone. Therefore, it is important to detect TB accurately at an early stage to prevent the infection and ...
Performance of artificial intelligence models in estimating blood glucose level among diabetic patients using non-invasive wearable device data
(
Elsevier
, 2023 , Article)
Introduction: Diabetes Mellitus (DM) is characterized by impaired ability to metabolize glucose for use in cells for energy, resulting in high blood sugar (hyperglycemia). DM impacted 463 million individuals worldwide in ...
Predicting emergency department utilization among children with asthma using deep learning models
(
Elsevier
, 2022 , Article)
Pediatric asthma is a leading cause of emergency department (ED) utilization, which is expensive and often preventable. Therefore, development of ED utilization predictive models that can accurately predict patients at ...
Self-ChakmaNet: A deep learning framework for indigenous language learning using handwritten characters
(
Elsevier
, 2023 , Article)
According to UNESCO's Atlas of the World's Languages in Danger, 40% of the languages today are counted as endangered in the future. Indigenous languages are endangered because of the less availability of interactive learning ...
AI and IoT-based concrete column base cover localization and degradation detection algorithm using deep learning techniques
(
Ain Shams University
, 2023 , Article)
Internet of Things (IoT) and Artificial Intelligence (AI) technologies are currently replacing the traditional methods of handling buildings, infrastructure, and facilities design, control, and maintenance due to their ...