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Now showing items 11-20 of 21
Deep Learning-Based Conjunctival Melanoma Detection Using Ocular Surface Images
(
springer link
, 2023 , Article)
The human eye could be affected with conjunctival melanoma, which indicates a fatal malignant growth of the eye. Being a very rare disease, there exists a lack of related data in the literature. Also, very few studies ...
RamanNet: a generalized neural network architecture for Raman spectrum analysis
(
Springer Science and Business Media Deutschland GmbH
, 2023 , Article)
Raman spectroscopy provides a vibrational profile of the molecules and thus can be used to uniquely identify different kinds of materials. This sort of molecule fingerprinting has thus led to the widespread application of ...
BIO-CXRNET: a robust multimodal stacking machine learning technique for mortality risk prediction of COVID-19 patients using chest X-ray images and clinical data
(
Springer Science and Business Media Deutschland GmbH
, 2023 , Article)
Nowadays, quick, and accurate diagnosis of COVID-19 is a pressing need. This study presents a multimodal system to meet this need. The presented system employs a machine learning module that learns the required knowledge ...
Development of deep learning framework to predict physicochemical properties for Ionic liquids
(
Elsevier
, 2023 , Book chapter)
In this paper, a deep learning-based group contribution approach has been developed to identify the optimum structure for ionic liquids (ILs) and to maximize the CO2 absorption capacity. The suggested methodology demonstrates ...
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 ...
Estimating Blood Glucose Levels Using Machine Learning Models with Non-Invasive Wearable Device Data
(
IOS Press BV
, 2023 , Conference Paper)
In 2019 alone, Diabetes Mellitus impacted 463 million individuals worldwide. Blood glucose levels (BGL) are often monitored via invasive techniques as part of routine protocols. Recently, AI-based approaches have shown the ...
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 ...
Using artificial intelligence to improve body iron quantification: A scoping review
(
Elsevier
, 2023 , Article Review)
This scoping review explores the potential of artificial intelligence (AI) in enhancing the screening, diagnosis, and monitoring of disorders related to body iron levels. A systematic search was performed to identify studies ...
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 ...
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 ...