An explainable ai framework for artificial intelligence of medical things
The healthcare industry has been revolutionized by the convergence of Artificial Intelligence
of Medical Things (AIoMT), allowing advanced data-driven solutions to improve healthcare …
of Medical Things (AIoMT), allowing advanced data-driven solutions to improve healthcare …
Comparative analysis of entropy weight method and c5 classifier for predicting employee churn
M Chaudhary, L Gaur… - 2022 3rd International …, 2022 - ieeexplore.ieee.org
As per Aon, three out of four employees leave voluntarily, hence making employee churn
(EC) a key issue that has an adverse impact on the productivity and growth of the …
(EC) a key issue that has an adverse impact on the productivity and growth of the …
[HTML][HTML] An exploratory simulation study and prediction model on human brain behavior and activity using an integration of deep neural network and biosensor Rabi …
The plasmonic antenna probe is constructed using a silver rod embedded in a modified
Mach-Zehnder interferometer (MZI) ad-drop filter. Rabi antennas are formed when space …
Mach-Zehnder interferometer (MZI) ad-drop filter. Rabi antennas are formed when space …
[PDF][PDF] A Deep Transfer Learning Approach for Accurate Dragon Fruit Ripeness Classification and Visual Explanation using Grad-CAM.
Dragon fruit, known for its rich antioxidant content and low-calorie attributes, has garnered
significant attention as a health-promoting fruit. Its economic value has also surged due to …
significant attention as a health-promoting fruit. Its economic value has also surged due to …
Enhanced word vector space with ensemble deep learning model for COVID-19 Hindi text sentiment analysis
V Jain, KL Kashyap - Multimedia Tools and Applications, 2024 - Springer
The SARS-CoV-2 virus has spread worldwide since March 2020 and became a global
pandemic. Millions of people worldwide have infected with this virus. This research work …
pandemic. Millions of people worldwide have infected with this virus. This research work …
[图书][B] Explainable Artificial Intelligence for Intelligent Transportation Systems: Ethics and Applications
Transportation typically entails crucial “life-death” choices, delegating crucial decisions to an
AI algorithm without any explanation poses a serious threat. Hence, explainability and …
AI algorithm without any explanation poses a serious threat. Hence, explainability and …
[PDF][PDF] Explainable AI is Responsible AI: How Explainability Creates Trustworthy and Socially Responsible Artificial Intelligence
The need to develop AI in a way that benefits human life and societies has lead to the
emergence of responsible AI (RAI). RAI is fundamentally the field of applying ethics to the …
emergence of responsible AI (RAI). RAI is fundamentally the field of applying ethics to the …
[HTML][HTML] A diagnosis model for brain atrophy using deep learning and MRI of type 2 diabetes mellitus
Objective Type 2 Diabetes Mellitus (T2DM) is linked to cognitive deterioration and
anatomical brain abnormalities like cerebral brain atrophy and cerebral diseases. We aim to …
anatomical brain abnormalities like cerebral brain atrophy and cerebral diseases. We aim to …
Digital twin and healthcare research agenda and bibliometric analysis
A digital twin (DT) is a virtual representation of a physical object or activity that acts as its real-
time digital equivalent. The authors evaluated the structure of research in the same field, and …
time digital equivalent. The authors evaluated the structure of research in the same field, and …
DLGAN: Undersampled MRI reconstruction using Deep Learning based Generative Adversarial Network
Abstract Magnetic Resonance Imaging (MRI) is a crucial tool for quantitative image analysis
and clinical diagnosis, providing detailed anatomical images to assist in the detection of …
and clinical diagnosis, providing detailed anatomical images to assist in the detection of …