Digital twins for well-being: an overview
Digital twin (DT) has gained success in various industries, and it is now getting attention in
the healthcare industry in the form of well-being digital twin (WDT). In this paper, we present …
the healthcare industry in the form of well-being digital twin (WDT). In this paper, we present …
Green synthesis of silver nanoparticles using Eulophia herbacea (Lindl.) tuber extract and evaluation of its biological and catalytic activity
The present work is a report on phytosynthesis of silver nanoparticles (AgNPs) carried out
using an aqueous extract of the tuber of Eulophia herbacea Lindl.(Orchidaceae) and …
using an aqueous extract of the tuber of Eulophia herbacea Lindl.(Orchidaceae) and …
A brief review of explainable artificial intelligence in healthcare
XAI refers to the techniques and methods for building AI applications which assist end users
to interpret output and predictions of AI models. Black box AI applications in high-stakes …
to interpret output and predictions of AI models. Black box AI applications in high-stakes …
Monkeypox diagnosis with interpretable deep learning
As the world gradually recovers from the impacts of COVID-19, the recent global spread of
Monkeypox disease has raised concerns about another potential pandemic, highlighting the …
Monkeypox disease has raised concerns about another potential pandemic, highlighting the …
[PDF][PDF] Incorporating Explainable Artificial Intelligence (XAI) to aid the Understanding of Machine Learning in the Healthcare Domain.
In the healthcare domain, Artificial Intelligence (AI) based systems are being increasingly
adopted with applications ranging from surgical robots to automated medical diagnostics …
adopted with applications ranging from surgical robots to automated medical diagnostics …
A comparison of explanations given by explainable artificial intelligence methods on analysing electronic health records
eXplainable Artificial Intelligence (XAI) aims to provide intelligible explanations to users. XAI
algorithms such as SHAP, LIME and Scoped Rules compute feature importance for machine …
algorithms such as SHAP, LIME and Scoped Rules compute feature importance for machine …
Artificial intelligence in cardiovascular imaging:“unexplainable” legal and ethical challenges?
M Lang, A Bernier, BM Knoppers - Canadian Journal of Cardiology, 2022 - Elsevier
Nowhere is the influence of artificial intelligence (AI) likely to be more profoundly felt than in
health care, from patient triage and diagnosis to surgery and follow-up. Over the medium …
health care, from patient triage and diagnosis to surgery and follow-up. Over the medium …
A taxonomy of explainable Bayesian networks
IP Derks, A De Waal - … Research: First Southern African Conference for AI …, 2020 - Springer
Artificial Intelligence (AI), and in particular, the explainability thereof, has gained
phenomenal attention over the last few years. Whilst we usually do not question the decision …
phenomenal attention over the last few years. Whilst we usually do not question the decision …
Explainability of deep learning models in medical video analysis: a survey
Deep learning methods have proven to be effective for multiple diagnostic tasks in medicine
and have been performing significantly better in comparison to other traditional machine …
and have been performing significantly better in comparison to other traditional machine …
XAI robot-assisted surgeries in future medical decision support systems
Artificial intelligence (AI) models are gaining widespread applications in various areas such
as the healthcare system, especially robotic surgeries. The output of these models needs to …
as the healthcare system, especially robotic surgeries. The output of these models needs to …