A systematic review of trustworthy and explainable artificial intelligence in healthcare: Assessment of quality, bias risk, and data fusion

AS Albahri, AM Duhaim, MA Fadhel, A Alnoor… - Information …, 2023‏ - Elsevier
In the last few years, the trend in health care of embracing artificial intelligence (AI) has
dramatically changed the medical landscape. Medical centres have adopted AI applications …

Explainable AI-driven IoMT fusion: Unravelling techniques, opportunities, and challenges with Explainable AI in healthcare

NA Wani, R Kumar, J Bedi, I Rida - Information Fusion, 2024‏ - Elsevier
Abstract Background and Objective: Artificial Intelligence (AI) has shown significant
advancements across several industries, including healthcare, using better fusion …

[HTML][HTML] AI for life: Trends in artificial intelligence for biotechnology

A Holzinger, K Keiblinger, P Holub, K Zatloukal… - New biotechnology, 2023‏ - Elsevier
Due to popular successes (eg, ChatGPT) Artificial Intelligence (AI) is on everyone's lips
today. When advances in biotechnology are combined with advances in AI unprecedented …

Real-time data visual monitoring of triboelectric nanogenerators enabled by deep learning

H Zhang, T Liu, X Zou, Y Zhu, M Chi, D Wu, K Jiang… - Nano Energy, 2024‏ - Elsevier
The rapid advancement of smart sensors and logic algorithms has propelled the widespread
adoption of the Internet of Things (IoT) and expedited the advent of the intelligent era. The …

A review on the recent applications of deep learning in predictive drug toxicological studies

K Sinha, N Ghosh, PC Sil - Chemical Research in Toxicology, 2023‏ - ACS Publications
Drug toxicity prediction is an important step in ensuring patient safety during drug design
studies. While traditional preclinical studies have historically relied on animal models to …

A trustworthy and explainable framework for benchmarking hybrid deep learning models based on chest X-ray analysis in CAD systems

AS Albahri, MM Jassim, L Alzubaidi… - … Journal of Information …, 2024‏ - World Scientific
Evaluating the trustworthiness of deep learning-based computer-aided diagnosis (CAD)
systems is challenging. There is a need to optimize trust and performance in model …

WS-LungNet: A two-stage weakly-supervised lung cancer detection and diagnosis network

Z Shen, P Cao, J Yang, OR Zaiane - Computers in Biology and Medicine, 2023‏ - Elsevier
Computer-aided lung cancer diagnosis (CAD) system on computed tomography (CT) helps
radiologists guide preoperative planning and prognosis assessment. The flexibility and …

A novel interactive deep cascade spectral graph convolutional network with multi-relational graphs for disease prediction

S Li, R Zhang - Neural Networks, 2024‏ - Elsevier
Graph neural networks (GNNs) have recently grown in popularity for disease prediction.
Existing GNN-based methods primarily build the graph topological structure around a single …

Development of PCA-MLP model based on visible and shortwave near infrared spectroscopy for authenticating Arabica coffee origins

A Dharmawan, RE Masithoh, HZ Amanah - Foods, 2023‏ - mdpi.com
Arabica coffee, one of Indonesia's economically important coffee commodities, is commonly
subject to fraud due to mislabeling and adulteration. In many studies, spectroscopic …

Improving performance of extreme learning machine for classification challenges by modified firefly algorithm and validation on medical benchmark datasets

N Bacanin, C Stoean, D Markovic, M Zivkovic… - Multimedia Tools and …, 2024‏ - Springer
The extreme learning machine (ELM) stands out as a contemporary neural network learning
model designed for neural networks, specifically emphasizing those with a single hidden …