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A systematic review of trustworthy and explainable artificial intelligence in healthcare: Assessment of quality, bias risk, and data fusion
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 …
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
Abstract Background and Objective: Artificial Intelligence (AI) has shown significant
advancements across several industries, including healthcare, using better fusion …
advancements across several industries, including healthcare, using better fusion …
[HTML][HTML] AI for life: Trends in artificial intelligence for biotechnology
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 …
today. When advances in biotechnology are combined with advances in AI unprecedented …
Real-time data visual monitoring of triboelectric nanogenerators enabled by deep learning
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 …
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
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 …
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
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 …
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
Computer-aided lung cancer diagnosis (CAD) system on computed tomography (CT) helps
radiologists guide preoperative planning and prognosis assessment. The flexibility and …
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
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 …
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
Arabica coffee, one of Indonesia's economically important coffee commodities, is commonly
subject to fraud due to mislabeling and adulteration. In many studies, spectroscopic …
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
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 …
model designed for neural networks, specifically emphasizing those with a single hidden …